{"type": "FeatureCollection", "features": [{"id": "10.1007/s10113-020-01617-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:15:12Z", "type": "Journal Article", "created": "2020-02-28", "title": "Future soil loss in highland Ethiopia under changing climate and land use", "description": "Soil erosion caused by climate and land-use changes is one of the biggest environmental challenges in highland Ethiopia. The aim of this study was to assess the future soil erosion risks and evaluate the potential conservation measures in the Rib watershed, northwestern highland Ethiopia. We used the HadGEM2-ES model with a moderate greenhouse gas (GHG) concentration scenario (RCP4.5) to project the future climate. The future land-use patterns were predicted using the CA-Markov model. We integrated the RUSLE model with GIS to estimate the spatial distribution of soil loss and identify erosion risk areas. We found that the Rib watershed is highly vulnerable to future climate and land-use changes, leading to a high soil erosion risk. Despite slight growth of forest cover during the study period, the total soil loss for the watershed was estimated to be 7.93\u2009\u00d7\u2009106\u00a0t\u00a0year\u22121 in 2017 and was predicted to increase to 9.75\u2009\u00d7\u2009106\u00a0t\u00a0year\u22121 in 2050, an increase of about 23%. The increase in forest cover was due to the expansion of the area of eucalyptus plantations which are more prone to erosion. Moreover, field survey showed that the residual native forests are sparsely vegetated and mostly used for cattle grazing, increasing the erosion risk even more. In contrast, the combined use of afforestation with native trees and physical soil conservation measures in the upper areas of the catchment could decrease soil loss by 62%. Our results stress the importance of combining soil conservation measures, including converting eucalyptus plantations to native forests, to mitigate the effects of future climate change and increased agricultural production on soil erosion.", "keywords": ["2. Zero hunger", "13. Climate action", "HadGEM2-ES model", "Modeling", "Nature-based solutions", "CA-Markov model", "0401 agriculture", " forestry", " and fisheries", "RUSLE model", "04 agricultural and veterinary sciences", "15. Life on land", "GIS", "6. Clean water"]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s10113-020-01617-6.pdf"}, {"href": "https://doi.org/10.1007/s10113-020-01617-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Regional%20Environmental%20Change", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10113-020-01617-6", "name": "item", "description": "10.1007/s10113-020-01617-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10113-020-01617-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-02-28T00:00:00Z"}}, {"id": "10.1007/s10457-011-9442-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:15:15Z", "type": "Journal Article", "created": "2011-11-02", "title": "Modeling The Impacts Of Agroforestry Systems On The Spatial Patterns Of Soil Erosion Risk In Three Catchments Of Claveria, The Philippines", "description": "Agroforestry is one of the preferred land-use options for smallholder farms in tropical landscapes due to its ability to increase land productivity and protect soil from erosion. We investigated the impacts of agroforestry and traditional monocropping systems on the spatial patterns of soil erosion risk in three catchment areas of Claveria, the Philippines, using WaTEM/SEDEM, a spatially distributed soil erosion model. The model predicts soil loss in catchments based on the Revised Universal Soil Loss Equation (RUSLE) by taking into account the influences of rainfall, soil erodibility, vegetation cover and 2-dimensional variations in landscape structure. The predicted soil erosion rates were transformed into risk values in order to identify areas with higher risk for erosion. Model results indicate a large spatial variability in soil erosion risk patterns, with higher risks occurring on slopes greater than 8% on land under non-agroforestry use. The soil erosion risk maps were used to formulate site-specific agroforestry recommendations for future landscape amelioration plans.", "keywords": ["2. Zero hunger", "soil erosion", "13. Climate action", "upland areas", "RUSLE", "WaTEM/SEDEM", "the Philippines", "15. Life on land", "01 natural sciences", "land-use planning", "tropical region", "agroforestry", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Delgado, Marc, Canters, Frank,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/s10457-011-9442-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agroforestry%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10457-011-9442-z", "name": "item", "description": "10.1007/s10457-011-9442-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10457-011-9442-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-11-02T00:00:00Z"}}, {"id": "10.1007/s12145-018-0349-3", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:15:46Z", "type": "Journal Article", "created": "2018-05-30", "title": "An integrated method for calculating DEM-based RUSLE LS", "description": "The improvement of resolution of digital elevation models (DEMs) and the increasing application of the Revised Universal Soil Loss Equation (RUSLE) over large areas have created problems for the efficiency of calculating the LS factor for large data sets. The pretreatment for flat areas, flow accumulation, and slope-length calculation have traditionally been the most time-consuming steps. However, obtaining these features are generally usually considered as separate steps, and calculations still tend to be time-consuming. We developed an integrated method to improve the efficiency of calculating the LS factor. The calculation model contains algorithms for calculating flow direction, flow accumulation, slope length, and the LS factor. We used the Deterministic 8 method to develop flow-direction octrees (FDOTs), flat matrices (FMs) and first-in-first-out queues (FIFOQs) tracing the flow path. These data structures were much more time-efficient for calculating the slope length inside the flats, the flow accumulation, and the slope length linearly by traversing the FDOTs from their leaves to their roots, which can reduce the search scope and data swapping. We evaluated the accuracy and effectiveness of this integrated algorithm by calculating the LS factor for three areas of the Loess Plateau in China and SRTM DEM of China. The results indicated that this tool could substantially improve the efficiency of LS-factor calculations over large areas without reducing accuracy.", "keywords": ["Revised universal soil loss equation (RUSLE)", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "0101 mathematics", "15. Life on land", "Geographic information system (GIS)", "01 natural sciences", "LS factor"], "contacts": [{"organization": "Wang, Meng, Baartman, Jantiene E.M., Zhang, Hongming, Yang, Qinke, Li, Shuqin, Yang, Jiangtao, Cai, Cheng, Wang, Meili, Ritsema, Coen J., Geissen, Violette,", "roles": ["creator"]}]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s12145-018-0349-3.pdf"}, {"href": "https://doi.org/10.1007/s12145-018-0349-3"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20Science%20Informatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s12145-018-0349-3", "name": "item", "description": "10.1007/s12145-018-0349-3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s12145-018-0349-3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-30T00:00:00Z"}}, {"id": "10.1016/j.catena.2024.108420", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:16:21Z", "type": "Journal Article", "created": "2024-10-09", "title": "Exploring the RUSLE-based structural sediment connectivity approach for agricultural erosion management", "description": "Models play a crucial role in guiding agricultural erosion management, though their incorporation of sediment connectivity and management strategies varies. This study evaluated the RUSLE/IC/SDR model\u2019s potential for simulating agricultural erosion management at both the field scale and across two catchments. We tested the model\u2019s ability to simulate erosion management measures at a high spatial resolution (2 m \u00d7 2 m) across diverse topographies, assessed whether incorporating sediment connectivity improves RUSLE-based erosion management planning within catchments, and explored its capacity to tailor measures based on local connectivity characteristics. Our findings showed significant variability in sediment sources and connectivity. The simulation of no-till and buffer strip measures effectively demonstrated their varying effectiveness across fields and catchments. At the catchment scale, erosion management planning that incorporates sediment connectivity through the RUSLE/IC/SDR approach did not contribute to significant additional sediment delivery reduction compared to using RUSLE alone. However, at the field scale, RUSLE/IC/SDR offered improved opportunities for tailoring erosion management measures to local sediment connectivity characteristics. These simulations highlight both the potential and limitations of RUSLE/IC/SDR, advancing our understanding of its application for erosion management. In conclusion, while RUSLE/IC/SDR represents a valuable extension of RUSLE, further research is needed to fully realize its practical applications. Nonetheless, it shows promise for high-resolution simulation of sediment connectivity and erosion management at the field scale, across large catchments and regions.", "keywords": ["550", "Erosion", "RUSLE", "Agriculture", "Sediment connectivity", "Erosion management"]}, "links": [{"href": "https://doi.org/10.1016/j.catena.2024.108420"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/CATENA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.catena.2024.108420", "name": "item", "description": "10.1016/j.catena.2024.108420", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.catena.2024.108420"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-11-01T00:00:00Z"}}, {"id": "10.1016/j.catena.2021.105818", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:16:21Z", "type": "Journal Article", "created": "2021-11-13", "title": "An optimized method for extracting slope length in RUSLE from raster digital elevation", "description": "Abstract   The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) have been widely used for predicting average soil loss. Slope length is an important topographical parameter of the L factor in USLE/RUSLE. Among the widely studied GIS procedures for extracting slope length, the distributed watershed erosion slope length (DWESL) based on the unit contributing area estimation method, which considers two-dimensional runoff process and cutoff factors, is a relatively complete model for calculating slope length. Slope length in the DWESL model is primarily calculated using conventional flow direction algorithms such as D8, Dinf, MS and MFD-md. However, DWESL outputs require further improvement due to the errors in the usual estimates of the uphill contributing area and the effective contour length of discrete elements. Combined with a theoretical differential equation of specific catchment area on hillsides, the calculation of the DWESL model was optimized without estimating the uphill contributing area or the effective contour length for each cell. The proposed integration method based on the topographical features slope line, contour curvature and cutoff factors (ITF method) was used to extract slope length from the raster digital elevation. Slope length extracted using the ITF method had the smallest error in verification of mathematical surfaces (average RRMSE \u00a0=\u00a00.0573), and its spatial distribution was more consistent with the structure of the terrain surface for all test data, relative to the conventional flow direction algorithms in the original DWESL model. The proposed ITF method could provide a reference for predicting soil erosion using the USLE/RUSLE model.", "keywords": ["Slope Length", "Soil erosion", "0211 other engineering and technologies", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "Terrain analysis", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "GIS"]}, "links": [{"href": "https://doi.org/10.1016/j.catena.2021.105818"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/CATENA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.catena.2021.105818", "name": "item", "description": "10.1016/j.catena.2021.105818", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.catena.2021.105818"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-01T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2017.08.006", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:16:59Z", "type": "Journal Article", "created": "2017-08-30", "title": "An improved method for calculating slope length (\u03bb) and the LS parameters of the Revised Universal Soil Loss Equation for large watersheds", "description": "Abstract   The Universal Soil Loss Equation (USLE) and its revised version (RUSLE) are often used to estimate soil erosion at regional landscape scales. USLE/RUSLE contain parameters for slope length factor (L) and slope steepness factor (S), usually combined as LS. However a major limitation is the difficulty in extracting the LS factor. Methods to estimate LS based on geographic information systems have been developed in the last two decades. L can be calculated for large watersheds using the unit contributing area (UCA) or the slope length (\u03bb) as input parameters. Due to the absence of an estimation of slope length, the UCA method is insufficiently accurate. Improvement of the spatial accuracy of slope length and LS factor is still necessary for estimating soil erosion. The purpose of this study was to develop an improved method to estimate the slope length and LS factor. We combined the algorithm for multiple-flow direction (MFD) used in the UCA method with the LS-TOOL (LS-TOOLSFD) algorithms, taking into account the calculation errors and cutoff conditions for distance, to obtain slope length (\u03bb) and the LS factor. The new method, LS-TOOLMFD, was applied and validated in a catchment with complexly variable slopes. The slope length and LS calculated by LS-TOOLMFD both agreed better with field data than with the calculations using the LS-TOOLSFD and UCA methods, respectively. We then integrated the LS-TOOLMFD algorithm into LS-TOOL developed in Microsoft's .NET environment using C# with a user-friendly interface. The method can automatically calculate slope length, slope steepness, L, S, and LS factor, providing the results as ASCII files that can be easily used in GIS software and erosion models. This study is an important step forward in conducting accurate large-scale erosion evaluation.", "keywords": ["13. Climate action", "LS", "Soil erosion", "0207 environmental engineering", "RUSLE", "Terrain analysis", "02 engineering and technology", "15. Life on land", "GIS", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2017.08.006"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2017.08.006", "name": "item", "description": "10.1016/j.geoderma.2017.08.006", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2017.08.006"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-12-01T00:00:00Z"}}, {"id": "10.1016/j.geodrs.2023.e00610", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:17:01Z", "type": "Journal Article", "created": "2023-01-20", "title": "Evaluation of RUSLE and spatial assessment of agricultural soil erosion in Finland", "description": "Agricultural soil erosion has negative effects on surface water quality and aquatic ecosystems. A major impediment to agricultural erosion management in Finland has been the lack of high-resolution country-scale data on the spatial distribution of erosion. As a result, erosion mitigation measures have been targeted with limited information. Therefore, we evaluated the performance of the widely used RUSLE model against measurements from experimental fields, used the model to produce a two-metre resolution crop and management independent erosion estimate for all agricultural lands of Finland, and analysed erosion over different spatial scales. RUSLE showed skill (R2 = 0.76, NSE = 0.72) in estimating the observed erosion at experimental fields (55\u20132100 kg ha\u22121 yr\u22121) but with large errors (mean: \u2212134 kg ha\u22121 yr\u22121, 90% range: \u2212711 and 218 kg ha\u22121 yr\u22121). The evaluation, however, suggests that RUSLE performs similarly in Finland as elsewhere. The analysis of the developed country-scale data, in turn, revealed high erosion regions, and it showed how erosion varies between sub-catchment and between and within field parcels. For example, high-erosion areas concentrated in the proximity of water bodies were identified at the sub-catchment and within-field parcel scales. Altogether, the results demonstrate the predictive skill of RUSLE in high-latitude conditions, fill the earlier data gap in country-scale erosion, provide information for targeting erosion mitigation measures, and considerably improve the understanding of the spatial distribution of erosion in Finland. ; 2023", "keywords": ["550", "500", "Agriculture", "Water protection", "04 agricultural and veterinary sciences", "Podzols", "Soil erosion", "Histosols", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "Gleysols", "Regosols", "Stagnosols", "ta218", "Finland"]}, "links": [{"href": "https://doi.org/10.1016/j.geodrs.2023.e00610"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma%20Regional", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geodrs.2023.e00610", "name": "item", "description": "10.1016/j.geodrs.2023.e00610", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geodrs.2023.e00610"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-03-01T00:00:00Z"}}, {"id": "10.1016/j.geodrs.2024.e00904", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:17:01Z", "type": "Journal Article", "created": "2024-12-08", "title": "How to site grassed areas to reduce agricultural erosion efficiently? A computational analysis in Finland", "description": "Spatial patterns of land-cover and agricultural operations have clear impacts on soil erosion. Allocating a portion of cultivated area for grass is a widely applied strategy to control erosion. However, it is still unclear how much and where grassed area should be spatially targeted in different landscapes to control erosion efficiently. To address this challenge, we estimate the potential of high-resolution RUSLE-based spatial targeting of grassed areas to improve erosion mitigation in two topographically different catchments in southern Finland. Erosion reductions of 1) policy-based targeting (buffer strips along main streams according to current CAP strategy) were compared with 2) RUSLE-targeted grassed areas (based on the highest computed erosion values within field parcels and sub-catchments). Furthermore, we computationally explored 3) how different rates of optimally located grass areas affected erosion and 4) how the areas could be computationally processed to continuous entities. The erosion reductions were estimated with 2 \u00d7 2 m2 resolution RUSLE computations in all the scenarios. The RUSLE-targeted grassed areas demonstrated greater erosion reductions compared to the policy-based siting of grass areas along riparian fields. With optimal targeting, erosion risks could potentially be reduced up to 24 percentage points (up to 46 % erosion reduction), compared to the buffer strips. Increasing optimally targeted grassed area gradually from 0 to 100 % decreased erosion non-linearly. The largest share of erosion was generated in disproportionally small land areas (\u223c20 % of the land area). The location of the hotspots in relation to the streams varied between the sub-catchments and field parcels. These quantifications demonstrate the potential value of models for targeted landscape scale spatial erosion management. A more comprehensive assessment of erosion mitigation could benefit of improved empirical validation and consideration of other aspects of erosion and sediment transport, such as local drainage ...", "keywords": ["550", "erosion control", "RUSLE", "erosion", "targeting", "siting"]}, "links": [{"href": "https://doi.org/10.1016/j.geodrs.2024.e00904"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma%20Regional", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geodrs.2024.e00904", "name": "item", "description": "10.1016/j.geodrs.2024.e00904", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geodrs.2024.e00904"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-03-01T00:00:00Z"}}, {"id": "10.1016/j.iswcr.2020.07.003", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:17:03Z", "type": "Journal Article", "created": "2020-07-17", "title": "Evaluation of soil erosion risk and identification of soil cover and management factor (C) for RUSLE in European vineyards with different soil management", "description": "Open AccessThis study was funded by the European BiodivERsA project VineDivers (https://short.boku.ac.at/vinedivers) through the BiodivERsA/FACCE JPI (2013\u20132014 joint call) for research proposals, with the national funders: Austrian Science Fund (grant numbers I 2044-/I 2043-/I 2042-B25 FWF), French National Research Agency (ANR), Spanish Ministry of Economy and Competitiveness (PCIN-2014-098), Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) and Federal Ministry of Education and Research (BMBF/Germany). Also to the CNR Short Term Mobility Program 2016 for funding a stay at IAS-CSIC during which M.Biddoccu contributed to this study and the SHui project funded by the European Commission (GA 773903), which supported the final steps of the analysis presented in this manuscript.", "keywords": ["[SDE] Environmental Sciences", "2. Zero hunger", "Soil management", "550", "Vineyard", " Erosion", " Soil management", " RUSLE", " Europe", "04 agricultural and veterinary sciences", "15. Life on land", "Engineering (General). Civil engineering (General)", "Vineyard", "630", "Europe", "Erosion", "13. Climate action", "[SDE]Environmental Sciences", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "TA1-2040"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/510459/1/Biddoccu_et_al_2020_Soil%20erosion%20vineyard%20Europe%20RUSLE.pdf"}, {"href": "https://doi.org/10.1016/j.iswcr.2020.07.003"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Soil%20and%20Water%20Conservation%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.iswcr.2020.07.003", "name": "item", "description": "10.1016/j.iswcr.2020.07.003", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.iswcr.2020.07.003"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-01T00:00:00Z"}}, {"id": "10261/309319", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:25:41Z", "type": "Journal Article", "created": "2023-02-02", "title": "Evaluation of Erosion Risk with Stakeholders using RUSLE Methodology and Publicly Available Information in a Large Olive Producing Area in Southern Spain", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "Stakeholders", "Erosion", "13. Climate action", "Olives", "RUSLE", "15. Life on land"], "contacts": [{"organization": "G\u00f3mez, Jos\u00e9 A, S\u00e1nchez, Ana, Soriano, Mar\u00eda A., Guzm\u00e1n, Gema,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10261/309319"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Erosion%20Research%20Under%20a%20Changing%20Climate%2C%20January%208-13%2C%202023%2C%20Aguadilla%2C%20Puerto%20Rico%2C%20USA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/309319", "name": "item", "description": "10261/309319", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/309319"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.1080/09064710.2022.2136583", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:18:56Z", "type": "Journal Article", "created": "2022-10-26", "title": "Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland", "description": "Spatial information on the distribution of erosion areas and sediment transport pathways within agricultural landscapes is limited. Thus, we assess structural sediment connectivity via surface runoff by using a digital elevation model (2 \u00d7 2 m<sup>2</sup>) and RUSLE-based erosion estimates to compute index of connectivity (IC) and sediment delivery estimates. The variables were analyzed within and between two topographically contrasting subcatchments. We found greater spatial variability of IC within a subcatchment than between the subcatchments. The majority of field parcel areas (65%\u201397%) were structurally connected to adjacent open ditches and streams. Areas with high erosion estimates also tended to be structurally well-connected, both at the pixel (Pearson <i>r</i> = 0.58\u20130.63) and parcel scale (<i>r</i> = 0.49\u20130.67). The IC model was not highly sensitive to parameter variations. In contrast, the magnitude of sediment delivery estimates was highly sensitive to parameter variations. However, based on the high rank correlation (Spearman <i>r</i><sub><i>s</i></sub> &gt; 0.95) between computed sediment delivery estimates, the tool provided consistent information on potentially high sediment delivery areas. More empirical data and dynamic model applications could be applied to improve the accuracy of the estimates. The method provides a feasible tool to generate open data on connectivity.", "keywords": ["550", "ta1172", "rusle", "SB1-1110", "Inorganic Chemistry", "Sociology", "FOS: Chemical sciences", "FOS: Mathematics", "RUSLE", "ta218", "Connectivity", "Ecology", "connectivity index", "Plant culture", "lowlands", "FOS: Earth and related environmental sciences", "04 agricultural and veterinary sciences", "ta4111", "15. Life on land", "erosion", "59999 Environmental Sciences not elsewhere classified", "FOS: Sociology", "FOS: Biological sciences", "connectivity", "Medicine", "19999 Mathematical Sciences not elsewhere classified", "0401 agriculture", " forestry", " and fisheries", "69999 Biological Sciences not elsewhere classified", "Biotechnology"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/09064710.2022.2136583"}, {"href": "https://doi.org/10.1080/09064710.2022.2136583"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Acta%20Agriculturae%20Scandinavica%2C%20Section%20B%20%E2%80%94%20Soil%20%26amp%3B%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1080/09064710.2022.2136583", "name": "item", "description": "10.1080/09064710.2022.2136583", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1080/09064710.2022.2136583"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-26T00:00:00Z"}}, {"id": "10.3390/rs11091106", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:21:50Z", "type": "Journal Article", "created": "2019-05-09", "title": "Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil erosion is one of the main causes of soil degradation among others (salinization, compaction, reduction of organic matter, and non-point source pollution) and is a serious threat in the Mediterranean region. A number of soil properties, such as soil organic matter (SOM), soil structure, particle size, permeability, and Calcium Carbonate equivalent (CaCO3), can be the key properties for the evaluation of soil erosion. In this work, several innovative methods (satellite remote sensing, field spectroscopy, soil chemical analysis, and GIS) were investigated for their potential in monitoring SOM, CaCO3, and soil erodibility (K-factor) of the Akrotiri cape in Crete, Greece. Laboratory analysis and soil spectral reflectance in the VIS-NIR (using either Landsat 8, Sentinel-2, or field spectroscopy data) range combined with machine learning and geostatistics permitted the spatial mapping of SOM, CaCO3, and K-factor. Synergistic use of geospatial modeling based on the aforementioned soil properties and the Revised Universal Soil Loss Equation (RUSLE) erosion assessment model enabled the estimation of soil loss risk. Finally, ordinary least square regression (OLSR) and geographical weighted regression (GWR) methodologies were employed in order to assess the potential contribution of different approaches in estimating soil erosion rates. The derived maps captured successfully the SOM, the CaCO3, and the K-factor spatial distribution in the GIS environment. The results may contribute to the design of erosion best management measures and wise land use planning in the study region.</p></article>", "keywords": ["Landsat 8", "2. Zero hunger", "soil erosion", "550", "Science", "Q", "04 agricultural and veterinary sciences", "Remote sensing", "15. Life on land", "01 natural sciences", "630", "field spectroscopy", "6. Clean water", "soil erosion; remote sensing; Sentinel-2; Landsat 8; ANN; RUSLE; field spectroscopy; OLSR; GWR", "remote sensing", "Field spectroscopy", "OLSR", "13. Climate action", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "Sentinel-2", "ANN", "GWR", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/11/9/1106/pdf"}, {"href": "https://doi.org/10.3390/rs11091106"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs11091106", "name": "item", "description": "10.3390/rs11091106", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs11091106"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-09T00:00:00Z"}}, {"id": "10.13031/soil.23056", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:20:09Z", "type": "Journal Article", "created": "2023-02-02", "title": "Evaluation of Erosion Risk with Stakeholders using RUSLE Methodology and Publicly Available Information in a Large Olive Producing Area in Southern Spain", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "Stakeholders", "Erosion", "13. Climate action", "Olives", "RUSLE", "15. Life on land"], "contacts": [{"organization": "G\u00f3mez, Jos\u00e9 A, S\u00e1nchez, Ana, Soriano, Mar\u00eda A., Guzm\u00e1n, Gema,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.13031/soil.23056"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Erosion%20Research%20Under%20a%20Changing%20Climate%2C%20January%208-13%2C%202023%2C%20Aguadilla%2C%20Puerto%20Rico%2C%20USA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.13031/soil.23056", "name": "item", "description": "10.13031/soil.23056", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.13031/soil.23056"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.3390/w12061787", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:21:57Z", "type": "Journal Article", "created": "2020-06-24", "title": "Can Lumped Characteristics of a Contributing Area Provide Risk Definition of Sediment Flux?", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Accelerated soil erosion by water has many offsite impacts on the municipal infrastructure. This paper discusses how to easily detect potential risk points around municipalities by simple spatial analysis using GIS. In the Czech Republic, the WaTEM/SEDEM model is verified and used in large scale studies to assess sediment transports. Instead of computing actual sediment transports in river systems, WaTEM/SEDEM has been innovatively used in high spatial detail to define indices of sediment flux from small contributing areas. Such an approach has allowed for the modeling of sediment fluxes in contributing areas with above 127,484 risk points, covering the entire Czech Republic territory. Risk points are defined as outlets of contributing areas larger than 1 ha, wherein the surface runoff goes into residential areas or vulnerable bodies of water. Sediment flux indices were calibrated by conducting terrain surveys in 4 large watersheds and splitting the risk points into 5 groups defined by the intensity of sediment transport threat. The best sediment flux index resulted from the correlation between the modeled total sediment input in a 100 m buffer zone of the risk point and the field survey data (R2 from 0.57 to 0.91 for the calibration watersheds). Correlation analysis and principal component analysis (PCA) of the modeled indices and their relation to 11 lumped characteristics of the contributing areas were computed (average K-factor; average R-factor; average slope; area of arable land; area of forest; area of grassland; total watershed area; average planar curvature; average profile curvature; specific width; stream power index). The comparison showed that for risk definition the most important is a combination of morphometric characteristics (specific width and stream power index), followed by watershed area, proportion of grassland, soil erodibility, and rain erosivity (described by PC2).</p></article>", "keywords": ["soil erosion", "PCA analysis", "residential areas", "RUSLE (Revised Universal Soil Loss Equation)", "watershed characteristics", "04 agricultural and veterinary sciences", "Residential areas", "15. Life on land", "6. Clean water", "total soil loss", "13. Climate action", "11. Sustainability", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "sediment flux", "Sediment flux", "WaTEM/SEDEM", "Watershed characteristics", "Total soil loss", "Czech Republic"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/12/6/1787/pdf"}, {"href": "https://www.mdpi.com/2073-4441/12/6/1787/pdf"}, {"href": "https://doi.org/10.3390/w12061787"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/w12061787", "name": "item", "description": "10.3390/w12061787", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/w12061787"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-06-23T00:00:00Z"}}, {"id": "3037981509", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:27:12Z", "type": "Journal Article", "created": "2020-06-24", "title": "Can Lumped Characteristics of a Contributing Area Provide Risk Definition of Sediment Flux?", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Accelerated soil erosion by water has many offsite impacts on the municipal infrastructure. This paper discusses how to easily detect potential risk points around municipalities by simple spatial analysis using GIS. In the Czech Republic, the WaTEM/SEDEM model is verified and used in large scale studies to assess sediment transports. Instead of computing actual sediment transports in river systems, WaTEM/SEDEM has been innovatively used in high spatial detail to define indices of sediment flux from small contributing areas. Such an approach has allowed for the modeling of sediment fluxes in contributing areas with above 127,484 risk points, covering the entire Czech Republic territory. Risk points are defined as outlets of contributing areas larger than 1 ha, wherein the surface runoff goes into residential areas or vulnerable bodies of water. Sediment flux indices were calibrated by conducting terrain surveys in 4 large watersheds and splitting the risk points into 5 groups defined by the intensity of sediment transport threat. The best sediment flux index resulted from the correlation between the modeled total sediment input in a 100 m buffer zone of the risk point and the field survey data (R2 from 0.57 to 0.91 for the calibration watersheds). Correlation analysis and principal component analysis (PCA) of the modeled indices and their relation to 11 lumped characteristics of the contributing areas were computed (average K-factor; average R-factor; average slope; area of arable land; area of forest; area of grassland; total watershed area; average planar curvature; average profile curvature; specific width; stream power index). The comparison showed that for risk definition the most important is a combination of morphometric characteristics (specific width and stream power index), followed by watershed area, proportion of grassland, soil erodibility, and rain erosivity (described by PC2).</p></article>", "keywords": ["soil erosion", "PCA analysis", "residential areas", "RUSLE (Revised Universal Soil Loss Equation)", "watershed characteristics", "04 agricultural and veterinary sciences", "Residential areas", "15. Life on land", "6. Clean water", "total soil loss", "13. Climate action", "11. Sustainability", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "sediment flux", "Sediment flux", "WaTEM/SEDEM", "Watershed characteristics", "Total soil loss", "Czech Republic"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/12/6/1787/pdf"}, {"href": "https://www.mdpi.com/2073-4441/12/6/1787/pdf"}, {"href": "https://doi.org/3037981509"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3037981509", "name": "item", "description": "3037981509", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3037981509"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-06-23T00:00:00Z"}}, {"id": "10.5281/zenodo.13951151", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:23:18Z", "type": "Dataset", "created": "2024-01-01", "title": "SERENA EJPSoil Soil loss by water erosion of Tuscany (Italy)", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as part of the EJP Soil SERENA programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results may contain inconsistencies, depending in particular on the raw data available and level of accuracy of the techniques chosen and their prior knowledge .      It is necessary to consider how the results have been obtained in order to decide on their relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental management and policy issues should be done keeping the previous aspects in mind and complementing when necessary the provided results with the best available data.       Finally, it is the responsibility of the users of this information to decide whether it is\u00a0appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the\u00a0results obtained from the use of this data.", "keywords": ["Soil Threat", "Italy", "Grant  n. 862695", "Tuscany", "EJP soil", "RUSLE", "Grant n. 862695", "SERENA Project", "Soil Erosion"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13951151"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13951151", "name": "item", "description": "10.5281/zenodo.13951151", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13951151"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-18T00:00:00Z"}}, {"id": "10.5281/zenodo.13951152", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:23:18Z", "type": "Dataset", "created": "2024-01-01", "title": "SERENA EJPSoil Soil loss by water erosion of Tuscany (Italy)", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as part of the EJP Soil SERENA programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results may contain inconsistencies, depending in particular on the raw data available and level of accuracy of the techniques chosen and their prior knowledge .      It is necessary to consider how the results have been obtained in order to decide on their relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental management and policy issues should be done keeping the previous aspects in mind and complementing when necessary the provided results with the best available data.       Finally, it is the responsibility of the users of this information to decide whether it is\u00a0appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the\u00a0results obtained from the use of this data.", "keywords": ["Soil Threat", "Italy", "Tuscany", "EJP soil", "RUSLE", "Grant n. 862695", "SERENA Project", "Soil Erosion"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13951152"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13951152", "name": "item", "description": "10.5281/zenodo.13951152", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13951152"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-18T00:00:00Z"}}, {"id": "10.5281/zenodo.13952097", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:23:18Z", "type": "Dataset", "created": "2024-01-01", "title": "SERENA EJPSoil Soil erosion control in Tuscany (Italy)", "description": "Open AccessThe internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.  One of the\u00a0objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The present data was prepared according to the methodology of the SERENA Soil erosion and soil erosion control cookbook.\u00a0 Soil loss was used as an indicator for soil erosion (ST). The map of soil mass not eroded was based on the RUSLE model. Soil erosion control was calculated as the difference between potential and actual soil erosion (SES, ecosystem service of soil erosion protection, i.e. soil eroded mass retained by vegetation, Mg/ha/y). For Italy, the cookbook was applied in the Tuscany region. \u00a0     To create the soil loss map we used:\u00a0       for R-factor, not freely available database of meteorological parameters spatialized at 250 m (minimum and maximum daily air temperature; cumulate daily precipitation) over Tuscany region (period 1990\u20132022, Lamma Consortium)\u00a0 and a local linear equation between R and mean annual precipitation (P);   for C -factor, Regional Land use map 1:10.000 (2018, freely available at:\u00a0https://www502.regione.toscana.it/geoscopio/usocoperturasuolo.html) and ESDAC method (https://doi.org/10.1016/j.landusepol.2015.05.021) ; \u00a0  for K-factor, sand, silt, clay, and O.C. (%) maps (built from 4.000 soil profiles, following FAO\u2019s methodology in GSP-GSOC map, Lamma Consortium), and Torri et al. (1997) function;   for LS-factor, DEM 10 m of Tuscany, (freely available at\u00a0https://www502.regione.toscana.it/geoscopio/cartoteca.html99) and Desmet & Govers (1996) SAGA tool (applied at 10 m and upscaled);   for P-factor, not freely available database 1:10.00 of terraced areas (Lamma Consortium, 2020) (for terraced areas a multiplication factor of\u00a0 0.5\u00a0 was considered, based on expert evaluation)   for P-factor, not freely available database 1:10.00 of terraced areas (Lamma Consortium, 2020) (for terraced areas a multiplication factor\u00a0of\u00a0 0.5\u00a0 was considered, based on expert evaluation)\u00a0      Maps was delivered in the GeoTIFF format in the resolution of 100m. \u00a0     Delivered data will be validated by stakeholders from Italy (scientist) in October, 2024.", "keywords": ["Italy", "Tuscany", "SERENA project", "Soil-based ecosystem service", "RUSLE", "soil erosion control", "Grant n. 862695", "EJP-Soil"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13952097"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13952097", "name": "item", "description": "10.5281/zenodo.13952097", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13952097"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-18T00:00:00Z"}}, {"id": "10.5281/zenodo.13993556", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:23:20Z", "type": "Dataset", "created": "2024-01-01", "title": "SERENA EJPSOIL SK Erosion SoilErosion", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as part of the EJP Soil SERENA programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results may contain inconsistencies, depending in particular on the raw data available and level of accuracy of the techniques chosen and their prior knowledge .     It is necessary to consider how the results have been obtained in order to decide on their relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental management and policy issues should be done keeping the previous aspects in mind and complementing when necessary the provided results with the best available data.      Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["Slovakia", "soil erosion", "SERENA project", "RUSLE", "Erosion cookbook", "Grant  n 862695", "Grant n 862695", "EJP-Soil"], "contacts": [{"organization": "P\u00e1lka, Boris, Makovnikova, Jarmila,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13993556"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13993556", "name": "item", "description": "10.5281/zenodo.13993556", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13993556"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-29T00:00:00Z"}}, {"id": "10.5281/zenodo.13993557", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:23:20Z", "type": "Dataset", "created": "2024-01-01", "title": "SERENA EJPSOIL SK Erosion SoilErosion", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as part of the EJP Soil SERENA programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results may contain inconsistencies, depending in particular on the raw data available and level of accuracy of the techniques chosen and their prior knowledge .     It is necessary to consider how the results have been obtained in order to decide on their relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental management and policy issues should be done keeping the previous aspects in mind and complementing when necessary the provided results with the best available data.      Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["Slovakia", "soil erosion", "SERENA project", "RUSLE", "Erosion cookbook", "Grant n 862695", "EJP-Soil"], "contacts": [{"organization": "P\u00e1lka, Boris, Makovnikova, Jarmila,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13993557"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13993557", "name": "item", "description": "10.5281/zenodo.13993557", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13993557"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-29T00:00:00Z"}}, {"id": "10.5281/zenodo.13993747", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:23:20Z", "type": "Dataset", "created": "2024-01-01", "title": "SERENA EJPSOIL SK SOIL Erosion ErosionControl", "description": "Open AccessThe internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.    The present data was prepared according to the methodology of SERENA soil erosion control cookbook for the territory of Slovakia. The map of soil loss by water erosion (soil threat) was based on the RUSLE model. or the soil erosion control, the difference between the erosion map without vegetation (C-factor = 1) and the erosion map with vegetation was calculated.\u00a0      The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats.\u00a0     To create the soil loss map we used theese data:\u00a0     \u00a0R factor - we used data from 100 automatic rain stations on minute rainfall for about 10-year period (national dataset)\u00a0     K factor \u2013 we used the\u00a0 source proposed in the cookbook from ESDAC\u00a0 dataset: Soil Erodibility (K- Factor) High Resolution dataset for Europe\u00a0     LS factor \u2013 we used the\u00a0 source proposed in the cookbook from ESDAC dataset: LS-factor (Slope Length and Steepness factor) for Slovakia\u00a0     C factor \u2013 we used LPIS database-this has information about crops on agricultural soil. We have values of C factor for all crops.\u00a0     P factor \u2013 we used the source proposed in the cookbook from ESDAC dataset:\u202fP factor for Slovakia. This map has values about 0.99 for Slovakia, so P-factor does not have much effect on the resulting erosion.\u00a0\u00a0     The delivered map was prepared in GeoTIFF format in the resolution of 500 * 500 m.", "keywords": ["Slovakia", "Soil-based ecosystem service", "RUSLE", "soil erosion control", "Grant n 862695", "Grant  n 862695", "Serena project", "EJP-Soil"], "contacts": [{"organization": "P\u00e1lka, Boris, Makovnikova, Jarmila,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13993747"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13993747", "name": "item", "description": "10.5281/zenodo.13993747", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13993747"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-25T00:00:00Z"}}, {"id": "10.5281/zenodo.14006019", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:23:21Z", "type": "Dataset", "title": "SERENA EJP SOIL: Soil water erosion map of Hungary according to the RUSLE model", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales.  Present data was prepared according to the methodology of SERENA Soil erosion and soil erosion control cookbook for the territory of Hungary. The map of soil loss by water erosion (soil threat) was based on the RUSLE model. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil loss was used as an indicator for soil erosion (ST). To create the soil loss map we used data on yearly precipitation of CARPATCLIM database, and AGRI4CAST MARS (R-factor); sand-, silt-, and clay content of DOSoReMI.hu database, and SOC map compiled in the framework of SERENA (K-factor); ESDAC LS-factor for the EU; ESDAC Cover Management factor for the EU (C-factor); ESDAC Support Practices factor for the EU (P-factor).", "keywords": ["EJP SOIL", "Hungary", "RUSLE", "water erosion", "erosion", "SERENA"], "contacts": [{"organization": "Laborczi, Annam\u00e1ria, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, P\u00e1sztor, L\u00e1szl\u00f3,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14006019"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14006019", "name": "item", "description": "10.5281/zenodo.14006019", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14006019"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "10.5281/zenodo.14017261", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:23:21Z", "type": "Dataset", "created": "2024-07-02", "title": "SERENA EJPSOIL PL EROSION SOIL LOSS", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as\u00a0part of the EJP Soil SERENA\u00a0programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results\u00a0may contain inconsistencies,\u00a0depending\u00a0in particular on\u00a0the raw data\u00a0available\u00a0and level of accuracy of the techniques chosen\u00a0and\u00a0their prior knowledge\u00a0.     It is necessary to consider how the results have been obtained\u00a0in order to\u00a0decide on their\u00a0relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental\u00a0management and policy issues should be done keeping the previous aspects in mind and\u00a0complementing when\u00a0necessary\u00a0the provided results with the best available data.      ==> Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["862695", "Agricultural soils", "Soil threats", "RUSLE", "Poland", "SERENA", "Soil Loss", "EJP-SOIL", "Soil Erosion"], "contacts": [{"organization": "Pindral, Sylwia, Klimkowicz-Pawlas, Agnieszka, Smreczak, Bo\u017cena,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14017261"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14017261", "name": "item", "description": "10.5281/zenodo.14017261", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14017261"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-31T00:00:00Z"}}, {"id": "10.5281/zenodo.14017262", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:23:21Z", "type": "Dataset", "created": "2024-07-02", "title": "SERENA EJPSOIL PL EROSION SOIL LOSS", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as\u00a0part of the EJP Soil SERENA\u00a0programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results\u00a0may contain inconsistencies,\u00a0depending\u00a0in particular on\u00a0the raw data\u00a0available\u00a0and level of accuracy of the techniques chosen\u00a0and\u00a0their prior knowledge\u00a0.     It is necessary to consider how the results have been obtained\u00a0in order to\u00a0decide on their\u00a0relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental\u00a0management and policy issues should be done keeping the previous aspects in mind and\u00a0complementing when\u00a0necessary\u00a0the provided results with the best available data.      ==> Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["862695", "Agricultural soils", "Soil threats", "RUSLE", "Poland", "SERENA", "Soil Loss", "EJP-SOIL", "Soil Erosion"], "contacts": [{"organization": "Pindral, Sylwia, Klimkowicz-Pawlas, Agnieszka, Smreczak, Bo\u017cena,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14017262"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14017262", "name": "item", "description": "10.5281/zenodo.14017262", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14017262"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-31T00:00:00Z"}}, {"id": "10.5281/zenodo.14018111", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:23:21Z", "type": "Dataset", "created": "2024-09-10", "title": "SERENA EJPSOIL PL EROSION CONTROL SOIL MASS NOT ERODED", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as\u00a0part of the EJP Soil SERENA\u00a0programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results\u00a0may contain inconsistencies,\u00a0depending\u00a0in particular on\u00a0the raw data\u00a0available\u00a0and level of accuracy of the techniques chosen\u00a0and\u00a0their prior knowledge\u00a0.     It is necessary to consider how the results have been obtained\u00a0in order to\u00a0decide on their\u00a0relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental\u00a0management and policy issues should be done keeping the previous aspects in mind and\u00a0complementing when\u00a0necessary\u00a0the provided results with the best available data.      ==> Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["RUSLE", "Poland", "Agricultural Land", "Erosion Control", "Soil-based Ecosystem Services", "SERENA", "EJP-SOIL", "Soil Mass Not Eroded"], "contacts": [{"organization": "Pindral, Sylwia, Klimkowicz-Pawlas, Agnieszka, Smreczak, Bo\u017cena,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14018111"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14018111", "name": "item", "description": "10.5281/zenodo.14018111", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14018111"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-31T00:00:00Z"}}, {"id": "10.5281/zenodo.14018112", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:23:21Z", "type": "Dataset", "created": "2024-09-10", "title": "SERENA EJPSOIL PL EROSION CONTROL SOIL MASS NOT ERODED", "description": "Open AccessThe data are derived from the calculation of indicators based on a standard methodology established as\u00a0part of the EJP Soil SERENA\u00a0programme. Please keep in mind that:       It is the result of a modelling exercise and does not necessarily reflect reality.     Despite the efforts made to provide reliable data, the results\u00a0may contain inconsistencies,\u00a0depending\u00a0in particular on\u00a0the raw data\u00a0available\u00a0and level of accuracy of the techniques chosen\u00a0and\u00a0their prior knowledge\u00a0.     It is necessary to consider how the results have been obtained\u00a0in order to\u00a0decide on their\u00a0relevance\u00a0in relation to the intended\u00a0purpose\u00a0of reuse.     These results are interesting from a scientific point of view, but their use\u00a0for environmental\u00a0management and policy issues should be done keeping the previous aspects in mind and\u00a0complementing when\u00a0necessary\u00a0the provided results with the best available data.      ==> Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.", "keywords": ["RUSLE", "Poland", "Agricultural Land", "Erosion Control", "Soil-based Ecosystem Services", "SERENA", "EJP-SOIL", "Soil Mass Not Eroded"], "contacts": [{"organization": "Pindral, Sylwia, Klimkowicz-Pawlas, Agnieszka, Smreczak, Bo\u017cena,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14018112"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14018112", "name": "item", "description": "10.5281/zenodo.14018112", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14018112"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-31T00:00:00Z"}}, {"id": "2944731604", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:27:00Z", "type": "Journal Article", "created": "2019-05-09", "title": "Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil erosion is one of the main causes of soil degradation among others (salinization, compaction, reduction of organic matter, and non-point source pollution) and is a serious threat in the Mediterranean region. A number of soil properties, such as soil organic matter (SOM), soil structure, particle size, permeability, and Calcium Carbonate equivalent (CaCO3), can be the key properties for the evaluation of soil erosion. In this work, several innovative methods (satellite remote sensing, field spectroscopy, soil chemical analysis, and GIS) were investigated for their potential in monitoring SOM, CaCO3, and soil erodibility (K-factor) of the Akrotiri cape in Crete, Greece. Laboratory analysis and soil spectral reflectance in the VIS-NIR (using either Landsat 8, Sentinel-2, or field spectroscopy data) range combined with machine learning and geostatistics permitted the spatial mapping of SOM, CaCO3, and K-factor. Synergistic use of geospatial modeling based on the aforementioned soil properties and the Revised Universal Soil Loss Equation (RUSLE) erosion assessment model enabled the estimation of soil loss risk. Finally, ordinary least square regression (OLSR) and geographical weighted regression (GWR) methodologies were employed in order to assess the potential contribution of different approaches in estimating soil erosion rates. The derived maps captured successfully the SOM, the CaCO3, and the K-factor spatial distribution in the GIS environment. The results may contribute to the design of erosion best management measures and wise land use planning in the study region.</p></article>", "keywords": ["Landsat 8", "2. Zero hunger", "soil erosion", "550", "Science", "Q", "04 agricultural and veterinary sciences", "Remote sensing", "15. Life on land", "01 natural sciences", "630", "field spectroscopy", "6. Clean water", "soil erosion; remote sensing; Sentinel-2; Landsat 8; ANN; RUSLE; field spectroscopy; OLSR; GWR", "remote sensing", "Field spectroscopy", "OLSR", "13. Climate action", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "Sentinel-2", "ANN", "GWR", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/11/9/1106/pdf"}, {"href": "https://doi.org/2944731604"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2944731604", "name": "item", "description": "2944731604", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2944731604"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-09T00:00:00Z"}}, {"id": "10.5281/zenodo.17036321", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:24:07Z", "type": "Dataset", "title": "Potential annual soil loss by erosion (RUSLE), Rwanda", "description": "unspecifiedDISCLAIMER:  These soil property maps were generated at a resolution of 100m, with the best available data at the time of production, including global datasets and legacy national level data, using digital soil mapping and GIS modelling. The derived products are provided 'as-is' without any warranty, regarding accuracy, completeness or fitness for a particular purpose. Users are advised to verify the information independently before making decisions based on it. Additionally, users should assess the local 'predictive' accuracy of the maps prior to using them for making recommendations at local (or field) level.  The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of ISRIC concerning the legal status of any country, territory, city or area or of is authorities, or concerning the delimitation of its frontiers or boundaries.  Despite the fact that this product is created with utmost care, the author(s) and/or publisher(s) and/or ISRIC cannot be held liable for any damage caused by the use of this portal or any content therein in whatever form, whether or not caused by possible errors or faults nor for any consequences thereof.", "keywords": ["Soil", "Land", "Mapping", "Soil erosion", "Rwanda", "RUSLE", "Agriculture", "Crop production", "Modelling"], "contacts": [{"organization": "Colman, Betony", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17036321"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17036321", "name": "item", "description": "10.5281/zenodo.17036321", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17036321"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-02T00:00:00Z"}}, {"id": "10.5281/zenodo.17067540", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-23T16:24:08Z", "type": "Dataset", "title": "Potential annual soil loss by erosion (RUSLE), Kenya", "description": "unspecifiedDISCLAIMER:    These soil property maps were generated at a resolution of 100m, with the best available data at the time of production, including global datasets and legacy national level data, using digital soil mapping and GIS modelling. The derived products are provided 'as-is' without any warranty, regarding accuracy, completeness or fitness for a particular purpose. Users are advised to verify the information independently before making decisions based on it. Additionally, users should assess the local 'predictive' accuracy of the maps prior to using them for making recommendations at local (or field) level.  The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of ISRIC concerning the legal status of any country, territory, city or area or of is authorities, or concerning the delimitation of its frontiers or boundaries.  Despite the fact that this product is created with utmost care, the author(s) and/or publisher(s) and/or ISRIC cannot be held liable for any damage caused by the use of this portal or any content therein in whatever form, whether or not caused by possible errors or faults nor for any consequences thereof.", "keywords": ["Soil", "Land", "Mapping", "Soil erosion", "RUSLE", "Agriculture", "Crop production", "Kenya", "Modelling"], "contacts": [{"organization": "Colman, Betony", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17067540"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17067540", "name": "item", "description": "10.5281/zenodo.17067540", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17067540"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-06T00:00:00Z"}}, {"id": "10.5281/zenodo.17067648", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-23T16:24:08Z", "type": "Dataset", "title": "Potential annual soil loss by erosion (RUSLE), Ethiopia", "description": "unspecifiedAverage annual soil loss (t ha-1 yr-1) calculated using the Revised Universal Soil Loss Equation (RUSLE): A = R \u00d7 K \u00d7 LS \u00d7 C \u00d7 P. This model estimates sheet and rill erosion risk based on five factors: rainfall erosivity (R), soil erodibility (K), topography (LS), cover-management (C), and support practices (P). The resulting map supports erosion risk assessment and soil conservation planning in Ethiopia. Each input layer (R, K, LS, C, P) was derived as a separate spatial dataset as follows:        R factor: Rainfall erosivity factor (MJ mm ha\u207b\u00b9 h\u207b\u00b9 yr\u207b\u00b9). Derived by clipping the global rainfall erosivity dataset of Panagos et al. (2017, https://doi.org/10.1038/s41598-017-04282-8), as published in Panagos et al. (2023, https://doi.org/10.1016/j.dib.2023.1094820), to the administrative country boundry of Ethiopia.  K factor:\u00a0 Soil erodibility factor ((Mg/ha)[(MJ/ha)(mm/h)]\u207b\u00b9), calculated following the method of Torri et al. (1997, https://doi.org/10.1016/S0341-8162(97)00036-2).\u00a0    The input sand, silt, clay and soil organic carbon maps were obtained from SoilGrids (https://doi.org/10.5194/soil-7-217-2021)          LS factor: Topographic factor computed using slope and flow accumulation following the method of Luvai et al. (2021, https://doi.org/10.7176/JEES/11-16-06), and applied to areas with slope <50% in accordance with Panagos, Borrelli, and Meusburger (2015, https://doi.org/10.1016/j.scitotenv.2015.01.008). The LS factor was derived from the MERIT Digital Elevation Model (https://doi.org/10.1002/2017GL072874).  C factor: Cover-management factor, calculated following the method of Negese (2024: https://doi.org/10.1016/j.rsase.2023.101089), using NDVI data derived from Landsat 8 Surface Reflectance Tier 1 Collection 2 imagery (2018\u20132023) (https://www.usgs.gov/landsat-missions/landsat-8).  P factor: Support practices factor. P = 1 due to data gaps.     This research was carried out for the LSC-IS hubs project under the funding program Development Smart Innovation through Research in Agriculture (DeSIRA), European Union. EU Contribution Agreement to MinBUZA: FOOD/2020/419-433 ; MinBUZA to WUR\u00a0Grant number: 4000004100.  \u00a0    Coordinate Reference System -\u00a0EPSG:20138", "keywords": ["Soil", "Land", "Mapping", "Soil erosion", "RUSLE", "Agriculture", "Ethiopia", "Crop production", "Modelling"], "contacts": [{"organization": "Colman, Betony", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17067648"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17067648", "name": "item", "description": "10.5281/zenodo.17067648", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17067648"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-06T00:00:00Z"}}, {"id": "10.5281/zenodo.7777673", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:24:39Z", "type": "Software", "title": "HiLSS Project", "description": "The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '<em>Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. - Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)</em>'. <strong>List of files included in <em>HLC_RUSLE.zip</em>:</strong> <em>R_script_code named 'HLC_RUSLE' in .rmd format</em> <em>Output folder: </em> <em>Figures folder: .png products of the R script code</em> <em>Rasters folder: .png products of the R script code</em> <em>Tables folder: .pdf products of the R script code</em> <em>GeoTiff folder (.TIFF file format): Regional RUSLE Data</em> <em>GPKG:</em> <em>HLC </em>dataset and <em>Region Of Interest file in .gpkg format.</em>", "keywords": ["13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Filippo, Brandolini", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7777673"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7777673", "name": "item", "description": "10.5281/zenodo.7777673", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7777673"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.5281/zenodo.7735993", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:24:38Z", "type": "Software", "title": "HiLSS Project", "description": "The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '<em>Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. - Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)</em>'. <strong>List of files included in <em>HLC_RUSLE.zip</em>:</strong> <em>R_script_code named 'HLC_RUSLE' in .rmd format</em> <em>Output folder: </em> <em>Figures folder: .png products of the R script code</em> <em>Rasters folder: .png products of the R script code</em> <em>Tables folder: .pdf products of the R script code</em> <em>GeoTiff folder (.TIFF file format): Regional RUSLE Data</em> <em>GPKG:</em> <em>HLC </em>dataset and <em>Region Of Interest file in .gpkg format.</em>", "keywords": ["13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Brandolini Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7735993"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7735993", "name": "item", "description": "10.5281/zenodo.7735993", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7735993"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.5281/zenodo.7856487", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:24:39Z", "type": "Dataset", "title": "HiLSS Project", "description": "This\u00a0repository is periodically updated.   Historic Landscape and Soil Sustainability (MSCA-IF-2019 - Individual Fellowships)   The HiLSS Project aims to investigate the relationships between sustainability and landscape heritage with particular reference to soil loss and degradation over the long term. The project will take a multidisciplinary approach that combines archaeology, Historical Landscape Characterisation (HLC), geosciences, and computer-based geospatial analysis (GIS - Geographical Information Systems) and modelling (RUSLE - Revisited Universal Soil Loss Equation). The research objectives of the HiLSS project are to quantify the impact of human activities during the Late Holocene in order to create spatial models which can inform the development of sustainable conservation strategies for rural landscape heritage. This project will focus on two mountainous regions that present historical and cultural similarities but located in different climatic zones of Europe (1- Tuscan-Emilian Apennines, Italy; 2- Northern-mid Galicia, Spain). In previous HLC studies, land-use has been evaluated from the perspective of cultural heritage, whereas RUSLE have used it as a proxy for the land-cover of an area and its effect on soil erosion. The HiLSS project will propose an innovative methodology that combines both the historic/cultural values and the environmental values of land-use to inform development of a model for the sustainable conservation. By considering the different agricultural land-use HLC types in GIS-RUSLE modelling, it will be possible to quantify the effect on soil loss for each HLC type and consequently to devise more environmentally sustainable management for each type. Environmental sustainability and historic landscape conservation are typically treated as two separate fields, but the HiLSS project will develop a transformative model for interdisciplinary research, proposing a new way to embrace both cultural and natural values as components of the same landscape management plans.     HLC_RUSLE.zip    The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: 'Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)'.   List of files included in HLC_RUSLE.zip:      R_script_code named 'HLC_RUSLE'\u00a0in .rmd format   Output folder:        Figures folder: .png products of the R script code    Rasters\u00a0folder: .png products of the R script code    Tables\u00a0folder: .pdf\u00a0products of the R script code       GeoTiff folder (.TIFF file format): Regional RUSLE\u00a0Data   GPKG:\u00a0HLC dataset\u00a0and\u00a0Region Of Interest file in .gpkg format      Spatial statistics to reveal patterns and connections in the historic landscape    The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '\u00a0F.\u00a0Brandolini & S.\u00a0Turner\u00a0(2022)\u00a0Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy),\u00a0Journal of Maps,\u00a0DOI:\u00a010.1080/17445647.2022.2088305.\u00a0'.   It is available at:\u00a0https://doi.org/10.5281/zenodo.5907229     Supplementary material_Land _SI_Historic Landscape Evolution.zip    Supplementary Materials to accompaing\u00a0the paper:\u00a0The evolution of historic agroforestry landscape in the Northern Apennines (Italy) and its consequences for slope geomorphic processes, submitted to\u00a0Land,\u00a0Special Issue\u00a0Historic Landscape Transformation.     Project_Publications.zip    List of .pdf file included in the folder:\u00a0   1) Brandolini F, Domingo-Ribas G, Zerboni A and Turner S. A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features [version 2; peer review: 2 approved, 1 approved with reservations]. Open Res Europe 2021,\u00a01:22\u00a0(https://doi.org/10.12688/openreseurope.13135.2)   2) Brandolini F., Turner S.\u00a0 2022 - Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy), \u00a0Journal of Maps,\u00a0 (https://doi.org/10.1080/17445647.2022.2088305)   3) Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. 2023 -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023), (https://doi.org/10.1038/s41598-023-31334-z)   4)\u00a0Brandolini, F., Compostella, C., Pelfini, M., and Turner, S. 2023 - 'The Evolution of Historic Agroforestry Landscape in the Northern Apennines (Italy) and Its Consequences for Slope Geomorphic Processes' Land 12, no. 5: 1054. (https://doi.org/10.3390/land12051054)", "keywords": ["2. Zero hunger", "13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "USPED", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Brandolini Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7856487"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7856487", "name": "item", "description": "10.5281/zenodo.7856487", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7856487"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.5281/zenodo.7934059", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:24:40Z", "type": "Dataset", "title": "HiLSS Project", "description": "This\u00a0repository is periodically updated.   Historic Landscape and Soil Sustainability (MSCA-IF-2019 - Individual Fellowships)   The HiLSS Project aims to investigate the relationships between sustainability and landscape heritage with particular reference to soil loss and degradation over the long term. The project will take a multidisciplinary approach that combines archaeology, Historical Landscape Characterisation (HLC), geosciences, and computer-based geospatial analysis (GIS - Geographical Information Systems) and modelling (RUSLE - Revisited Universal Soil Loss Equation). The research objectives of the HiLSS project are to quantify the impact of human activities during the Late Holocene in order to create spatial models which can inform the development of sustainable conservation strategies for rural landscape heritage. This project will focus on two mountainous regions that present historical and cultural similarities but located in different climatic zones of Europe (1- Tuscan-Emilian Apennines, Italy; 2- Northern-mid Galicia, Spain). In previous HLC studies, land-use has been evaluated from the perspective of cultural heritage, whereas RUSLE have used it as a proxy for the land-cover of an area and its effect on soil erosion. The HiLSS project will propose an innovative methodology that combines both the historic/cultural values and the environmental values of land-use to inform development of a model for the sustainable conservation. By considering the different agricultural land-use HLC types in GIS-RUSLE modelling, it will be possible to quantify the effect on soil loss for each HLC type and consequently to devise more environmentally sustainable management for each type. Environmental sustainability and historic landscape conservation are typically treated as two separate fields, but the HiLSS project will develop a transformative model for interdisciplinary research, proposing a new way to embrace both cultural and natural values as components of the same landscape management plans.     HLC_RUSLE.zip    The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: 'Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)'.   List of files included in HLC_RUSLE.zip:      R_script_code named 'HLC_RUSLE'\u00a0in .rmd format   Output folder:        Figures folder: .png products of the R script code    Rasters\u00a0folder: .png products of the R script code    Tables\u00a0folder: .pdf\u00a0products of the R script code       GeoTiff folder (.TIFF file format): Regional RUSLE\u00a0Data   GPKG:\u00a0HLC dataset\u00a0and\u00a0Region Of Interest file in .gpkg format      Spatial statistics to reveal patterns and connections in the historic landscape    The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '\u00a0F.\u00a0Brandolini & S.\u00a0Turner\u00a0(2022)\u00a0Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy),\u00a0Journal of Maps,\u00a0DOI:\u00a010.1080/17445647.2022.2088305.\u00a0'.   It is available at:\u00a0https://doi.org/10.5281/zenodo.5907229     Supplementary material_Land _SI_Historic Landscape Evolution.zip    Supplementary Materials to accompaing\u00a0the paper:\u00a0The evolution of historic agroforestry landscape in the Northern Apennines (Italy) and its consequences for slope geomorphic processes, submitted to\u00a0Land,\u00a0Special Issue\u00a0Historic Landscape Transformation.     Project_Publications.zip    List of .pdf file included in the folder:\u00a0   1) Brandolini F, Domingo-Ribas G, Zerboni A and Turner S. A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features [version 2; peer review: 2 approved, 1 approved with reservations]. Open Res Europe 2021,\u00a01:22\u00a0(https://doi.org/10.12688/openreseurope.13135.2)   2) Brandolini F., Turner S.\u00a0 2022 - Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy), \u00a0Journal of Maps,\u00a0 (https://doi.org/10.1080/17445647.2022.2088305)   3) Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. 2023 -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023), (https://doi.org/10.1038/s41598-023-31334-z)   4)\u00a0Brandolini, F., Compostella, C., Pelfini, M., and Turner, S. 2023 - 'The Evolution of Historic Agroforestry Landscape in the Northern Apennines (Italy) and Its Consequences for Slope Geomorphic Processes' Land 12, no. 5: 1054. (https://doi.org/10.3390/land12051054)", "keywords": ["2. Zero hunger", "13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "USPED", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Brandolini Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7934059"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7934059", "name": "item", "description": "10.5281/zenodo.7934059", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7934059"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.6084/m9.figshare.21401999", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:25:19Z", "type": "Journal Article", "created": "2022-10-26", "title": "Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland", "description": "Spatial information on the distribution of erosion areas and sediment transport pathways within agricultural landscapes is limited. Thus, we assess structural sediment connectivity via surface runoff by using a digital elevation model (2 \u00d7 2 m<sup>2</sup>) and RUSLE-based erosion estimates to compute index of connectivity (IC) and sediment delivery estimates. The variables were analyzed within and between two topographically contrasting subcatchments. We found greater spatial variability of IC within a subcatchment than between the subcatchments. The majority of field parcel areas (65%\u201397%) were structurally connected to adjacent open ditches and streams. Areas with high erosion estimates also tended to be structurally well-connected, both at the pixel (Pearson <i>r</i> = 0.58\u20130.63) and parcel scale (<i>r</i> = 0.49\u20130.67). The IC model was not highly sensitive to parameter variations. In contrast, the magnitude of sediment delivery estimates was highly sensitive to parameter variations. However, based on the high rank correlation (Spearman <i>r</i><sub><i>s</i></sub> &gt; 0.95) between computed sediment delivery estimates, the tool provided consistent information on potentially high sediment delivery areas. More empirical data and dynamic model applications could be applied to improve the accuracy of the estimates. The method provides a feasible tool to generate open data on connectivity.", "keywords": ["550", "ta1172", "rusle", "SB1-1110", "Inorganic Chemistry", "Sociology", "FOS: Chemical sciences", "FOS: Mathematics", "RUSLE", "ta218", "Connectivity", "Ecology", "connectivity index", "Plant culture", "lowlands", "FOS: Earth and related environmental sciences", "04 agricultural and veterinary sciences", "ta4111", "15. Life on land", "erosion", "59999 Environmental Sciences not elsewhere classified", "FOS: Sociology", "FOS: Biological sciences", "connectivity", "Medicine", "19999 Mathematical Sciences not elsewhere classified", "0401 agriculture", " forestry", " and fisheries", "69999 Biological Sciences not elsewhere classified", "Biotechnology"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/09064710.2022.2136583"}, {"href": "https://doi.org/10.6084/m9.figshare.21401999"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Acta%20Agriculturae%20Scandinavica%2C%20Section%20B%20%E2%80%94%20Soil%20%26amp%3B%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.6084/m9.figshare.21401999", "name": "item", "description": "10.6084/m9.figshare.21401999", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.6084/m9.figshare.21401999"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-26T00:00:00Z"}}, {"id": "10261/253137", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:25:38Z", "type": "Journal Article", "created": "2020-06-24", "title": "Can Lumped Characteristics of a Contributing Area Provide Risk Definition of Sediment Flux?", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Accelerated soil erosion by water has many offsite impacts on the municipal infrastructure. This paper discusses how to easily detect potential risk points around municipalities by simple spatial analysis using GIS. In the Czech Republic, the WaTEM/SEDEM model is verified and used in large scale studies to assess sediment transports. Instead of computing actual sediment transports in river systems, WaTEM/SEDEM has been innovatively used in high spatial detail to define indices of sediment flux from small contributing areas. Such an approach has allowed for the modeling of sediment fluxes in contributing areas with above 127,484 risk points, covering the entire Czech Republic territory. Risk points are defined as outlets of contributing areas larger than 1 ha, wherein the surface runoff goes into residential areas or vulnerable bodies of water. Sediment flux indices were calibrated by conducting terrain surveys in 4 large watersheds and splitting the risk points into 5 groups defined by the intensity of sediment transport threat. The best sediment flux index resulted from the correlation between the modeled total sediment input in a 100 m buffer zone of the risk point and the field survey data (R2 from 0.57 to 0.91 for the calibration watersheds). Correlation analysis and principal component analysis (PCA) of the modeled indices and their relation to 11 lumped characteristics of the contributing areas were computed (average K-factor; average R-factor; average slope; area of arable land; area of forest; area of grassland; total watershed area; average planar curvature; average profile curvature; specific width; stream power index). The comparison showed that for risk definition the most important is a combination of morphometric characteristics (specific width and stream power index), followed by watershed area, proportion of grassland, soil erodibility, and rain erosivity (described by PC2).</p></article>", "keywords": ["soil erosion", "PCA analysis", "residential areas", "RUSLE (Revised Universal Soil Loss Equation)", "watershed characteristics", "04 agricultural and veterinary sciences", "Residential areas", "15. Life on land", "6. Clean water", "total soil loss", "13. Climate action", "11. Sustainability", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "sediment flux", "Sediment flux", "WaTEM/SEDEM", "Watershed characteristics", "Total soil loss", "Czech Republic"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/12/6/1787/pdf"}, {"href": "https://www.mdpi.com/2073-4441/12/6/1787/pdf"}, {"href": "https://doi.org/10261/253137"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/253137", "name": "item", "description": "10261/253137", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/253137"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-06-23T00:00:00Z"}}, {"id": "2807185283", "type": "Feature", "geometry": null, "properties": {"license": "Restricted", "updated": "2026-06-23T16:26:56Z", "type": "Journal Article", "created": "2018-05-30", "title": "An integrated method for calculating DEM-based RUSLE LS", "description": "The improvement of resolution of digital elevation models (DEMs) and the increasing application of the Revised Universal Soil Loss Equation (RUSLE) over large areas have created problems for the efficiency of calculating the LS factor for large data sets. The pretreatment for flat areas, flow accumulation, and slope-length calculation have traditionally been the most time-consuming steps. However, obtaining these features are generally usually considered as separate steps, and calculations still tend to be time-consuming. We developed an integrated method to improve the efficiency of calculating the LS factor. The calculation model contains algorithms for calculating flow direction, flow accumulation, slope length, and the LS factor. We used the Deterministic 8 method to develop flow-direction octrees (FDOTs), flat matrices (FMs) and first-in-first-out queues (FIFOQs) tracing the flow path. These data structures were much more time-efficient for calculating the slope length inside the flats, the flow accumulation, and the slope length linearly by traversing the FDOTs from their leaves to their roots, which can reduce the search scope and data swapping. We evaluated the accuracy and effectiveness of this integrated algorithm by calculating the LS factor for three areas of the Loess Plateau in China and SRTM DEM of China. The results indicated that this tool could substantially improve the efficiency of LS-factor calculations over large areas without reducing accuracy.", "keywords": ["Revised universal soil loss equation (RUSLE)", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "0101 mathematics", "Geographic information system (GIS)", "01 natural sciences", "LS factor"], "contacts": [{"organization": "Wang, Meng, Baartman, Jantiene E.M., Zhang, Hongming, Yang, Qinke, Li, Shuqin, Yang, Jiangtao, Cai, Cheng, Wang, Meili, Ritsema, Coen J., Geissen, Violette,", "roles": ["creator"]}]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s12145-018-0349-3.pdf"}, {"href": "https://doi.org/2807185283"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20Science%20Informatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2807185283", "name": "item", "description": "2807185283", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2807185283"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-30T00:00:00Z"}}, {"id": "20.500.14243/510459", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:26:33Z", "type": "Journal Article", "created": "2020-07-17", "title": "Evaluation of soil erosion risk and identification of soil cover and management factor (C) for RUSLE in European vineyards with different soil management", "description": "Vineyards show some of the largest erosion rates reported in agricultural areas in Europe. Reported rates vary considerably under the same land use, since erosion processes are highly affected by climate, soil, topography and by the adopted soil management practices. Literature also shows differences in the effect of same conservation practices on reducing soil erosion from conventional, bare soil based, management. The Revised Universal Soil Loss Equation (RUSLE) is commonly adopted to estimate rates of water erosion on cropland under different forms of land use and management, but it requires proper value of soil cover and management (C) factors in order to obtain a reliable evaluation of local soil erosion rates. In this study the ORUSCAL (Orchard RUSle CALibration) is used to identify the best calibration strategy against long-term experimental data. Afterwards, ORUSCAL is used in order to apply the RUSLE technology from farm based information across different European wine-growing regions. The results suggest that the best strategy for calibration should incorporate the soil moisture sub-factor (Sm) to provide better soil loss predictions. The C factor, whose average values ranged from 0.012 to 0.597, presented a large spatial variability due to coupling with local climate and specific local management. The comparison across the five wine-growing regions indicates that for the soil protection management, permanent cover crop is the best measure for accomplishing sustainable erosion rates across the studied areas. Alternate and temporary cover crops, that are used in areas of limited water resources to prevent competition with vines, failed to achieve sustainable erosion rates, that still need to be addressed. This raises the need for a careful use of C values developed under different environmental conditions. This study was funded by the European BiodivERsA project VineDivers (https://short.boku.ac.at/vinedivers) through the BiodivERsA/FACCE JPI (2013\u20132014 joint call) for research proposals, with the national funders: Austrian Science Fund (grant numbers I 2044-/I 2043-/I 2042-B25 FWF), French National Research Agency (ANR), Spanish Ministry of Economy and Competitiveness (PCIN-2014-098), Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) and Federal Ministry of Education and Research (BMBF/Germany). Also to the CNR Short Term Mobility Program 2016 for funding a stay at IAS-CSIC during which M.Biddoccu contributed to this study and the SHui project funded by the European Commission (GA 773903), which supported the final steps of the analysis presented in this manuscript.", "keywords": ["[SDE] Environmental Sciences", "2. Zero hunger", "Soil management", "550", "Vineyard", " Erosion", " Soil management", " RUSLE", " Europe", "04 agricultural and veterinary sciences", "15. Life on land", "Engineering (General). Civil engineering (General)", "Vineyard", "630", "Europe", "Erosion", "13. Climate action", "[SDE]Environmental Sciences", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "TA1-2040"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/510459/1/Biddoccu_et_al_2020_Soil%20erosion%20vineyard%20Europe%20RUSLE.pdf"}, {"href": "https://doi.org/20.500.14243/510459"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Soil%20and%20Water%20Conservation%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.14243/510459", "name": "item", "description": "20.500.14243/510459", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14243/510459"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-01T00:00:00Z"}}, {"id": "2750657721", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:26:53Z", "type": "Journal Article", "created": "2017-08-30", "title": "An improved method for calculating slope length (\u03bb) and the LS parameters of the Revised Universal Soil Loss Equation for large watersheds", "description": "Abstract   The Universal Soil Loss Equation (USLE) and its revised version (RUSLE) are often used to estimate soil erosion at regional landscape scales. USLE/RUSLE contain parameters for slope length factor (L) and slope steepness factor (S), usually combined as LS. However a major limitation is the difficulty in extracting the LS factor. Methods to estimate LS based on geographic information systems have been developed in the last two decades. L can be calculated for large watersheds using the unit contributing area (UCA) or the slope length (\u03bb) as input parameters. Due to the absence of an estimation of slope length, the UCA method is insufficiently accurate. Improvement of the spatial accuracy of slope length and LS factor is still necessary for estimating soil erosion. The purpose of this study was to develop an improved method to estimate the slope length and LS factor. We combined the algorithm for multiple-flow direction (MFD) used in the UCA method with the LS-TOOL (LS-TOOLSFD) algorithms, taking into account the calculation errors and cutoff conditions for distance, to obtain slope length (\u03bb) and the LS factor. The new method, LS-TOOLMFD, was applied and validated in a catchment with complexly variable slopes. The slope length and LS calculated by LS-TOOLMFD both agreed better with field data than with the calculations using the LS-TOOLSFD and UCA methods, respectively. We then integrated the LS-TOOLMFD algorithm into LS-TOOL developed in Microsoft's .NET environment using C# with a user-friendly interface. The method can automatically calculate slope length, slope steepness, L, S, and LS factor, providing the results as ASCII files that can be easily used in GIS software and erosion models. This study is an important step forward in conducting accurate large-scale erosion evaluation.", "keywords": ["13. Climate action", "LS", "Soil erosion", "0207 environmental engineering", "RUSLE", "Terrain analysis", "02 engineering and technology", "15. Life on land", "GIS", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/2750657721"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2750657721", "name": "item", "description": "2750657721", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2750657721"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-12-01T00:00:00Z"}}, {"id": "3211874429", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:27:26Z", "type": "Journal Article", "created": "2021-11-13", "title": "An optimized method for extracting slope length in RUSLE from raster digital elevation", "description": "Abstract   The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) have been widely used for predicting average soil loss. Slope length is an important topographical parameter of the L factor in USLE/RUSLE. Among the widely studied GIS procedures for extracting slope length, the distributed watershed erosion slope length (DWESL) based on the unit contributing area estimation method, which considers two-dimensional runoff process and cutoff factors, is a relatively complete model for calculating slope length. Slope length in the DWESL model is primarily calculated using conventional flow direction algorithms such as D8, Dinf, MS and MFD-md. However, DWESL outputs require further improvement due to the errors in the usual estimates of the uphill contributing area and the effective contour length of discrete elements. Combined with a theoretical differential equation of specific catchment area on hillsides, the calculation of the DWESL model was optimized without estimating the uphill contributing area or the effective contour length for each cell. The proposed integration method based on the topographical features slope line, contour curvature and cutoff factors (ITF method) was used to extract slope length from the raster digital elevation. Slope length extracted using the ITF method had the smallest error in verification of mathematical surfaces (average RRMSE \u00a0=\u00a00.0573), and its spatial distribution was more consistent with the structure of the terrain surface for all test data, relative to the conventional flow direction algorithms in the original DWESL model. The proposed ITF method could provide a reference for predicting soil erosion using the USLE/RUSLE model.", "keywords": ["Slope Length", "Soil erosion", "0211 other engineering and technologies", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "Terrain analysis", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "GIS"]}, "links": [{"href": "https://doi.org/3211874429"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/CATENA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3211874429", "name": "item", "description": "3211874429", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3211874429"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-01T00:00:00Z"}}, {"id": "50|od______2659::1b6081f8bd9a44803fc91990862b9ee4", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:27:59Z", "type": "Dataset", "title": "SERENA EJP SOIL: Soil water erosion map of Hungary according to the RUSLE model", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales.  Present data was prepared according to the methodology of SERENA Soil erosion and soil erosion control cookbook for the territory of Hungary. The map of soil loss by water erosion (soil threat) was based on the RUSLE model. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil loss was used as an indicator for soil erosion (ST). To create the soil loss map we used data on yearly precipitation of CARPATCLIM database, and AGRI4CAST MARS (R-factor); sand-, silt-, and clay content of DOSoReMI.hu database, and SOC map compiled in the framework of SERENA (K-factor); ESDAC LS-factor for the EU; ESDAC Cover Management factor for the EU (C-factor); ESDAC Support Practices factor for the EU (P-factor).", "keywords": ["EJP SOIL", "Hungary", "RUSLE", "water erosion", "erosion", "SERENA"], "contacts": [{"organization": "Laborczi, Annam\u00e1ria, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, P\u00e1sztor, L\u00e1szl\u00f3,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::1b6081f8bd9a44803fc91990862b9ee4"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::1b6081f8bd9a44803fc91990862b9ee4", "name": "item", "description": "50|od______2659::1b6081f8bd9a44803fc91990862b9ee4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::1b6081f8bd9a44803fc91990862b9ee4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "50|od______2659::89950871bb66a5f7dab33e62c1dd289a", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:28:00Z", "type": "Dataset", "title": "SERENA EJPSOIL FR EROSION SOIL LOSS", "description": "General description of SERENA   The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.  Actual dataset  This dataset was product following cookbook recommandation described here : 10.5281/zenodo.13991088. Values are annual erosion rate estimated with the RUSLE method using national data.", "keywords": ["soil erosion", "RUSLE model", "France"], "contacts": [{"organization": "Gaillot, Arthur", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::89950871bb66a5f7dab33e62c1dd289a"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::89950871bb66a5f7dab33e62c1dd289a", "name": "item", "description": "50|od______2659::89950871bb66a5f7dab33e62c1dd289a", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::89950871bb66a5f7dab33e62c1dd289a"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-29T00:00:00Z"}}, {"id": "50|od______2659::faea77e44934fa0ba199639d29e95776", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:28:01Z", "type": "Dataset", "title": "SERENA EJP SOIL: Erosion control map of Hungary", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales.  Present data was prepared according to the methodology of SERENA Soil erosion and soil erosion control cookbook for the territory of Hungary. The map of soil loss by water erosion (soil threat) was based on the RUSLE model. To create the soil loss map we used data on yearly precipitation of CARPATCLIM database, and AGRI4CAST MARS (R-factor); sand-, silt-, and clay content of DOSoReMI.hu database, and SOC map compiled in the framework of SERENA (K-factor); ESDAC LS-factor for the EU; ESDAC Cover Management factor for the EU (C-factor); ESDAC Support Practices factor for the EU (P-factor). For the soil erosion control, the difference between the erosion map without vegetation (C-factor = 1) and the erosion map with vegetation was calculated. The erosion maps with-, and without vegetation were categorized according to the cookbook, and the result map shows how many categories the pixel has changed when vegetation is taken into account (0: the pixel is in the same category in both maps, 1: minor role of vegetation, 2: moderate role of vegetation, 3: significant role of vegetation).", "keywords": ["EJP SOIL", "Hungary", "erosion control", "RUSLE", "water erosion", "SERENA"], "contacts": [{"organization": "Laborczi, Annam\u00e1ria, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, P\u00e1sztor, L\u00e1szl\u00f3,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::faea77e44934fa0ba199639d29e95776"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::faea77e44934fa0ba199639d29e95776", "name": "item", "description": "50|od______2659::faea77e44934fa0ba199639d29e95776", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::faea77e44934fa0ba199639d29e95776"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=RUSLE&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=RUSLE&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=RUSLE&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=RUSLE&offset=43", "hreflang": "en-US"}], "numberMatched": 43, "numberReturned": 43, "distributedFeatures": [], "timeStamp": "2026-06-24T03:21:16.453663Z"}