{"type": "FeatureCollection", "features": [{"id": "010201_CA350_CobSol", "type": "Feature", "geometry": null, "properties": {"updated": "2020-12-22T00:00:00Z", "type": "Dataset", "language": "es", "title": "Autonomous thematic series CV350: Land use and coverage map in the Valencian Community at scale 1:350.000", "description": "Land cover map in the Valencian Community at a scale of 1: 350.000 belonging to the regional thematic serires carried out by the Institut Cartogr\u00e0fic Valenci\u00e0, based on the CORINE Land Cover project, promoted by the European Union through the Copernicus program of the European Environment Agency (EEA).A generalization process (geometric and semantic) has been carried out in order to adapt the thematic information to the scale of the map.Thus,the 44 classes of land cover originally contained in CORINE Land Cover have been reduced to 14: four classes corresponding to residential, industrial and other anthropic uses; four other classes pertaining to agricultural uses; four more classes corresponding to natural vegetation and, finally, another two classes for water and wetlands covers.Cartographic official series CV350 ellaborated by the Institut Cartogr\u00e0fic Valenci\u00e0 has been used as a reference map. ETRS89 geodetic reference system. UTM projection zone 30. Contains modified Copernicus CORINE Land Cover Data 2018", "keywords": ["coberturas", "cobertures", "comunitat-valenciana", "covers", "cv350", "es", "espanya", "espan\u0303a", "icv", "icv_clas:cartografia-de-refere\u0300ncia;se\u0300ries-tema\u0300tiques", "icv_clas:cartografi\u0301a-de-referencia;series-tema\u0301ticas", "icv_clas:reference-cartography;thematic-series", "land", "so\u0300l", "spain", "suelo", "uses", "usos"]}, "links": [{"href": "http://descargas.icv.gva.es/CV350USOL_DATO_DIRECTA_PDF"}, {"href": "http://data.europa.eu/88u/dataset/spaicv_ca350_cobsol"}, {"rel": "self", "type": "application/geo+json", "title": "010201_CA350_CobSol", "name": "item", "description": "010201_CA350_CobSol", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/010201_CA350_CobSol"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "010201_CA350_PermeabilitatAquifers", "type": "Feature", "geometry": null, "properties": {"updated": "2023-01-01T00:00:00Z", "type": "Dataset", "language": "es", "title": "Autonomous thematic series CV350: Soil permeability and aquifer recharge at scale 1:350.000", "description": "Soil permeability and aquifer recharge map in the Valencian Community at a scale of 1:350.000 belonging to the regional thematic series of the Institut Cartogr\u00e0fic Valenci\u00e0. Map derived from the Cartography of critical soils for the recharge of aquifers prepared at a scale of 1:50,000 owned by the Direcci\u00f3n General de Pol\u00edtica Territorial y Paisaje de la Conselleria de Pol\u00edtica Territorial, Obras P\u00fablicas y Movilidad. The thematic information has been prepared considering the permeability of the territory based on its lithological nature, and its relationship with the underlying aquifer,as well as the state of the underground water masses, both from the quantitative and qualitative point of view. Cartographic official series CV350 ellaborated by the Institut Cartogr\u00e0fic Valenci\u00e0 has been used as a reference map. ETRS89 geodetic reference system. UTM projection zone 30", "keywords": ["acui\u0301feros", "aquifers", "aqu\u0308i\u0301fers", "comunitat-valenciana", "cv350", "es", "espanya", "espan\u0303a", "icv", "icv_clas:cartografia-de-refere\u0300ncia;se\u0300ries-tema\u0300tiques", "icv_clas:cartografi\u0301a-de-referencia;series-tema\u0301ticas", "icv_clas:reference-cartography;thematic-series", "permeabilidad", "permeabilitat", "permeability", "soil", "so\u0300l", "spain", "suelo"]}, "links": [{"href": "https://descargas.icv.gva.es/CA350_PermeabilitatAquifers_DATO_DIRECTA_PDF"}, {"href": "http://data.europa.eu/88u/dataset/spaicv_ca350_permeabilitataquifers"}, {"rel": "self", "type": "application/geo+json", "title": "010201_CA350_PermeabilitatAquifers", "name": "item", "description": "010201_CA350_PermeabilitatAquifers", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/010201_CA350_PermeabilitatAquifers"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1007/s10661-023-11079-y", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:14:46Z", "type": "Journal Article", "created": "2023-03-25", "title": "Evaluating the impacts of sustainable land management practices on water quality in an agricultural catchment in Lower Austria using SWAT", "description": "Abstract

Managing agricultural watersheds in an environmentally friendly manner necessitate the strategic implementation of well-targeted sustainable land management (SLM) practices that limit soil and nonpoint source pollution losses and translocation. Watershed-scale SLM-scenario modeling has the potential to identify efficient and effective management strategies from the field to the integrated landscape level. In a case study targeting a 66-hectare watershed in Petzenkirchen, Lower Austria, the Soil and Water Assessment Tool (SWAT) was utilized to evaluate a variety of locally adoptable SLM practices. SWAT was calibrated and validated (monthly) at the catchment outlet for flow, sediment, nitrate-nitrogen (NO3\uffe2\uff80\uff93N), ammonium nitrogen (NH4\uffe2\uff80\uff93N), and mineralized phosphorus (PO4\uffe2\uff80\uff93P) using SWATplusR. Considering the locally existing agricultural practices and socioeconomic and environmental factors of the research area, four conservation practices were evaluated: baseline scenario, contour farming (CF), winter cover crops (CC), and a combination of no-till and cover crops (NT\uffe2\uff80\uff89+\uffe2\uff80\uff89CC). The NT\uffe2\uff80\uff89+\uffe2\uff80\uff89CC SLM practice was found to be the most effective soil conservation practice in reducing soil loss by around 80%, whereas CF obtained the best results for decreasing the nutrient loads of NO3\uffe2\uff80\uff93N and PO4\uffe2\uff80\uff93P by 11% and 35%, respectively. The findings of this study imply that the setup SWAT model can serve the context-specific performance assessment and eventual promotion of SLM interventions that mitigate on-site land degradation and the consequential off-site environmental pollution resulting from agricultural nonpoint sources.Widespread soil acidification due to atmospheric acid deposition and agricultural fertilization may greatly accelerate soil carbonate dissolution and CO2 release. However, to date, few studies have addressed these processes. Here, we use meta-analysis and nationwide-survey datasets to investigate changes in soil inorganic carbon (SIC) stocks in China. We observe an overall decrease in SIC stocks in topsoil (0\uffe2\uff80\uff9330\uffc2\uffa0cm) (11.33\uffc2\uffa0g C m\uffe2\uff80\uff932 yr\uffe2\uff80\uff931) from the 1980s to the 2010s. Total SIC stocks have decreased by \uffe2\uff88\uffbc8.99\uffc2\uffa0\uffc2\uffb1\uffc2\uffa02.24% (1.37\uffc2\uffa0\uffc2\uffb1\uffc2\uffa00.37\uffc2\uffa0Pg C). The average SIC losses across China (0.046 Pg C yr\uffe2\uff80\uff931) and in cropland (0.016 Pg C yr\uffe2\uff80\uff931) account for \uffe2\uff88\uffbc17.6%\uffe2\uff80\uff9324.0% of the terrestrial C sink and 57.1% of the soil organic carbon sink in cropland, respectively. Nitrogen deposition and climate change have profound influences on SIC cycling. We estimate that \uffe2\uff88\uffbc19.12%\uffe2\uff80\uff9319.47% of SIC stocks will be further lost by 2100. The consumption of SIC may offset a large portion of global efforts aimed at ecosystem carbon sequestration, which emphasizes the importance of achieving a better understanding of the indirect coupling mechanisms of nitrogen and carbon cycling and of effective countermeasures to minimize SIC loss.

The recently launched Sentinel-1 satellite with a Synthetic Aperture Radar (SAR) sensor onboard offers a powerful tool for irrigation monitoring under various weather conditions, with high spatial and temporal resolution. This research discusses the potential of different metrics calculated from the Sentinel-1 time series for mapping irrigated fields. A methodology for irrigation mapping using SAR data is proposed. The study is performed using VV (vertical\u2013vertical) and VH (vertical\u2013horizontal) polarizations over an agricultural site in Urgell, Catalunya (Spain). With field segmentation information from SIGPAC (the Geographic Information System for Agricultural Parcels), the backscatter intensities are averaged within each field. From the Sentinel-1 time series for each field, the statistics and metrics, including the mean value, the variance of the signal, the correlation length, and the fractal dimension, are analyzed. With the Support Vector Machine (SVM), the classification of irrigated crops, irrigated trees, and non-irrigated fields is performed with the metrics vector. The results derived from the SVM are validated with ground truthing from SIGPAC over the whole study area, with a good overall accuracy of 81.08%. Random Forest (RF) machine classification is also tested in this study, which gives an accuracy of around 82.2% when setting the tree depth at three. The methodology is based only on SAR data, which makes it applicable to all areas, even with frequent cloud cover, but this method may be less robust when irrigation is less dominated to soil moisture change.

", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "IMAGE SATELLITE", "irrigated farming", "0211 other engineering and technologies", "0207 environmental engineering", "02 engineering and technology", "630", "irrigation", "remote sensing", "cartography", "CULTURE IRRIGUEE", "TELEDETECTION", "CARTOGRAPHIE", "2. Zero hunger", "HUMIDITE DU SOL", "Q", "soil water content", "15. Life on land", "6. Clean water", "classification", "[SDE]Environmental Sciences", "Sentinel-1", "soil moisture", "soil moisture; SAR; Sentinel-1; irrigation; classification", "SAR"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/10/9/1495/pdf"}, {"href": "https://doi.org/10.3390/rs10091495"}, {"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/rs10091495", "name": "item", "description": "10.3390/rs10091495", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs10091495"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-09-18T00:00:00Z"}}, {"id": "10.4995/cigeo2021.2021.12729", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:21:07Z", "type": "Journal Article", "created": "2021-10-11", "title": "Methodological proposal for the identification of marginal lands with remote sensing-derived products and ancillary data", "description": "

The concept of marginal land (ML) is dynamic and depends on various factors related to the environment, climate, scale,culture, and economic sector. The current methods for identifying ML are diverse, they employ multiple parameters andvariables derived from land use and land cover, and mostly reflect specific management purposes. A methodologicalapproach for the identification of marginal lands using remote sensing and ancillary data products and validated on samplesfrom four European countries (i.e., Germany, Spain, Greece, and Poland) is presented in this paper. The methodologyproposed combines land use and land cover data sets as excluding indicators (forest, croplands, protected areas,impervious areas, land-use change, water bodies, and permanent snow areas) and environmental constraints informationas marginality indicators: (i) physical soil properties, in terms of slope gradient, erosion, soil depth, soil texture, percentageof coarse soil texture fragments, etc.; (ii) climatic factors e.g. aridity index; (iii) chemical soil properties, including soil pH,cation exchange capacity, contaminants, and toxicity, among others. This provides a common vision of marginality thatintegrates a multidisciplinary approach. To determine the ML, we first analyzed the excluding indicators used to delimit theareas with defined land use. Then, thresholds were determined for each marginality indicator through which the landproductivity progressively decreases. Finally, the marginality indicator layers were combined in Google Earth Engine. Theresult was categorized into 3 levels of productivity of ML: high productivity, low productivity, and potentially unsuitable land.The results obtained indicate that the percentage of marginal land per country is 11.64% in Germany, 19.96% in Spain,18.76% in Greece, and 7.18% in Poland. The overall accuracies obtained per country were 60.61% for Germany, 88.87%for Spain, 71.52% for Greece, and 90.97% for Poland.

", "keywords": ["Cartography", "Land cover", "Cultural Heritage", "Cobertura de suelo", "3D Modelling", "11. Sustainability", "Teledetecci\u00f3n", "Environmental applications", "Uso de suelo", "2. Zero hunger", "Earth observation", "Tierra abandonada", "Remote sensing", "15. Life on land", "GIS", "SIG", "Geophysics", "Idle land", "13. Climate action", "Degradaci\u00f3n del suelo", "Land use", "Land degradation", "land use", " land cover", " idle land", " land degradation", " GIS", " remote sensing", " Google Earth Engine", "Geocomputing", "Google Earth Engine", "Geodesy"]}, "links": [{"href": "https://doi.org/10.4995/cigeo2021.2021.12729"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Proceedings%20-%203rd%20Congress%20in%20Geomatics%20Engineering%20-%20CIGeo", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.4995/cigeo2021.2021.12729", "name": "item", "description": "10.4995/cigeo2021.2021.12729", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.4995/cigeo2021.2021.12729"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-07T00:00:00Z"}}, {"id": "10.3390/agronomy11122403", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:20:36Z", "type": "Journal Article", "created": "2021-11-29", "title": "Impacts of Farming Layer Constructions on Cultivated Land Quality under the Cultivated Land Balance Policy", "description": "

Cultivated Land Balance Policy (CLBP) has led to the \u201cbetter land occupied and worse land supplemented\u201d program. At the same time, the current field-scale cultivated land quality (CLQ) evaluation cannot meet the work requirements of the CLBP. To this end, this study selected 24 newly added farmland in Fuping County and performed eight different high quality farming layer construction experiments to improve the CLQ. A new comprehensive model was constructed on a field scale to evaluate the CLQ using different tests from multi-dimensional perspectives of soil fertility, engineering, environment, and ecology, and to determine the best test mode. The results showed that after the test, around 62% of the cultivated land improved by one level, and the average cultivated land quality level and quality index of the test area increased by 0.63 and 30.63, respectively. The treatment of \u201cwoody peat + rotten crop straw + biostimulation regulator II + conventional fertilization\u201d had the best effect on the improvement of organic matter, soil aggregates, and soil microbial activity, and was the best treatment method. In general, application of soil amendments, such as woody peat when constructing high quality farmland, could quickly improve CLQ, and field-scale CLQ evaluation model constructed from a multi-dimensional perspective could accurately assess the true quality of farmland and allow managers to improve and manage arable land resources under CLBP.

", "keywords": ["Scale (ratio)", "cultivated land quality evaluation", "Agricultural engineering", "Agricultural and Biological Sciences", "Engineering", "Soil Evaluation", "Agricultural land", "Soil water", "Arable land", "cultivated land quality evaluation; field scale; high-quality farming layer; woody peat", "2. Zero hunger", "Global and Planetary Change", "Global Analysis of Ecosystem Services and Land Use", "Geography", "Ecology", "S", "high-quality farming layer", "Life Sciences", "Land Suitability", "Land-Use Suitability Assessment Using GIS", "Land reclamation", "Agriculture", "04 agricultural and veterinary sciences", "woody peat", "Soil Erosion and Agricultural Sustainability", "Agricultural Land Use", "6. Clean water", "FOS: Philosophy", " ethics and religion", "Physical Sciences", "Quality (philosophy)", "field scale", "Cartography", "Soil Science", "Epistemology", "Management", " Monitoring", " Policy and Law", "Soil quality", "Environmental science", "Crop Suitability", "Agroforestry", "Biology", "Soil science", "Peat", "15. Life on land", "Topsoil", "Philosophy", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2403/pdf"}, {"href": "https://doi.org/10.3390/agronomy11122403"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agronomy11122403", "name": "item", "description": "10.3390/agronomy11122403", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agronomy11122403"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-25T00:00:00Z"}}, {"id": "10.3390/s17091966", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:20:51Z", "type": "Journal Article", "created": "2017-08-28", "title": "Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution", "description": "

The recent deployment of ESA\u2019s Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015\u2013November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m3/m3 and 0.059 m3/m3 for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded.

", "keywords": ["[SDE] Environmental Sciences", "NDVI", "Chemical technology", "HUMIDITE DU SOL", "soil moisture; SAR; Sentinel-1; NDVI; Sentinel-2; change detection", "0211 other engineering and technologies", "soil water content", "TP1-1185", "02 engineering and technology", "15. Life on land", "01 natural sciences", "Article", "remote sensing", "Sentinel-1", "cartography", "soil moisture", "Sentinel-2", "TELEDETECTION", "change detection", "CARTOGRAPHIE", "SAR", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/17/9/1966/pdf"}, {"href": "https://doi.org/10.3390/s17091966"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sensors", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/s17091966", "name": "item", "description": "10.3390/s17091966", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/s17091966"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-08-26T00:00:00Z"}}, {"id": "10.4995/cigeo2021.2021.12694", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:21:07Z", "type": "Journal Article", "created": "2021-10-11", "title": "A review of the use of remote sensing for monitoring and quantifying carbon sequestration in marginal lands", "description": "

In recent years, Remote Sensing (RS) and its derived products have been used as a key tool for the detection, monitoring,management and future use of Marginal Lands (ML). Currently, there is no single, universally accepted definition of theterm and there is a wide variety of synonyms. In this paper, we conduct a compilation of synonyms and meanings thatencompass the term, as well as propose a definition. To reach this objective, an overview of the state of the art of ML isdone, visualising trends by science maps, based on bibliographic data of established research journals, found in GoogleScholar, Web of Science (WoS) and Scopus search engines. The bibliographic review carried out shows that the study ofML has traditionally been carried out with an ad hoc basis focused on the objective to be achieved, this aspect and otherknowledge gaps are discussed to analyse the global study of ML. Due to the broad spectrum of uses in which ML havebeen studied, the work has been focused on RS for monitoring and characterizing ML, focusing on two different aspects:(i) satellite monitoring of marginal lands; and (ii) determining carbon sequestration potential of marginal lands using remotesensing.

", "keywords": ["Cartography", "Carbon sequestration", "Earth observation", "Uso del suelo", "Cultural Heritage", "Marginal lands", "Remote sensing", "15. Life on land", "12. Responsible consumption", "3D Modelling", "Geophysics", "Captura de carbono", "13. Climate action", "Land use", "11. Sustainability", "Teledetecci\u00f3n", "Tierras marginales", "marginal lands", " remote sensing", " carbon sequestration", " land use", "Geocomputing", "Environmental applications", "Geodesy"]}, "links": [{"href": "https://doi.org/10.4995/cigeo2021.2021.12694"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Proceedings%20-%203rd%20Congress%20in%20Geomatics%20Engineering%20-%20CIGeo", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.4995/cigeo2021.2021.12694", "name": "item", "description": "10.4995/cigeo2021.2021.12694", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.4995/cigeo2021.2021.12694"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-07T00:00:00Z"}}, {"id": "10.5194/hess-19-4201-2015", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:21:34Z", "type": "Journal Article", "created": "2015-10-20", "title": "Multidecadal Change In Streamflow Associated With Anthropogenic Disturbances In The Tropical Andes", "description": "

Abstract. Andean headwater catchments are an important source of freshwater for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes in these catchments. In this paper, we assess change in streamflow based on long time series of hydrometeorological data (1974\uffe2\uff80\uff932008) and land cover reconstructions (1963\uffe2\uff80\uff932009) in the Pangor catchment (282 km2) located in the tropical Andes. Three main land cover change trajectories can be distinguished during the period 1963\uffe2\uff80\uff932009: (1) expansion of agricultural land by an area equal to 14 % of the catchment area (or 39 km2) in 46 years' time, (2) deforestation of native forests by 11 % (or \uffe2\uff88\uff9231 km2) corresponding to a mean rate of 67 ha yr\uffe2\uff88\uff921, and (3) afforestation with exotic species in recent years by about 5 % (or 15 km2). Over the time period 1963\uffe2\uff80\uff932009, about 50 % of the 64 km2 of native forests was cleared and converted to agricultural land. Given the strong temporal variability of precipitation and streamflow data related to El Ni\uffc3\uffb1o\uffe2\uff80\uff93Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow, which exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term change in precipitation but very likely result from anthropogenic disturbances associated with land cover change.

", "keywords": ["Technology", "Period (music)", "0208 environmental biotechnology", "Urban Flooding", "Precipitation", "02 engineering and technology", "Oceanography", "Environmental technology. Sanitary engineering", "land-use change", "Geography. Anthropology. Recreation", "Climate change", "GE1-350", "TD1-1066", "Water Science and Technology", "Climatology", "2. Zero hunger", "Global and Planetary Change", "Geography", "Ecology", "T", "Physics", "Hydrology (agriculture)", "Geology", "Programming language", "Hydrological Modeling and Water Resource Management", "Physical Sciences", "Cartography", "Land cover", "1443", "Hydrometeorology", "Drainage basin", "0207 environmental engineering", "Streamflow", "Environmental science", "G", "Global Flood Risk Assessment and Management", "Meteorology", "Afforestation", "Agroforestry", "Biology", "Land use", " land-use change and forestry", "FOS: Earth and related environmental sciences", "Acoustics", "15. Life on land", "Computer science", "Environmental sciences", "Geotechnical engineering", "Deforestation (computer science)", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Global Drought Monitoring and Assessment", "Land use"]}, "links": [{"href": "https://doi.org/10.5194/hess-19-4201-2015"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-19-4201-2015", "name": "item", "description": "10.5194/hess-19-4201-2015", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-19-4201-2015"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-10-20T00:00:00Z"}}, {"id": "10.60692/2ezcc-55g95", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:23:54Z", "type": "Journal Article", "created": "2021-11-28", "title": "Impacts of Farming Layer Constructions on Cultivated Land Quality under the Cultivated Land Balance Policy", "description": "

Cultivated Land Balance Policy (CLBP) has led to the \u201cbetter land occupied and worse land supplemented\u201d program. At the same time, the current field-scale cultivated land quality (CLQ) evaluation cannot meet the work requirements of the CLBP. To this end, this study selected 24 newly added farmland in Fuping County and performed eight different high quality farming layer construction experiments to improve the CLQ. A new comprehensive model was constructed on a field scale to evaluate the CLQ using different tests from multi-dimensional perspectives of soil fertility, engineering, environment, and ecology, and to determine the best test mode. The results showed that after the test, around 62% of the cultivated land improved by one level, and the average cultivated land quality level and quality index of the test area increased by 0.63 and 30.63, respectively. The treatment of \u201cwoody peat + rotten crop straw + biostimulation regulator II + conventional fertilization\u201d had the best effect on the improvement of organic matter, soil aggregates, and soil microbial activity, and was the best treatment method. In general, application of soil amendments, such as woody peat when constructing high quality farmland, could quickly improve CLQ, and field-scale CLQ evaluation model constructed from a multi-dimensional perspective could accurately assess the true quality of farmland and allow managers to improve and manage arable land resources under CLBP.

", "keywords": ["Scale (ratio)", "cultivated land quality evaluation", "Agricultural engineering", "Agricultural and Biological Sciences", "Engineering", "Soil Evaluation", "Agricultural land", "Soil water", "Arable land", "cultivated land quality evaluation; field scale; high-quality farming layer; woody peat", "2. Zero hunger", "Global and Planetary Change", "Global Analysis of Ecosystem Services and Land Use", "Geography", "Ecology", "S", "high-quality farming layer", "Life Sciences", "Land Suitability", "Land-Use Suitability Assessment Using GIS", "Land reclamation", "Agriculture", "04 agricultural and veterinary sciences", "woody peat", "Soil Erosion and Agricultural Sustainability", "Agricultural Land Use", "6. Clean water", "FOS: Philosophy", " ethics and religion", "Physical Sciences", "Quality (philosophy)", "field scale", "Cartography", "Soil Science", "Epistemology", "Management", " Monitoring", " Policy and Law", "Soil quality", "Environmental science", "Crop Suitability", "Agroforestry", "Biology", "Soil science", "Peat", "15. Life on land", "Topsoil", "Philosophy", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2403/pdf"}, {"href": "https://doi.org/10.60692/2ezcc-55g95"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/2ezcc-55g95", "name": "item", "description": "10.60692/2ezcc-55g95", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/2ezcc-55g95"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-25T00:00:00Z"}}, {"id": "3178537690", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:25:48Z", "type": "Journal Article", "created": "2021-06-29", "title": "Significant loss of soil inorganic carbon at the continental scale", "description": "Abstract

Widespread soil acidification due to atmospheric acid deposition and agricultural fertilization may greatly accelerate soil carbonate dissolution and CO2 release. However, to date, few studies have addressed these processes. Here, we use meta-analysis and nationwide-survey datasets to investigate changes in soil inorganic carbon (SIC) stocks in China. We observe an overall decrease in SIC stocks in topsoil (0\uffe2\uff80\uff9330\uffc2\uffa0cm) (11.33\uffc2\uffa0g C m\uffe2\uff80\uff932 yr\uffe2\uff80\uff931) from the 1980s to the 2010s. Total SIC stocks have decreased by \uffe2\uff88\uffbc8.99\uffc2\uffa0\uffc2\uffb1\uffc2\uffa02.24% (1.37\uffc2\uffa0\uffc2\uffb1\uffc2\uffa00.37\uffc2\uffa0Pg C). The average SIC losses across China (0.046 Pg C yr\uffe2\uff80\uff931) and in cropland (0.016 Pg C yr\uffe2\uff80\uff931) account for \uffe2\uff88\uffbc17.6%\uffe2\uff80\uff9324.0% of the terrestrial C sink and 57.1% of the soil organic carbon sink in cropland, respectively. Nitrogen deposition and climate change have profound influences on SIC cycling. We estimate that \uffe2\uff88\uffbc19.12%\uffe2\uff80\uff9319.47% of SIC stocks will be further lost by 2100. The consumption of SIC may offset a large portion of global efforts aimed at ecosystem carbon sequestration, which emphasizes the importance of achieving a better understanding of the indirect coupling mechanisms of nitrogen and carbon cycling and of effective countermeasures to minimize SIC loss.

The recent deployment of ESA\u2019s Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015\u2013November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m3/m3 and 0.059 m3/m3 for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded.

", "keywords": ["[SDE] Environmental Sciences", "NDVI", "Chemical technology", "HUMIDITE DU SOL", "soil moisture; SAR; Sentinel-1; NDVI; Sentinel-2; change detection", "0211 other engineering and technologies", "soil water content", "TP1-1185", "02 engineering and technology", "15. Life on land", "01 natural sciences", "Article", "remote sensing", "Sentinel-1", "cartography", "soil moisture", "Sentinel-2", "TELEDETECTION", "change detection", "CARTOGRAPHIE", "SAR", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/17/9/1966/pdf"}, {"href": "https://doi.org/2747196278"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sensors", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2747196278", "name": "item", "description": "2747196278", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2747196278"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-08-26T00:00:00Z"}}, {"id": "2889759488", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:25:26Z", "type": "Journal Article", "created": "2018-09-19", "title": "Irrigation Mapping Using Sentinel-1 Time Series at Field Scale", "description": "

The recently launched Sentinel-1 satellite with a Synthetic Aperture Radar (SAR) sensor onboard offers a powerful tool for irrigation monitoring under various weather conditions, with high spatial and temporal resolution. This research discusses the potential of different metrics calculated from the Sentinel-1 time series for mapping irrigated fields. A methodology for irrigation mapping using SAR data is proposed. The study is performed using VV (vertical\u2013vertical) and VH (vertical\u2013horizontal) polarizations over an agricultural site in Urgell, Catalunya (Spain). With field segmentation information from SIGPAC (the Geographic Information System for Agricultural Parcels), the backscatter intensities are averaged within each field. From the Sentinel-1 time series for each field, the statistics and metrics, including the mean value, the variance of the signal, the correlation length, and the fractal dimension, are analyzed. With the Support Vector Machine (SVM), the classification of irrigated crops, irrigated trees, and non-irrigated fields is performed with the metrics vector. The results derived from the SVM are validated with ground truthing from SIGPAC over the whole study area, with a good overall accuracy of 81.08%. Random Forest (RF) machine classification is also tested in this study, which gives an accuracy of around 82.2% when setting the tree depth at three. The methodology is based only on SAR data, which makes it applicable to all areas, even with frequent cloud cover, but this method may be less robust when irrigation is less dominated to soil moisture change.

", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "IMAGE SATELLITE", "irrigated farming", "0211 other engineering and technologies", "0207 environmental engineering", "02 engineering and technology", "630", "irrigation", "remote sensing", "cartography", "CULTURE IRRIGUEE", "TELEDETECTION", "CARTOGRAPHIE", "2. Zero hunger", "HUMIDITE DU SOL", "Q", "soil water content", "15. Life on land", "6. Clean water", "classification", "[SDE]Environmental Sciences", "Sentinel-1", "soil moisture", "soil moisture; SAR; Sentinel-1; irrigation; classification", "SAR"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/10/9/1495/pdf"}, {"href": "https://doi.org/2889759488"}, {"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": "2889759488", "name": "item", "description": "2889759488", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2889759488"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-09-18T00:00:00Z"}}, {"id": "3217045336", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:25:52Z", "type": "Journal Article", "created": "2021-11-29", "title": "Impacts of Farming Layer Constructions on Cultivated Land Quality under the Cultivated Land Balance Policy", "description": "

Cultivated Land Balance Policy (CLBP) has led to the \u201cbetter land occupied and worse land supplemented\u201d program. At the same time, the current field-scale cultivated land quality (CLQ) evaluation cannot meet the work requirements of the CLBP. To this end, this study selected 24 newly added farmland in Fuping County and performed eight different high quality farming layer construction experiments to improve the CLQ. A new comprehensive model was constructed on a field scale to evaluate the CLQ using different tests from multi-dimensional perspectives of soil fertility, engineering, environment, and ecology, and to determine the best test mode. The results showed that after the test, around 62% of the cultivated land improved by one level, and the average cultivated land quality level and quality index of the test area increased by 0.63 and 30.63, respectively. The treatment of \u201cwoody peat + rotten crop straw + biostimulation regulator II + conventional fertilization\u201d had the best effect on the improvement of organic matter, soil aggregates, and soil microbial activity, and was the best treatment method. In general, application of soil amendments, such as woody peat when constructing high quality farmland, could quickly improve CLQ, and field-scale CLQ evaluation model constructed from a multi-dimensional perspective could accurately assess the true quality of farmland and allow managers to improve and manage arable land resources under CLBP.

", "keywords": ["Scale (ratio)", "cultivated land quality evaluation", "Agricultural engineering", "Agricultural and Biological Sciences", "Engineering", "Soil Evaluation", "Agricultural land", "Soil water", "Arable land", "cultivated land quality evaluation; field scale; high-quality farming layer; woody peat", "2. Zero hunger", "Global and Planetary Change", "Global Analysis of Ecosystem Services and Land Use", "Geography", "Ecology", "S", "high-quality farming layer", "Life Sciences", "Land Suitability", "Land-Use Suitability Assessment Using GIS", "Land reclamation", "Agriculture", "04 agricultural and veterinary sciences", "woody peat", "Soil Erosion and Agricultural Sustainability", "Agricultural Land Use", "6. Clean water", "FOS: Philosophy", " ethics and religion", "Physical Sciences", "Quality (philosophy)", "field scale", "Cartography", "Soil Science", "Epistemology", "Management", " Monitoring", " Policy and Law", "Soil quality", "Environmental science", "Crop Suitability", "Agroforestry", "Biology", "Soil science", "Peat", "15. Life on land", "Topsoil", "Philosophy", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2403/pdf"}, {"href": "https://doi.org/3217045336"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3217045336", "name": "item", "description": "3217045336", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3217045336"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-25T00:00:00Z"}}, {"id": "PMC8824702", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:27:45Z", "type": "Journal Article", "created": "2021-06-29", "title": "Significant loss of soil inorganic carbon at the continental scale", "description": "Abstract

Widespread soil acidification due to atmospheric acid deposition and agricultural fertilization may greatly accelerate soil carbonate dissolution and CO2 release. However, to date, few studies have addressed these processes. Here, we use meta-analysis and nationwide-survey datasets to investigate changes in soil inorganic carbon (SIC) stocks in China. We observe an overall decrease in SIC stocks in topsoil (0\uffe2\uff80\uff9330\uffc2\uffa0cm) (11.33\uffc2\uffa0g C m\uffe2\uff80\uff932 yr\uffe2\uff80\uff931) from the 1980s to the 2010s. Total SIC stocks have decreased by \uffe2\uff88\uffbc8.99\uffc2\uffa0\uffc2\uffb1\uffc2\uffa02.24% (1.37\uffc2\uffa0\uffc2\uffb1\uffc2\uffa00.37\uffc2\uffa0Pg C). The average SIC losses across China (0.046 Pg C yr\uffe2\uff80\uff931) and in cropland (0.016 Pg C yr\uffe2\uff80\uff931) account for \uffe2\uff88\uffbc17.6%\uffe2\uff80\uff9324.0% of the terrestrial C sink and 57.1% of the soil organic carbon sink in cropland, respectively. Nitrogen deposition and climate change have profound influences on SIC cycling. We estimate that \uffe2\uff88\uffbc19.12%\uffe2\uff80\uff9319.47% of SIC stocks will be further lost by 2100. The consumption of SIC may offset a large portion of global efforts aimed at ecosystem carbon sequestration, which emphasizes the importance of achieving a better understanding of the indirect coupling mechanisms of nitrogen and carbon cycling and of effective countermeasures to minimize SIC loss.Managing agricultural watersheds in an environmentally friendly manner necessitate the strategic implementation of well-targeted sustainable land management (SLM) practices that limit soil and nonpoint source pollution losses and translocation. Watershed-scale SLM-scenario modeling has the potential to identify efficient and effective management strategies from the field to the integrated landscape level. In a case study targeting a 66-hectare watershed in Petzenkirchen, Lower Austria, the Soil and Water Assessment Tool (SWAT) was utilized to evaluate a variety of locally adoptable SLM practices. SWAT was calibrated and validated (monthly) at the catchment outlet for flow, sediment, nitrate-nitrogen (NO3\uffe2\uff80\uff93N), ammonium nitrogen (NH4\uffe2\uff80\uff93N), and mineralized phosphorus (PO4\uffe2\uff80\uff93P) using SWATplusR. Considering the locally existing agricultural practices and socioeconomic and environmental factors of the research area, four conservation practices were evaluated: baseline scenario, contour farming (CF), winter cover crops (CC), and a combination of no-till and cover crops (NT\uffe2\uff80\uff89+\uffe2\uff80\uff89CC). The NT\uffe2\uff80\uff89+\uffe2\uff80\uff89CC SLM practice was found to be the most effective soil conservation practice in reducing soil loss by around 80%, whereas CF obtained the best results for decreasing the nutrient loads of NO3\uffe2\uff80\uff93N and PO4\uffe2\uff80\uff93P by 11% and 35%, respectively. The findings of this study imply that the setup SWAT model can serve the context-specific performance assessment and eventual promotion of SLM interventions that mitigate on-site land degradation and the consequential off-site environmental pollution resulting from agricultural nonpoint sources.

The recent deployment of ESA\u2019s Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015\u2013November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m3/m3 and 0.059 m3/m3 for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded.

", "keywords": ["[SDE] Environmental Sciences", "NDVI", "Chemical technology", "HUMIDITE DU SOL", "soil moisture; SAR; Sentinel-1; NDVI; Sentinel-2; change detection", "0211 other engineering and technologies", "soil water content", "TP1-1185", "02 engineering and technology", "15. Life on land", "01 natural sciences", "Article", "remote sensing", "Sentinel-1", "cartography", "soil moisture", "Sentinel-2", "TELEDETECTION", "change detection", "CARTOGRAPHIE", "SAR", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/17/9/1966/pdf"}, {"href": "https://doi.org/PMC5621168"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sensors", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC5621168", "name": "item", "description": "PMC5621168", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC5621168"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-08-26T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Cartography&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=Cartography&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=Cartography&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Cartography&offset=18", "hreflang": "en-US"}], "numberMatched": 18, "numberReturned": 18, "distributedFeatures": [], "timeStamp": "2026-05-25T02:11:04.614527Z"}