{"type": "FeatureCollection", "features": [{"id": "10.3390/rs13214195", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:20:56Z", "type": "Journal Article", "created": "2021-10-20", "title": "Sentinel-2 Recognition of Uncovered and Plastic Covered Agricultural Soil", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Medium resolution satellite data, such as Sentinel-2 of the Copernicus programme, offer great new opportunities for the agricultural sector, and provide insights on soil surface characteristics and their management. Soil monitoring requires a high-quality dataset of uncovered and plastic covered agricultural soil. We developed a methodology to identify uncovered soil pixels in agricultural parcels during seedbed preparation and considered the impacts of clouds and shadows, vegetation cover, and artificial covers, such as those of greenhouses and plastic mulch films. We preserved the spatial and temporal integrity of parcels in the process and analysed spectral anomalies and their sources. The approach is based on freely available tools, namely Google Earth Engine and R Programming packages. We tested the methodology on the northern region of Belgium, which is characterised by small, fragmented parcels. We selected a period between mid-April to end-May, when active agricultural management practices leave the soil bare in preparation for the main cropping season. The spectral angle mapper was used to identify soil covered by non-plastic greenhouses or temporary soil covers, such as plastic mulch films. The effect of underlying soil on temporary covers was considered. The retrogressive plastic greenhouse index was used for detecting plastic greenhouses. The result was a high quality dataset of potential bare uncovered agricultural soil that allows further soil surface characterisation. This offered an improved understanding of the use of artificial covers, their spatial distribution, and their corresponding crops during the considered period. Artificial covers occurred most frequently in maize parcels. The approach resulted in precision values exceeding 0.9 for the detection of temporary covers and non-plastic greenhouses and a sensitivity value exceeding 0.95 for non-plastic and plastic greenhouses.</p></article>", "keywords": ["Technology", "SURFACE", "Science", "Environmental Sciences & Ecology", "TEXTURE", "artificial cover", "ALMERIA", "0203 Classical Physics", "soil", "Remote Sensing", "SUPPORT", "0909 Geomatic Engineering", "Geosciences", " Multidisciplinary", "Imaging Science & Photographic Technology", "agriculture", "2. Zero hunger", "plastic mulch", "Science & Technology", "IDENTIFICATION", "soil; agriculture; Sentinel-2; artificial cover; plastic mulch", "Q", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "CLOUD", "REFLECTANCE", "RESOLUTION", "13. Climate action", "Physical Sciences", "0401 agriculture", " forestry", " and fisheries", "4013 Geomatic engineering", "Sentinel-2", "GREENHOUSE", "0406 Physical Geography and Environmental Geoscience", "Life Sciences & Biomedicine", "3701 Atmospheric sciences", "Environmental Sciences", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/21/4195/pdf"}, {"href": "https://www.mdpi.com/2072-4292/13/21/4195/pdf"}, {"href": "https://doi.org/10.3390/rs13214195"}, {"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/rs13214195", "name": "item", "description": "10.3390/rs13214195", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs13214195"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-20T00:00:00Z"}}, {"id": "10.5194/tc-12-3293-2018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:21:53Z", "type": "Journal Article", "created": "2018-03-09", "title": "Carbonaceous material export from Siberian permafrost tracked across the Arctic Shelf using Raman spectroscopy", "description": "<p>Abstract. Warming-induced erosion of permafrost from Eastern Siberia mobilises large amounts of organic carbon and delivers it to the East Siberian Arctic Shelf (ESAS). In this study Raman spectroscopy of Carbonaceous Material (CM) was used to characterise, identify and track the most recalcitrant fraction of the organic load. 1463 spectra were obtained from surface sediments collected across the ESAS and automatically analysed for their Raman peaks. Spectra were classified by their peak areas and widths into Disordered, Intermediate, Mildly Graphitised and Highly Graphitised groups, and the distribution of these classes was investigated across the shelf. Disordered CM was most prevalent in a permafrost core from Kurungnakh Island, and from areas known to have high rates of coastal erosion. Sediments from outflows of the Indigirka and Kolyma rivers were generally enriched in Intermediate CM. These different sediment sources were identified and distinguished along an E-W transect using their Raman spectra, showing that sediment is not homogenised on the ESAS. Distal samples, from the ESAS slope, contained greater amounts of Highly Graphitised CM compared to the rest of the shelf, attributable to degradation or, more likely, winnowing processes offshore. The presence of all four spectral classes in distal sediments demonstrates that CM degrades much slower than lipid biomarkers and other traditional tracers of terrestrial organic matter, and shows that alongside degradation of the more labile organic matter component there is also conservative transport of carbon across the shelf toward the deep ocean. Thus, carbon cycle calculations must consider the nature as well as the amount of carbon liberated from thawing permafrost and other erosional settings.                         </p>", "keywords": ["Ocean", "River", "QE1-996.5", "550", "500", "Terrigenous Organic-Matter", "Geology", "Terrestrial", "Old Carbon", "01 natural sciences", "Sediments", "Environmental sciences", "Degradation", "13. Climate action", "Laptev Sea", "Meteorology & Atmospheric Sciences", "Graphite", "GE1-350", "0405 Oceanography", "14. Life underwater", "Black Carbon", "0406 Physical Geography And Environmental Geoscience", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://tc.copernicus.org/articles/12/3293/2018/tc-12-3293-2018.pdf"}, {"href": "https://doi.org/10.5194/tc-12-3293-2018"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20Cryosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/tc-12-3293-2018", "name": "item", "description": "10.5194/tc-12-3293-2018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/tc-12-3293-2018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-09T00:00:00Z"}}, {"id": "10.5194/tc-2018-16", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:21:53Z", "type": "Journal Article", "created": "2018-03-09", "title": "Carbonaceous material export from Siberian permafrost tracked across the Arctic Shelf using Raman spectroscopy", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Warming-induced erosion of permafrost from Eastern Siberia mobilises large amounts of organic carbon and delivers it to the East Siberian Arctic Shelf (ESAS). In this study Raman spectroscopy of Carbonaceous Material (CM) was used to characterise, identify and track the most recalcitrant fraction of the organic load. 1463 spectra were obtained from surface sediments collected across the ESAS and automatically analysed for their Raman peaks. Spectra were classified by their peak areas and widths into Disordered, Intermediate, Mildly Graphitised and Highly Graphitised groups, and the distribution of these classes was investigated across the shelf. Disordered CM was most prevalent in a permafrost core from Kurungnakh Island, and from areas known to have high rates of coastal erosion. Sediments from outflows of the Indigirka and Kolyma rivers were generally enriched in Intermediate CM. These different sediment sources were identified and distinguished along an E-W transect using their Raman spectra, showing that sediment is not homogenised on the ESAS. Distal samples, from the ESAS slope, contained greater amounts of Highly Graphitised CM compared to the rest of the shelf, attributable to degradation or, more likely, winnowing processes offshore. The presence of all four spectral classes in distal sediments demonstrates that CM degrades much slower than lipid biomarkers and other traditional tracers of terrestrial organic matter, and shows that alongside degradation of the more labile organic matter component there is also conservative transport of carbon across the shelf toward the deep ocean. Thus, carbon cycle calculations must consider the nature as well as the amount of carbon liberated from thawing permafrost and other erosional settings.                         </p></article>", "keywords": ["Ocean", "River", "QE1-996.5", "550", "500", "Terrigenous Organic-Matter", "Geology", "Terrestrial", "Old Carbon", "01 natural sciences", "Sediments", "Environmental sciences", "Degradation", "13. Climate action", "Laptev Sea", "Meteorology & Atmospheric Sciences", "Graphite", "GE1-350", "0405 Oceanography", "14. Life underwater", "Black Carbon", "0406 Physical Geography And Environmental Geoscience", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://tc.copernicus.org/articles/12/3293/2018/tc-12-3293-2018.pdf"}, {"href": "https://doi.org/10.5194/tc-2018-16"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20Cryosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/tc-2018-16", "name": "item", "description": "10.5194/tc-2018-16", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/tc-2018-16"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-09T00:00:00Z"}}, {"id": "1854/LU-8751352", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:10Z", "type": "Journal Article", "created": "2022-03-29", "title": "Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil surveys with line-scanning platforms appear to have great advantages over the traditional methods used to collect soil information for the development of field-scale soil mapping and applications. These carry VNIR (visible and near infrared) spectrometers and have been used in recent years extensively for the assessment of soil fertility at the field scale, and the delineation of site-specific management zones (MZ). A challenging feature of VNIR applications in precision agriculture (PA) is the massiveness of the derived datasets that contain point predictions of soil properties, and the interpolation techniques involved in incorporating these data into site-specific management plans. In this study, fixed-rank kriging (FRK) geostatistical interpolation, which is a flexible, non-stationary spatial interpolation method especially suited to handling huge datasets, was applied to massive VNIR soil scanner data for the production of useful, smooth interpolated maps, appropriate for the delineation of site-specific MZ maps. Moreover, auxiliary Sentinel-2 data-based biophysical parameters NDVI (normalized difference vegetation index) and fAPAR (fraction of photosynthetically active radiation absorbed by the canopy) were included as covariates to improve the filtering performance of the interpolator and the ability to generate uniform patterns of spatial variation from which it is easier to receive a meaningful interpretation in PA applications. Results from the VNIR prediction dataset obtained from a pivot-irrigated field in Albacete, southeastern Spain, during 2019, have shown that FRK variants outperform ordinary kriging in terms of filtering capacity, by doubling the noise removal metrics while keeping the computation cost reasonably low. Such features, along with the capacity to handle a large volume of spatial information, nominate the method as ideal for PA applications with massive proximal and remote sensing datasets.</p></article>", "keywords": ["Technology", "MANAGEMENT ZONES", "PREDICTION", "NDVI", "SPATIAL VARIABILITY", "Science", "MODELS", "PHYSICAL-PROPERTIES", "ONLINE", "Environmental Sciences & Ecology", "VNIR spectrometer", "geostatistical interpolation", "VARIABLES", "0203 Classical Physics", "Remote Sensing", "geostatistical interpolation; VNIR spectrometer; NDVI; fAPAR; precision agriculture", "0909 Geomatic Engineering", "QUALITY", "DATA FUSION", "Geosciences", " Multidisciplinary", "Imaging Science & Photographic Technology", "agriculture", "Science & Technology", "precision agriculture", "Q", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "DELINEATION", "Earth and Environmental Sciences", "Physical Sciences", "fAPAR", "0401 agriculture", " forestry", " and fisheries", "precision", "4013 Geomatic engineering", "0406 Physical Geography and Environmental Geoscience", "Life Sciences & Biomedicine", "3701 Atmospheric sciences", "Environmental Sciences", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/14/7/1639/pdf"}, {"href": "https://www.mdpi.com/2072-4292/14/7/1639/pdf"}, {"href": "https://doi.org/1854/LU-8751352"}, {"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": "1854/LU-8751352", "name": "item", "description": "1854/LU-8751352", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8751352"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-29T00:00:00Z"}}, {"id": "10261/277923", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:24:37Z", "type": "Journal Article", "created": "2022-07-18", "title": "Net irrigation requirement under different climate scenarios using AquaCrop over Europe", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70\u2009% of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5\u2218lat\u00d70.5\u2218long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06\u2009m3\u2009m\u22123, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015\u20132016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015\u20132020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031\u20132060 and 2071\u20132100) is compared to the baseline period of 1985\u20132014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22\u2009mm per month (+30\u2009%) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3\u20137.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1\u20132.6), the increase in Inet will stabilize at around 13\u2009mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.</p></article>", "keywords": ["IMPACTS", "LAND", "Technology", "Environmental Engineering", "AGRICULTURE", "DEFICIT IRRIGATION", "SIMULATE YIELD RESPONSE", "0207 environmental engineering", "UNCERTAINTY", "02 engineering and technology", "CROP WATER PRODUCTIVITY", "Environmental technology. Sanitary engineering", "01 natural sciences", "0905 Civil Engineering", "G", "DATA ASSIMILATION", "Geography. Anthropology. Recreation", "GE1-350", "Geosciences", " Multidisciplinary", "TD1-1066", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "3707 Hydrology", "T", "Geology", "15. Life on land", "TRENDS", "6. Clean water", "MODEL", "Environmental sciences", "0907 Environmental Engineering", "13. Climate action", "Physical Sciences", "Water Resources", "4013 Geomatic engineering", "0406 Physical Geography and Environmental Geoscience", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "https://biblio.vub.ac.be/vubirfiles/86261359/Busschaert_etal_2022_HESS.pdf"}, {"href": "https://hess.copernicus.org/articles/26/3731/2022/hess-26-3731-2022.pdf"}, {"href": "https://doi.org/10261/277923"}, {"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": "10261/277923", "name": "item", "description": "10261/277923", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/277923"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-12T00:00:00Z"}}, {"id": "11585/910145", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:00Z", "type": "Journal Article", "created": "2021-11-09", "title": "The International Soil Moisture Network: serving  Earth system science for over a decade", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. In\u00a02009, the International Soil Moisture Network\u00a0(ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et\u00a0al.,\u00a02011b, a). The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal (https://ismn.earth/en/, last access: 28\u00a0October\u00a02021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000\u00a0active users and over 1000\u00a0scientific publications referencing the data sets provided by the network. As of July\u00a02021, the ISMN now contains the data of 71\u00a0networks and 2842\u00a0stations located all over the globe, with a time period spanning from\u00a01952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70\u2009% of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository.</p></article>", "keywords": ["[SDE] Environmental Sciences", "Technology", "Atmospheric Science", "550", "Soil Moisture", "TA Engineering (General). Civil engineering (General)", "02 engineering and technology", "Soil Moisture; ISMN; IMA_CAN1; swc; STEMS", "SMOS BRIGHTNESS TEMPERATURE", "Spatial variability", "Environmental technology. Sanitary engineering", "01 natural sciences", "Agency (philosophy)", "remote sensing", "Antecedent wetness conditions", "Engineering", "Geography. Anthropology. Recreation", "GE1-350", "Geosciences", " Multidisciplinary", "TD1-1066", "Smos brightness temperature", "Heihe river-basin", "T", "Soil Water Retention", "Geology", "Leaf-area index", "004", "FOS: Philosophy", " ethics and religion", "Programming language", "HEIHE RIVER-BASIN", "Earth and Planetary Sciences", "Physical Sciences", "Water Resources", "name=Water Science and Technology", "/dk/atira/pure/subjectarea/asjc/1900/1901", "Medicine", "0406 Physical Geography and Environmental Geoscience", "name=Earth and Planetary Sciences (miscellaneous)", "3709 Physical geography and environmental geoscience", "Mechanics and Transport in Unsaturated Soils", "Environmental Engineering", "SPATIAL VARIABILITY", "IN-SITU MEASUREMENTS", "0207 environmental engineering", "Epistemology", "0905 Civil Engineering", "Environmental science", "G", "Database", "LAND DATA ASSIMILATION", "Soil Moisture; network", "WIRELESS SENSOR NETWORK", "Arctic Permafrost Dynamics and Climate Change", "Scope (computer science)", "Land data assimilation", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "info:eu-repo/classification/ddc/550", "Science & Technology", "3707 Hydrology", "Consecutive dry days", "LEAF-AREA INDEX", "in situ", "FOS: Environmental engineering", "AMSR-E", "15. Life on land", "Remote Sensing of Soil Moisture", "ANTECEDENT WETNESS CONDITIONS", "Globe", "Computer science", "Environmental sciences", "QE Geology", "0907 Environmental Engineering", "Philosophy", "Ophthalmology", "In-situ measurements", "13. Climate action", "ITC-ISI-JOURNAL-ARTICLE", "global scale", "Environmental Science", "G70.212-70.215 Geographic information system", "4013 Geomatic engineering", "soil moisture", "CONSECUTIVE DRY DAYS", "ITC-GOLD", "/dk/atira/pure/subjectarea/asjc/2300/2312", "Wireless sensor network"]}, "links": [{"href": "https://iris.polito.it/bitstream/11583/2998914/1/prod_447100-doc_161016.pdf"}, {"href": "https://iris.polito.it/bitstream/11583/2998914/2/prod_447100-doc_178365.pdf"}, {"href": "https://cris.unibo.it/bitstream/11585/910145/1/Dourigo_etal_2021.pdf"}, {"href": "https://doi.org/11585/910145"}, {"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": "11585/910145", "name": "item", "description": "11585/910145", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11585/910145"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-09T00:00:00Z"}}, {"id": "1871.1/270d8bb4-64f4-4f60-b44e-492fcf327fc8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:10Z", "type": "Journal Article", "created": "2024-02-09", "title": "Improving the fire weather index system for peatlands using peat-specific hydrological input data", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.</p></article>", "keywords": ["CARBON SINK", "Environmental technology. Sanitary engineering", "01 natural sciences", "G", "4406 Human geography", "Geography. Anthropology. Recreation", "Meteorology & Atmospheric Sciences", "GE1-350", "ALGORITHM", "Geosciences", " Multidisciplinary", "TD1-1066", "0105 earth and related environmental sciences", "QE1-996.5", "Science & Technology", "CLIMATE-CHANGE", "Strategic", " Defence & Security Studies", "CONSUMPTION", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "Environmental sciences", "SEVERITY", "0403 Geology", "0911 Maritime Engineering", "13. Climate action", "Physical Sciences", "Water Resources", "0401 agriculture", " forestry", " and fisheries", "0406 Physical Geography and Environmental Geoscience", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "https://nhess.copernicus.org/articles/24/445/2024/nhess-24-445-2024.pdf"}, {"href": "https://doi.org/1871.1/270d8bb4-64f4-4f60-b44e-492fcf327fc8"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Natural%20Hazards%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1871.1/270d8bb4-64f4-4f60-b44e-492fcf327fc8", "name": "item", "description": "1871.1/270d8bb4-64f4-4f60-b44e-492fcf327fc8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1871.1/270d8bb4-64f4-4f60-b44e-492fcf327fc8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-09T00:00:00Z"}}, {"id": "1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:09Z", "type": "Journal Article", "created": "2023-05-13", "title": "Optimisation of AquaCrop backscatter simulations using Sentinel-1 observations", "description": "Open AccessIn preparation for active microwave-based data assimilation into a crop modeling system, the mapping of daily 1-km AquaCrop model (v6.1) biomass and surface soil moisture to backscatter was optimised, using two forward operators, i.e. the Water Cloud Model (WCM) and the Support Vector Regression (SVR). Both forward operators were calibrated (2014\u20132018) with 1-km Sentinel-1 backscatter (\u03d2\u00b0) observations in VV and VH polarisation, for three different study domains in Europe. For the validation period (2019\u20132021), the \u03d2\u00b0 simulations showed reasonable performances around Czech Republic and the Iberian Peninsula, to good performances over Belgium, but with strong variations within each domain. The domain-averaged root mean square difference between the model and Sentinel-1 \u03d2\u00b0 remained below 2 dB for both forward operators and all three study domains, and the mean bias for VV remained close to 0 dB, and close 0.5 dB for the VH polarisation. The WCM and SVR performed better in VV than VH and overall the SVR performed slightly better in mapping the AquaCrop soil moisture and vegetation to backscatter than the WCM. Additionally, the assumed linear relationship in the WCM between soil moisture and soil \u03d2\u00b0 holds better for VV than for VH. The remaining differences between WCM or SVR simulations and Sentinel-1 observations are mainly caused by AquaCrop model errors.", "keywords": ["Agriculture and Food Sciences", "Technology", "ASSIMILATION", "Sentine;-1", "Environmental Sciences & Ecology", "Geological & Geomatics Engineering", "BIOMASS", "Remote Sensing", "SAR BACKSCATTER", "SURFACE SOIL-MOISTURE", "SUPPORT", "0909 Geomatic Engineering", "WATER", "FAO CROP MODEL", "Imaging Science & Photographic Technology", "crop biomass", "Crop biomass", "YIELD RESPONSE", "Science & Technology", "backscatter modelling", "Backscatter modeling", "LEAF-AREA INDEX", "RADAR BACKSCATTER", "37 Earth sciences", "AquaCrop optimisation", "13. Climate action", "Earth and Environmental Sciences", "Sentinel-1", "Soil moisture", "0406 Physical Geography and Environmental Geoscience", "Life Sciences & Biomedicine", "Environmental Sciences"]}, "links": [{"href": "https://biblio.vub.ac.be/vubirfiles/112110259/108189295.pdf"}, {"href": "https://doi.org/1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing%20of%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4", "name": "item", "description": "1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-01T00:00:00Z"}}, {"id": "1854/LU-01GM39MMFY2YP4FTDY102R50HB", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:09Z", "type": "Journal Article", "created": "2021-11-17", "title": "Spatiotemporal Prediction and Mapping of Heavy Metals at Regional Scale Using Regression Methods and Landsat 7", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil contamination by heavy metals is of particular concern, due to the direct negative impact on crop yield, food quality and human health. Although the conventional approach to monitor heavy metals relies on field sampling and lab analysis, the proliferation in the use of portable spectrometers has reduced the cost and time of investigation. However, discrepancies in spectral data from different spectrometers increase the modeling time and undermine the model accuracy for spatial mapping. This study, therefore, took advantage of the readily accessible Landsat 7 data to predict and map the spatiotemporal distribution of ten heavy metals (i.e., Sb, Pb, Ni, Mn, Hg, Cu, Cr, Co, Cd and As) over a 640 km2 area in Belgium. The Land Use/Cover Area Frame Survey (LUCAS) database of a region in north-eastern Belgium was used to retrieve variation in heavy metals concentrations over time and space, using the Landsat 7 imagery for four single dates in 2009, 2013, 2016 and 2020. Three regression methods, namely, partial least squares regression (PLSR), random forest (RF) and support vector machine (SVM) were used to model and predict the heavy metal concentrations for 2009. By comparing these models unbiasedly, the best model was selected for predicting and mapping the heavy metal distributions for 2013, 2016 and 2020. RF turned out to be the optimal model for 2009 with a coefficient of determination of prediction (R2P) and residual prediction deviation of prediction (RPDP) ranging from 0.62 to 0.92, and 1.23 to 2.79, respectively. The measured heavy metal distributions along the river floodplains, at the highlands and in the lowlands, were generally high, compared to their RF spatiotemporal predictions, which decreased over time. Increasing moisture contents in the floodplains adjacent to the river channels and the lowlands were the primary contributors to the reduction in the satellite reflectance spectra. However, topsoil erosion from rainfall, snowmelt as well as wind into the lowlands could have influenced the reduction in heavy metal spatiotemporal predicted values over time in the highlands. The spatiotemporal prediction maps produced for the heavy metals for the four different years revealed a good spatial similarity and consistency with the measured maps for 2009, which indicates their stability over the years.</p></article>", "keywords": ["Technology", "PROVINCE", "Landsat 7", "analysis", "Science", "Environmental Sciences & Ecology", "random forest (RF)", "MOISTURE", "01 natural sciences", "NIR SPECTROSCOPY", "0203 Classical Physics", "Remote Sensing", "0909 Geomatic Engineering", "spatiotemporal analysis", "AGRICULTURAL SOILS", "Geosciences", " Multidisciplinary", "Imaging Science & Photographic Technology", "spatiotemporal", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "RANGE", "Q", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "3. Good health", "MULTIVARIATE", "TOPSOILS", "13. Climate action", "Earth and Environmental Sciences", "Physical Sciences", "soil heavy metal; Landsat 7; partial least squares regression (PLSR); random forest (RF); support vector machine (SVM); spatiotemporal analysis", "0401 agriculture", " forestry", " and fisheries", "support vector machine (SVM)", "4013 Geomatic engineering", "0406 Physical Geography and Environmental Geoscience", "soil heavy metal", "partial least squares regression (PLSR)", "Life Sciences & Biomedicine", "3701 Atmospheric sciences", "Environmental Sciences", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/22/4615/pdf"}, {"href": "https://www.mdpi.com/2072-4292/13/22/4615/pdf"}, {"href": "https://doi.org/1854/LU-01GM39MMFY2YP4FTDY102R50HB"}, {"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": "1854/LU-01GM39MMFY2YP4FTDY102R50HB", "name": "item", "description": "1854/LU-01GM39MMFY2YP4FTDY102R50HB", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-01GM39MMFY2YP4FTDY102R50HB"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-16T00:00:00Z"}}, {"id": "1983/5da4f0df-4d79-4aa3-9d5e-3d013ed9c52d", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:16Z", "type": "Journal Article", "created": "2018-03-09", "title": "Carbonaceous material export from Siberian permafrost tracked across the Arctic Shelf using Raman spectroscopy", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Warming-induced erosion of permafrost from Eastern Siberia mobilises large amounts of organic carbon and delivers it to the East Siberian Arctic Shelf (ESAS). In this study Raman spectroscopy of Carbonaceous Material (CM) was used to characterise, identify and track the most recalcitrant fraction of the organic load. 1463 spectra were obtained from surface sediments collected across the ESAS and automatically analysed for their Raman peaks. Spectra were classified by their peak areas and widths into Disordered, Intermediate, Mildly Graphitised and Highly Graphitised groups, and the distribution of these classes was investigated across the shelf. Disordered CM was most prevalent in a permafrost core from Kurungnakh Island, and from areas known to have high rates of coastal erosion. Sediments from outflows of the Indigirka and Kolyma rivers were generally enriched in Intermediate CM. These different sediment sources were identified and distinguished along an E-W transect using their Raman spectra, showing that sediment is not homogenised on the ESAS. Distal samples, from the ESAS slope, contained greater amounts of Highly Graphitised CM compared to the rest of the shelf, attributable to degradation or, more likely, winnowing processes offshore. The presence of all four spectral classes in distal sediments demonstrates that CM degrades much slower than lipid biomarkers and other traditional tracers of terrestrial organic matter, and shows that alongside degradation of the more labile organic matter component there is also conservative transport of carbon across the shelf toward the deep ocean. Thus, carbon cycle calculations must consider the nature as well as the amount of carbon liberated from thawing permafrost and other erosional settings.</p></article>", "keywords": ["Ocean", "River", "QE1-996.5", "550", "500", "Terrigenous Organic-Matter", "Geology", "Terrestrial", "Old Carbon", "01 natural sciences", "Sediments", "Environmental sciences", "Degradation", "13. Climate action", "Laptev Sea", "Meteorology & Atmospheric Sciences", "Graphite", "GE1-350", "0405 Oceanography", "14. Life underwater", "Black Carbon", "0406 Physical Geography And Environmental Geoscience", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://tc.copernicus.org/articles/12/3293/2018/tc-12-3293-2018.pdf"}, {"href": "https://doi.org/1983/5da4f0df-4d79-4aa3-9d5e-3d013ed9c52d"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20Cryosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1983/5da4f0df-4d79-4aa3-9d5e-3d013ed9c52d", "name": "item", "description": "1983/5da4f0df-4d79-4aa3-9d5e-3d013ed9c52d", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1983/5da4f0df-4d79-4aa3-9d5e-3d013ed9c52d"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-09T00:00:00Z"}}, {"id": "20.500.11850/688246", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:24Z", "type": "Journal Article", "created": "2024-07-29", "title": "Hydro-pedotransfer functions: a roadmap for future development", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Hydro-pedotransfer functions\u00a0(PTFs) relate easy-to-measure and readily available soil information to soil hydraulic properties\u00a0(SHPs) for applications in a wide range of process-based and empirical models, thereby enabling the assessment of soil hydraulic effects on hydrological, biogeochemical, and ecological processes. At least more than 4 decades of research have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental concerns related to the scope and adequacy of current PTFs, particularly when applied to parameterise models used at the field scale and beyond. Most of the PTF development process has focused on refining and advancing the regression methods, while fundamental aspects have remained largely unconsidered. Most soil systems are not represented in PTFs, which have been built mostly for agricultural soils in temperate climates. Thus, existing PTFs largely ignore how parent material, vegetation, land use, and climate affect processes that shape SHPs. The PTFs used to parameterise the Richards\u2013Richardson equation are mostly limited to predicting parameters of the van\u00a0Genuchten\u2013Mualem soil hydraulic functions, despite sufficient evidence demonstrating their shortcomings. Another fundamental issue relates to the diverging scales of derivation and application, whereby PTFs are derived based on laboratory measurements while often being applied at the field to regional scales. Scaling, modulation, and constraining strategies exist to alleviate some of these shortcomings in the mismatch between scales. These aspects are addressed here in a joint effort by the members of the International Soil Modelling Consortium\u00a0(ISMC) Pedotransfer Functions Working Group with the aim of systematising PTF research and providing a roadmap guiding both PTF development and use. We close with a 10-point catalogue for funders and researchers to guide review processes and research.</p></article>", "keywords": ["Technology", "550", "Bodenanalyse", "Modell", "SPHAGNUM MOSS", "Environmental technology. Sanitary engineering", "630", "Ing\u00e9nierie", " informatique & technologie", "Biogeochemical process", "Earth and Planetary Sciences (miscellaneous)", "Geography. Anthropology. Recreation", "GE1-350", "SATURATED HYDRAULIC CONDUCTIVITY", "Geosciences", " Multidisciplinary", "TD1-1066", "Water Science and Technology", "2. Zero hunger", "T", "Geology", "Hydraulics effects", "Agriculture & agronomy", "Life sciences", "Daten", "Pedo-transfer functions", "6. Clean water", "Soil hydraulics", "REFLECTANCE SPECTROSCOPY", "Roadmap", "Physical Sciences", "Sciences du vivant", "Water Resources", "SOIL-WATER-RETENTION", "0406 Physical Geography and Environmental Geoscience", "3709 Physical geography and environmental geoscience", "Process-based modeling", "Environmental Engineering", "Physique", " chimie", " math\u00e9matiques & sciences de la terre", "PHYSICAL-PROPERTIES", "SENSITIVITY-ANALYSIS", "Soil hydraulic properties", "0905 Civil Engineering", "333", "G", "Physical", " chemical", " mathematical & earth Sciences", "Empirical model", "Agriculture & agronomie", "Life Science", "UNSATURATED CONDUCTIVITY", "SEASONAL-CHANGES", "Pedotransfer functions", "HYSTERETIC MOISTURE PROPERTIES", "info:eu-repo/classification/ddc/550", "Science & Technology", "3707 Hydrology", "Physikochemische Bodeneigenschaft", "500", "15. Life on land", "Engineering", " computing & technology", "Sciences de la terre & g\u00e9ographie physique", "Environmental sciences", "0907 Environmental Engineering", "13. Climate action", "ITC-ISI-JOURNAL-ARTICLE", "Earth sciences & physical geography", "HETEROGENEOUS SOILS", "4013 Geomatic engineering", "ITC-GOLD", "Hydrological process"]}, "links": [{"href": "https://orbi.uliege.be/bitstream/2268/321088/1/hess-28-3391-2024.pdf"}, {"href": "https://hess.copernicus.org/articles/28/3391/2024/hess-28-3391-2024.pdf"}, {"href": "https://doi.org/20.500.11850/688246"}, {"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": "20.500.11850/688246", "name": "item", "description": "20.500.11850/688246", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/688246"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-29T00:00:00Z"}}, {"id": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:26Z", "type": "Journal Article", "created": "2022-07-18", "title": "Net irrigation requirement under different climate scenarios using AquaCrop over Europe", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70\u2009% of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5\u2218lat\u00d70.5\u2218long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06\u2009m3\u2009m\u22123, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015\u20132016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015\u20132020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031\u20132060 and 2071\u20132100) is compared to the baseline period of 1985\u20132014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22\u2009mm per month (+30\u2009%) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3\u20137.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1\u20132.6), the increase in Inet will stabilize at around 13\u2009mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.                     </p></article>", "keywords": ["IMPACTS", "LAND", "Technology", "Environmental Engineering", "AGRICULTURE", "DEFICIT IRRIGATION", "SIMULATE YIELD RESPONSE", "0207 environmental engineering", "UNCERTAINTY", "02 engineering and technology", "CROP WATER PRODUCTIVITY", "Environmental technology. Sanitary engineering", "01 natural sciences", "0905 Civil Engineering", "G", "DATA ASSIMILATION", "Geography. Anthropology. Recreation", "GE1-350", "Geosciences", " Multidisciplinary", "TD1-1066", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "3707 Hydrology", "T", "Geology", "15. Life on land", "TRENDS", "6. Clean water", "MODEL", "Environmental sciences", "0907 Environmental Engineering", "13. Climate action", "Physical Sciences", "Water Resources", "4013 Geomatic engineering", "0406 Physical Geography and Environmental Geoscience", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "https://hess.copernicus.org/articles/26/3731/2022/hess-26-3731-2022.pdf"}, {"href": "https://doi.org/20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8"}, {"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": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "name": "item", "description": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-12T00:00:00Z"}}, {"id": "2164/6134", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:37Z", "type": "Journal Article", "created": "2016-05-13", "title": "Modeling Soil Processes: Review, Key Challenges, and New Perspectives", "description": "Core Ideas                     <p>                                                                           <p>A community effort is needed to move soil modeling forward.</p>                                                                             <p>Establishing an international soil modeling consortium is key in this respect.</p>                                                                             <p>There is a need to better integrate existing knowledge in soil models.</p>                                                                             <p>Integration of data and models is a key challenge in soil modeling.</p>                                                                     </p>                     <p>The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate\uffe2\uff80\uff90change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.</p>", "keywords": ["organic-matter dynamics", "550", "Sciences de l\u2019environnement & \u00e9cologie", "QH301 Biology", "Knowledge management", "0208 environmental biotechnology", "ECOSYSTEM SERVICES", "02 engineering and technology", "soil processes", "01 natural sciences", "Physical Geography and Environmental Geoscience", "Sciences de la Terre", "Biological process", "ANZSRC::3707 Hydrology", "DROUGHT SEVERITY INDEX", "SYNTHETIC-APERTURE RADAR", "ANZSRC::4106 Soil sciences", "SDG 13 - Climate Action", "Climate change", "0503 Soil Sciences", "GROUND-PENETRATING RADAR", "Integration of knowledge", "Life sciences", "ANZSRC::050399 Soil Sciences not elsewhere classified", "synthetic-aperture radar", "Physical Sciences", "Water Resources", "Knowledge and experience", "MULTIPLE ECOSYSTEM SERVICES", "knowledge integration", "570", "DIFFUSE-REFLECTANCE SPECTROSCOPY", "Environmental Engineering", "Physique", " chimie", " math\u00e9matiques & sciences de la terre", "Scientific discipline", "0703 Crop and Pasture Production", "0207 environmental engineering", "Soil Science", "soil science", "ORGANIC-MATTER DYNAMICS", "DATA ASSIMILATION", "Physical", " chemical", " mathematical & earth Sciences", "ANZSRC::0503 Soil Sciences", "Science disciplines", "PEDOTRANSFER FUNCTIONS", "Feedback mechanisms", "mod\u00e9lisation", "ground-penetrating radar", "Science & Technology", "ANZSRC::080110 Simulation and Modelling", "15. Life on land", "Sciences de la terre & g\u00e9ographie physique", "multiple ecosystem services", "root water-uptake", "Observation and measurement", "DIGITAL ELEVATION MODEL", "Quality of predictions", "SATURATED-UNSATURATED FLOW", "ARBUSCULAR MYCORRHIZAL FUNGI", "sciences du sol", "HYDRAULIC-PROPERTIES", "2. Zero hunger", "Agriculture", "diffuse-reflectance spectroscopy", "4106 Soil sciences", "ORGANIC-MATTER", "digital elevation model", "SDG 13 \u2013 Ma\u00dfnahmen zum Klimaschutz", "Sciences du vivant", "Uncertainty analysis", "0406 Physical Geography and Environmental Geoscience", "Life Sciences & Biomedicine", "Crop and Pasture Production", "101028 Mathematical modelling", "international soil modeling consortium", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Environmental Sciences & Ecology", "arbuscular mycorrhizal fungi", "Ecosystems", "Climate models", "QH301", "Environmental sciences & ecology", "Life Science", "SEDIMENT TRANSPORT MODELS", "data integration", "sediment transport models", "approche ecosyst\u00e9mique", "0105 earth and related environmental sciences", "info:eu-repo/classification/ddc/550", "3707 Hydrology", "soil modeling", "ROOT WATER-UPTAKE", "SOLUTE TRANSPORT", "13. Climate action", "Earth and Environmental Sciences", "Soil Sciences", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "Earth Sciences", "Earth sciences & physical geography", "Soils", "101028 Mathematische Modellierung", "saturated-unsaturated flow", "Environmental Sciences", "root water-uptake", " sediment transport models", " diffuse-reflectance spectroscopy", " arbuscular mycorrhizal fungi", " multiple ecosystem services", " saturated-unsaturated flow", " ground-penetrating radar", " synthetic-aperture radar", " digital elevation model", " organic-matter dynamics."]}, "links": [{"href": "https://orbi.uliege.be/bitstream/2268/263634/1/Vereecken%20VZJ%202016.pdf"}, {"href": "http://onlinelibrary.wiley.com/wol1/doi/10.2136/vzj2015.09.0131/fullpdf"}, {"href": "https://escholarship.org/content/qt6976n34c/qt6976n34c.pdf"}, {"href": "https://doi.org/2164/6134"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Vadose%20Zone%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2164/6134", "name": "item", "description": "2164/6134", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2164/6134"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-05-01T00:00:00Z"}}, {"id": "3207901193", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:26:17Z", "type": "Journal Article", "created": "2021-10-21", "title": "Sentinel-2 Recognition of Uncovered and Plastic Covered Agricultural Soil", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Medium resolution satellite data, such as Sentinel-2 of the Copernicus programme, offer great new opportunities for the agricultural sector, and provide insights on soil surface characteristics and their management. Soil monitoring requires a high-quality dataset of uncovered and plastic covered agricultural soil. We developed a methodology to identify uncovered soil pixels in agricultural parcels during seedbed preparation and considered the impacts of clouds and shadows, vegetation cover, and artificial covers, such as those of greenhouses and plastic mulch films. We preserved the spatial and temporal integrity of parcels in the process and analysed spectral anomalies and their sources. The approach is based on freely available tools, namely Google Earth Engine and R Programming packages. We tested the methodology on the northern region of Belgium, which is characterised by small, fragmented parcels. We selected a period between mid-April to end-May, when active agricultural management practices leave the soil bare in preparation for the main cropping season. The spectral angle mapper was used to identify soil covered by non-plastic greenhouses or temporary soil covers, such as plastic mulch films. The effect of underlying soil on temporary covers was considered. The retrogressive plastic greenhouse index was used for detecting plastic greenhouses. The result was a high quality dataset of potential bare uncovered agricultural soil that allows further soil surface characterisation. This offered an improved understanding of the use of artificial covers, their spatial distribution, and their corresponding crops during the considered period. Artificial covers occurred most frequently in maize parcels. The approach resulted in precision values exceeding 0.9 for the detection of temporary covers and non-plastic greenhouses and a sensitivity value exceeding 0.95 for non-plastic and plastic greenhouses.</p></article>", "keywords": ["Technology", "SURFACE", "Science", "Environmental Sciences & Ecology", "TEXTURE", "artificial cover", "ALMERIA", "0203 Classical Physics", "soil", "Remote Sensing", "SUPPORT", "0909 Geomatic Engineering", "Geosciences", " Multidisciplinary", "Imaging Science & Photographic Technology", "agriculture", "2. Zero hunger", "plastic mulch", "Science & Technology", "IDENTIFICATION", "soil; agriculture; Sentinel-2; artificial cover; plastic mulch", "Q", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "CLOUD", "REFLECTANCE", "RESOLUTION", "13. Climate action", "Physical Sciences", "0401 agriculture", " forestry", " and fisheries", "4013 Geomatic engineering", "Sentinel-2", "GREENHOUSE", "0406 Physical Geography and Environmental Geoscience", "Life Sciences & Biomedicine", "3701 Atmospheric sciences", "Environmental Sciences", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/21/4195/pdf"}, {"href": "https://www.mdpi.com/2072-4292/13/21/4195/pdf"}, {"href": "https://doi.org/3207901193"}, {"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": "3207901193", "name": "item", "description": "3207901193", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3207901193"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-20T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=0406+Physical+Geography+and+Environmental+Geoscience&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=0406+Physical+Geography+and+Environmental+Geoscience&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=0406+Physical+Geography+and+Environmental+Geoscience&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=0406+Physical+Geography+and+Environmental+Geoscience&offset=14", "hreflang": "en-US"}], "numberMatched": 14, "numberReturned": 14, "distributedFeatures": [], "timeStamp": "2026-07-27T05:19:36.475669Z"}