{"type": "FeatureCollection", "features": [{"id": "10.1016/j.envpol.2021.118128", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:16:39Z", "type": "Journal Article", "created": "2021-09-09", "title": "Diagnosis of cadmium contamination in urban and suburban soils using visible-to-near-infrared spectroscopy", "description": "Previous studies have mostly focused on using visible-to-near-infrared spectral technique to quantitatively estimate soil cadmium (Cd) content, whereas little attention has been paid to identifying soil Cd contamination from a perspective of spectral classification. Here, we developed a framework to compare the potential of two spectral transformations (i.e., raw reflectance and continuum removal [CR]), three optimization strategies (i.e., full-spectrum, Boruta feature selection, and synthetic minority over-sampling technique [SMOTE]), and three classification algorithms (i.e., partial least squares discriminant analysis, random forest [RF], and support vector machine) for diagnosing soil Cd contamination. A total of 536 soil samples were collected from urban and suburban areas located in Wuhan City, China. Specifically, Boruta and SMOTE strategies were aimed at selecting the most informative predictors and obtaining balanced training datasets, respectively. Results indicated that soils contaminated by Cd induced decrease in spectral reflectance magnitude. Classification models developed after Boruta and SMOTE strategies out-performed to those from full-spectrum. A diagnose model combining CR preprocessing, SMOTE strategy, and RF algorithm achieved the highest validation accuracy for soil Cd (Kappa = 0.74). This study provides a theoretical reference for rapid identification of and monitoring of soil Cd contamination in urban and suburban areas.", "keywords": ["DIFFUSE-REFLECTANCE SPECTROSCOPY", "HUMAN HEALTH", "PREDICTION", "POTENTIALLY TOXIC ELEMENTS", "Boruta algorithm", "01 natural sciences", "Visible-to-near-infrared spectroscopy", "NIR SPECTROSCOPY", "Soil", "ORGANIC-CARBON", "Machine learning", "11. Sustainability", "Soil Pollutants", "Least-Squares Analysis", "0105 earth and related environmental sciences", "Spectroscopy", " Near-Infrared", "RANDOM FOREST", "Urban and suburban soil Cd contamination", "04 agricultural and veterinary sciences", "15. Life on land", "QUANTITATIVE-ANALYSIS", "6. Clean water", "RIVER DELTA", "13. Climate action", "Earth and Environmental Sciences", "Synthetic minority over-sampling technique", "0401 agriculture", " forestry", " and fisheries", "HEAVY-METAL CONCENTRATIONS", "Cadmium"]}, "links": [{"href": "https://doi.org/10.1016/j.envpol.2021.118128"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Pollution", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.envpol.2021.118128", "name": "item", "description": "10.1016/j.envpol.2021.118128", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.envpol.2021.118128"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-12-01T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2019.114009", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:17:00Z", "type": "Journal Article", "created": "2019-11-12", "title": "Predicting glyphosate sorption across New Zealand pastoral soils using basic soil properties or Vis\u2013NIR spectroscopy", "description": "<p>Glyphosate [N-(phosphonomethyl) glycine] is the active ingredient in Roundup, which is the most used herbicide around the world. It is a non-selective herbicide with carboxyl, amino, and phosphonate functional groups, and it has a strong affinity to the soil mineral fraction. Sorption plays a major role for the fate and transport of glyphosate in the environment. The sorption coefficient (K<sub>d</sub>) of glyphosate, and hence its mobility, varies greatly among different soil types. Determining K<sub>d</sub> is laborious and requires the use of wet chemistry. In this study, we aimed to estimate K<sub>d</sub> using basic soil properties, and visible near-infrared spectroscopy (vis\u2013NIRS). The latter method is fast, requires no chemicals, and several soil properties can be estimated from the same spectrum. The data set included 68 topsoil samples collected across the South Island of New Zealand, with clay and organic carbon (OC) contents ranging from 0.001 to 0.520 kg kg<sup>\u22121</sup> and 0.021 to 0.217 kg kg<sup>\u22121</sup>, respectively. The K<sub>d</sub> was determined with batch equilibration sorption experiments and ranged from 13 to 3810 L kg<sup>\u22121</sup>. The visible near-infrared spectra were obtained from 400 to 2500 nm. Multiple linear regression was used to correlate K<sub>d</sub> to oxalate extractable aluminium and phosphorous and pH, which resulted in an R<sup>2</sup> of 0.89 and an RMSE of 259.59 L kg<sup>\u22121</sup>. Further, interval partial least squares regression with ten-fold cross-validation was used to predict K<sub>d</sub> by vis\u2013NIRS, and an R<sup>2</sup> of 0.93 and an RMSECV of 207.58 L kg<sup>\u22121</sup> were obtained. Thus, these results show that both basic soil properties and vis\u2013NIRS can predict the variation in K<sub>d</sub> across these samples with high accuracy and hence, that glyphosate sorption to a soil can be determined with vis\u2013NIRS.</p>", "keywords": ["2. Zero hunger", "ADSORPTION", "NEAR-INFRARED SPECTROSCOPY", "04 agricultural and veterinary sciences", "DEGRADATION", "15. Life on land", "WATER REPELLENCY", "FIELD-SCALE", "REFLECTANCE SPECTROSCOPY", "MOBILITY", "FACILITATED TRANSPORT", "CONTAMINANTS", "0401 agriculture", " forestry", " and fisheries", "COEFFICIENT"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2019.114009"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2019.114009", "name": "item", "description": "10.1016/j.geoderma.2019.114009", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2019.114009"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-02-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2022.156582", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:17:25Z", "type": "Journal Article", "created": "2022-06-14", "title": "Potential of visible and near infrared spectroscopy coupled with machine learning for predicting soil metal concentrations at the regional scale", "description": "Chemical analytical methods for metal analysis in soils are laborious, time-consuming and costly. This paper aims to evaluate the potential of short-range (SR) and full-range (FR) visible and infrared spectroscopy (vis-NIR) combined with linear and nonlinear calibration methods to estimate concentrations of nickel (Ni), cobalt (Co), cadmium (Cd), lead (Pb) and copper (Cu) in soils. A total of 435 soil samples were collected over agricultural sites, forest (7 %), pasture (5 %) and fallow land across a region in the northern part of Belgium. Generally, better predictions were obtained when using partial least squares regression (PLSR) and nonlinear calibration method [i.e., random forest (RF)] for processing of the spectral data, than when using support vector machine (SVM). FR generally outperformed SR and provided the best prediction results for Ni (R<sup>2</sup><sub>p</sub> = 0.76), Co (R<sup>2</sup><sub>p</sub> = 0.77), Cd (R<sup>2</sup><sub>p</sub> = 0.64) and Pb (R<sup>2</sup><sub>p</sub> = 0.65), when using PLSR and RF. SVM produced the best prediction result only for Pb (R<sup>2</sup><sub>p</sub> = 0.57) using the SR spectra. The metals Ni, Co, Cd and Pb can be predicted successfully (good accuracy) from the FR vis-NIR spectra using PLSR for Co, and RF for Ni, Cd, Pb and Cu. Compared to the FR spectrophotometer, improvement in accuracy was obtained for Cd and Co, using the SR spectra when combined with PLSR and RF, respectively. It is concluded that the SR spectrometer can be used successfully for the prediction of Co with RF (R<sup>2</sup><sub>p</sub> = 0.70), while it best predicted Cd with PLSR with an R<sup>2</sup><sub>p</sub> value of 0.67, which is of value for regional survey.", "keywords": ["Spectroscopy", " Near-Infrared", "Support Vector Machine", "RANGE", "Machine", "Machine learning modelling", "learning modelling", "REFLECTANCE SPECTROSCOPY", "CONTAMINATION", "Soil", "Lead", "Soil contamination", "Nickel", "Metals", "Earth and Environmental Sciences", "Soil Pollutants", "Chemometrics", "Cadmium", "Near-infrared spectra"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2022.156582"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2022.156582", "name": "item", "description": "10.1016/j.scitotenv.2022.156582", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2022.156582"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-01T00:00:00Z"}}, {"id": "10.1080/05704928.2022.2128365", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:18:55Z", "type": "Journal Article", "created": "2022-10-03", "title": "Mathematical techniques to remove moisture effects from visible\u2013near-infrared\u2013shortwave-infrared soil spectra\u2014review", "description": "This is an Accepted Manuscript of an article published by Taylor & Francis in Applied Spectroscopy Reviews on 03 October 2022, available at: https://doi.org/10.1080/05704928.2022.2128365", "keywords": ["EJP Soil", "Proximal Sensing", "ProbeField", "Soil Moisture", "04 agricultural and veterinary sciences", "algorithms", "01 natural sciences", "diffuse reflectance spectroscopy", "field-moist conditions", "EJPSOIL", "0401 agriculture", " forestry", " and fisheries", "indices", "Soil moisture", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/05704928.2022.2128365"}, {"href": "https://doi.org/10.1080/05704928.2022.2128365"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20Spectroscopy%20Reviews", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1080/05704928.2022.2128365", "name": "item", "description": "10.1080/05704928.2022.2128365", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1080/05704928.2022.2128365"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-03T00:00:00Z"}}, {"id": "10.1111/gcb.14815", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:19:26Z", "type": "Journal Article", "created": "2019-08-30", "title": "How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal", "description": "Abstract<p>There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international \uffe2\uff80\uff984p1000\uffe2\uff80\uff99 initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long\uffe2\uff80\uff90term experiments and space\uffe2\uff80\uff90for\uffe2\uff80\uff90time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.</p>", "keywords": ["[SDE] Environmental Sciences", "550", "BULK-DENSITY", "QH301 Biology", "Climate", "[SDV]Life Sciences [q-bio]", "NEW-ZEALAND", "630", "Soil", "NE/M021327/1", "11. Sustainability", "SDG 13 - Climate Action", "AGRICULTURAL SOILS", "SDG 15 - Life on Land", "General Environmental Science", "agriculture", "2. Zero hunger", "Global and Planetary Change", "reporting", "Measurement", "Ecology", "IN-SITU", "Agricultura", "NE/P019455/1", "carbono org\u00e1nico del suelo", "Agriculture", "LAND-USE CHANGE", "04 agricultural and veterinary sciences", "[SDV] Life Sciences [q-bio]", "climate change", "Sustainability", "[SDE]Environmental Sciences", "Carbon Sequestration", "DIFFUSE-REFLECTANCE SPECTROSCOPY", "LONG-TERM EXPERIMENTS", "330", "Monitoring", "STOCK CHANGES", "MRV", "secuestro de carbon", "12. Responsible consumption", "QH301", "Greenhouse Gases", "ORGANIC-CARBON", "soil organic matter", "greenhouse gases", "Invited Research Reviews", "Environmental Chemistry", "774378", "SDG 2 - Zero Hunger", "European Commission", "resilience", "Climate Solutions", "Soil organic matter", "Soil organic carbon", "Natural Environment Research Council (NERC)", "Verification", "food security", "15. Life on land", "carbon sequestration", "Sustainable Agriculture", "Carbon", "EDDY-COVARIANCE", "soil organic carbon", "monitoring", "Reporting", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "measurement", "verification"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.14815"}, {"href": "https://scholarworks.uvm.edu/context/rsfac/article/1079/viewcontent/Lini2019b.pdf"}, {"href": "https://doi.org/10.1111/gcb.14815"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.14815", "name": "item", "description": "10.1111/gcb.14815", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.14815"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-06T00:00:00Z"}}, {"id": "10.2136/vzj2015.09.0131", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:21:12Z", "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", "QH301 Biology", "0208 environmental biotechnology", "SATURATED-UNSATURATED FLOW", "02 engineering and technology", "soil processes", "01 natural sciences", "Physical Geography and Environmental Geoscience", "Sciences de la Terre", "ARBUSCULAR MYCORRHIZAL FUNGI", "sciences du sol", "ANZSRC::3707 Hydrology", "SYNTHETIC-APERTURE RADAR", "ANZSRC::4106 Soil sciences", "SDG 13 - Climate Action", "2. Zero hunger", "GROUND-PENETRATING RADAR", "diffuse-reflectance spectroscopy", "ANZSRC::050399 Soil Sciences not elsewhere classified", "synthetic-aperture radar", "digital elevation model", "SDG 13 \u2013 Ma\u00dfnahmen zum Klimaschutz", "MULTIPLE ECOSYSTEM SERVICES", "knowledge integration", "Crop and Pasture Production", "101028 Mathematical modelling", "570", "DIFFUSE-REFLECTANCE SPECTROSCOPY", "Environmental Engineering", "international soil modeling consortium", "0207 environmental engineering", "Soil Science", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "arbuscular mycorrhizal fungi", "soil science", "ORGANIC-MATTER DYNAMICS", "QH301", "ANZSRC::0503 Soil Sciences", "Life Science", "SEDIMENT TRANSPORT MODELS", "data integration", "sediment transport models", "approche ecosyst\u00e9mique", "mod\u00e9lisation", "0105 earth and related environmental sciences", "ground-penetrating radar", "info:eu-repo/classification/ddc/550", "soil modeling", "ANZSRC::080110 Simulation and Modelling", "ROOT WATER-UPTAKE", "15. Life on land", "multiple ecosystem services", "root water-uptake", "13. Climate action", "Earth and Environmental Sciences", "Soil Sciences", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "Earth Sciences", "101028 Mathematische Modellierung", "saturated-unsaturated flow", "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.", "DIGITAL ELEVATION MODEL"]}, "links": [{"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/10.2136/vzj2015.09.0131"}, {"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": "10.2136/vzj2015.09.0131", "name": "item", "description": "10.2136/vzj2015.09.0131", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2136/vzj2015.09.0131"}, {"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": "2164/6134", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:26:43Z", "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": "1854/LU-8720112", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:26:14Z", "type": "Journal Article", "created": "2021-09-09", "title": "Diagnosis of cadmium contamination in urban and suburban soils using visible-to-near-infrared spectroscopy", "description": "Previous studies have mostly focused on using visible-to-near-infrared spectral technique to quantitatively estimate soil cadmium (Cd) content, whereas little attention has been paid to identifying soil Cd contamination from a perspective of spectral classification. Here, we developed a framework to compare the potential of two spectral transformations (i.e., raw reflectance and continuum removal [CR]), three optimization strategies (i.e., full-spectrum, Boruta feature selection, and synthetic minority over-sampling technique [SMOTE]), and three classification algorithms (i.e., partial least squares discriminant analysis, random forest [RF], and support vector machine) for diagnosing soil Cd contamination. A total of 536 soil samples were collected from urban and suburban areas located in Wuhan City, China. Specifically, Boruta and SMOTE strategies were aimed at selecting the most informative predictors and obtaining balanced training datasets, respectively. Results indicated that soils contaminated by Cd induced decrease in spectral reflectance magnitude. Classification models developed after Boruta and SMOTE strategies out-performed to those from full-spectrum. A diagnose model combining CR preprocessing, SMOTE strategy, and RF algorithm achieved the highest validation accuracy for soil Cd (Kappa = 0.74). This study provides a theoretical reference for rapid identification of and monitoring of soil Cd contamination in urban and suburban areas.", "keywords": ["DIFFUSE-REFLECTANCE SPECTROSCOPY", "HUMAN HEALTH", "PREDICTION", "POTENTIALLY TOXIC ELEMENTS", "Boruta algorithm", "01 natural sciences", "Visible-to-near-infrared spectroscopy", "NIR SPECTROSCOPY", "Soil", "ORGANIC-CARBON", "Machine learning", "11. Sustainability", "Soil Pollutants", "Least-Squares Analysis", "0105 earth and related environmental sciences", "Spectroscopy", " Near-Infrared", "RANDOM FOREST", "Urban and suburban soil Cd contamination", "04 agricultural and veterinary sciences", "15. Life on land", "QUANTITATIVE-ANALYSIS", "6. Clean water", "RIVER DELTA", "13. Climate action", "Earth and Environmental Sciences", "Synthetic minority over-sampling technique", "0401 agriculture", " forestry", " and fisheries", "HEAVY-METAL CONCENTRATIONS", "Cadmium"]}, "links": [{"href": "https://doi.org/1854/LU-8720112"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Pollution", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-8720112", "name": "item", "description": "1854/LU-8720112", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8720112"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-12-01T00:00:00Z"}}, {"id": "1854/LU-01GM39KW0F5ENNMCF40YD35GFY", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:26:13Z", "type": "Journal Article", "created": "2022-06-14", "title": "Potential of visible and near infrared spectroscopy coupled with machine learning for predicting soil metal concentrations at the regional scale", "description": "Chemical analytical methods for metal analysis in soils are laborious, time-consuming and costly. This paper aims to evaluate the potential of short-range (SR) and full-range (FR) visible and infrared spectroscopy (vis-NIR) combined with linear and nonlinear calibration methods to estimate concentrations of nickel (Ni), cobalt (Co), cadmium (Cd), lead (Pb) and copper (Cu) in soils. A total of 435 soil samples were collected over agricultural sites, forest (7 %), pasture (5 %) and fallow land across a region in the northern part of Belgium. Generally, better predictions were obtained when using partial least squares regression (PLSR) and nonlinear calibration method [i.e., random forest (RF)] for processing of the spectral data, than when using support vector machine (SVM). FR generally outperformed SR and provided the best prediction results for Ni (R<sup>2</sup><sub>p</sub> = 0.76), Co (R<sup>2</sup><sub>p</sub> = 0.77), Cd (R<sup>2</sup><sub>p</sub> = 0.64) and Pb (R<sup>2</sup><sub>p</sub> = 0.65), when using PLSR and RF. SVM produced the best prediction result only for Pb (R<sup>2</sup><sub>p</sub> = 0.57) using the SR spectra. The metals Ni, Co, Cd and Pb can be predicted successfully (good accuracy) from the FR vis-NIR spectra using PLSR for Co, and RF for Ni, Cd, Pb and Cu. Compared to the FR spectrophotometer, improvement in accuracy was obtained for Cd and Co, using the SR spectra when combined with PLSR and RF, respectively. It is concluded that the SR spectrometer can be used successfully for the prediction of Co with RF (R<sup>2</sup><sub>p</sub> = 0.70), while it best predicted Cd with PLSR with an R<sup>2</sup><sub>p</sub> value of 0.67, which is of value for regional survey.", "keywords": ["Spectroscopy", " Near-Infrared", "Support Vector Machine", "RANGE", "Machine", "Machine learning modelling", "learning modelling", "REFLECTANCE SPECTROSCOPY", "CONTAMINATION", "Soil", "Lead", "Soil contamination", "Nickel", "Metals", "Earth and Environmental Sciences", "Soil Pollutants", "Chemometrics", "Cadmium", "Near-infrared spectra"]}, "links": [{"href": "https://doi.org/1854/LU-01GM39KW0F5ENNMCF40YD35GFY"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-01GM39KW0F5ENNMCF40YD35GFY", "name": "item", "description": "1854/LU-01GM39KW0F5ENNMCF40YD35GFY", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-01GM39KW0F5ENNMCF40YD35GFY"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-01T00:00:00Z"}}, {"id": "20.500.11850/688246", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-23T16:26:30Z", "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": "20.500.14243/532031", "type": "Feature", "geometry": null, "properties": {"license": "Restricted", "updated": "2026-06-23T16:26:34Z", "type": "Journal Article", "created": "2022-10-03", "title": "Mathematical techniques to remove moisture effects from visible\u2013near-infrared\u2013shortwave-infrared soil spectra\u2014review", "description": "This is an Accepted Manuscript of an article published by Taylor & Francis in Applied Spectroscopy Reviews on 03 October 2022, available at: https://doi.org/10.1080/05704928.2022.2128365", "keywords": ["EJP Soil", "Proximal Sensing", "ProbeField", "Soil Moisture", "04 agricultural and veterinary sciences", "algorithms", "01 natural sciences", "diffuse reflectance spectroscopy", "field-moist conditions", "EJPSOIL", "0401 agriculture", " forestry", " and fisheries", "indices", "Soil moisture", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/05704928.2022.2128365"}, {"href": "https://doi.org/20.500.14243/532031"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20Spectroscopy%20Reviews", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.14243/532031", "name": "item", "description": "20.500.14243/532031", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14243/532031"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-03T00:00:00Z"}}, {"id": "2164/13497", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:26:42Z", "type": "Journal Article", "created": "2019-08-30", "title": "How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal", "description": "Abstract<p>There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international \uffe2\uff80\uff984p1000\uffe2\uff80\uff99 initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long\uffe2\uff80\uff90term experiments and space\uffe2\uff80\uff90for\uffe2\uff80\uff90time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.</p", "keywords": ["[SDE] Environmental Sciences", "550", "BULK-DENSITY", "[SDV]Life Sciences [q-bio]", "QH301 Biology", "Climate", "NEW-ZEALAND", "630", "Soil", "NE/M021327/1", "11. Sustainability", "SDG 13 - Climate Action", "AGRICULTURAL SOILS", "SDG 15 - Life on Land", "General Environmental Science", "agriculture", "2. Zero hunger", "Global and Planetary Change", "reporting", "Measurement", "Ecology", "IN-SITU", "Agricultura", "NE/P019455/1", "carbono org\u00e1nico del suelo", "Agriculture", "LAND-USE CHANGE", "04 agricultural and veterinary sciences", "[SDV] Life Sciences [q-bio]", "climate change", "Sustainability", "[SDE]Environmental Sciences", "Carbon Sequestration", "DIFFUSE-REFLECTANCE SPECTROSCOPY", "LONG-TERM EXPERIMENTS", "330", "Monitoring", "STOCK CHANGES", "MRV", "secuestro de carbon", "12. Responsible consumption", "QH301", "Greenhouse Gases", "ORGANIC-CARBON", "soil organic matter", "greenhouse gases", "Invited Research Reviews", "Environmental Chemistry", "774378", "SDG 2 - Zero Hunger", "European Commission", "resilience", "Climate Solutions", "Soil organic matter", "Soil organic carbon", "Natural Environment Research Council (NERC)", "Verification", "food security", "15. Life on land", "carbon sequestration", "Sustainable Agriculture", "Carbon", "EDDY-COVARIANCE", "soil organic carbon", "monitoring", "Reporting", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "measurement", "verification"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.14815"}, {"href": "https://scholarworks.uvm.edu/context/rsfac/article/1079/viewcontent/Lini2019b.pdf"}, {"href": "https://doi.org/2164/13497"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2164/13497", "name": "item", "description": "2164/13497", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2164/13497"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-06T00:00:00Z"}}, {"id": "2987388425", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:27:03Z", "type": "Journal Article", "created": "2019-11-12", "title": "Predicting glyphosate sorption across New Zealand pastoral soils using basic soil properties or Vis\u2013NIR spectroscopy", "description": "<p>Glyphosate [N-(phosphonomethyl) glycine] is the active ingredient in Roundup, which is the most used herbicide around the world. It is a non-selective herbicide with carboxyl, amino, and phosphonate functional groups, and it has a strong affinity to the soil mineral fraction. Sorption plays a major role for the fate and transport of glyphosate in the environment. The sorption coefficient (K<sub>d</sub>) of glyphosate, and hence its mobility, varies greatly among different soil types. Determining K<sub>d</sub> is laborious and requires the use of wet chemistry. In this study, we aimed to estimate K<sub>d</sub> using basic soil properties, and visible near-infrared spectroscopy (vis\u2013NIRS). The latter method is fast, requires no chemicals, and several soil properties can be estimated from the same spectrum. The data set included 68 topsoil samples collected across the South Island of New Zealand, with clay and organic carbon (OC) contents ranging from 0.001 to 0.520 kg kg<sup>\u22121</sup> and 0.021 to 0.217 kg kg<sup>\u22121</sup>, respectively. The K<sub>d</sub> was determined with batch equilibration sorption experiments and ranged from 13 to 3810 L kg<sup>\u22121</sup>. The visible near-infrared spectra were obtained from 400 to 2500 nm. Multiple linear regression was used to correlate K<sub>d</sub> to oxalate extractable aluminium and phosphorous and pH, which resulted in an R<sup>2</sup> of 0.89 and an RMSE of 259.59 L kg<sup>\u22121</sup>. Further, interval partial least squares regression with ten-fold cross-validation was used to predict K<sub>d</sub> by vis\u2013NIRS, and an R<sup>2</sup> of 0.93 and an RMSECV of 207.58 L kg<sup>\u22121</sup> were obtained. Thus, these results show that both basic soil properties and vis\u2013NIRS can predict the variation in K<sub>d</sub> across these samples with high accuracy and hence, that glyphosate sorption to a soil can be determined with vis\u2013NIRS.</p>", "keywords": ["2. Zero hunger", "ADSORPTION", "NEAR-INFRARED SPECTROSCOPY", "04 agricultural and veterinary sciences", "DEGRADATION", "15. Life on land", "WATER REPELLENCY", "FIELD-SCALE", "REFLECTANCE SPECTROSCOPY", "MOBILITY", "FACILITATED TRANSPORT", "CONTAMINANTS", "0401 agriculture", " forestry", " and fisheries", "COEFFICIENT"]}, "links": [{"href": "https://doi.org/2987388425"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2987388425", "name": "item", "description": "2987388425", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2987388425"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-02-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=REFLECTANCE+SPECTROSCOPY&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=REFLECTANCE+SPECTROSCOPY&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=REFLECTANCE+SPECTROSCOPY&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=REFLECTANCE+SPECTROSCOPY&offset=13", "hreflang": "en-US"}], "numberMatched": 13, "numberReturned": 13, "distributedFeatures": [], "timeStamp": "2026-06-23T23:40:11.590509Z"}