{"type": "FeatureCollection", "features": [{"id": "10.1016/j.scitotenv.2021.152524", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:17:29Z", "type": "Journal Article", "created": "2021-12-23", "title": "Use of remote sensing to evaluate the effects of environmental factors on soil salinity in a semi-arid area", "description": "The global water crisis, driven by water scarcity and water quality deterioration, is expected to continue and intensify in dry and overpopulated areas, and will play a critical role in meeting future agricultural demands. Sustainability of agriculture irrigated with low quality water will require a comprehensive approach to soil, water, and crop management consisting of site- and situation-specific preventive measures and management strategies. Other problem related with water quality deterioration is soil salinization. Around 1Bha globally are salinized and soil salinization may be accelerating for several reasons including the changing climate. The consequences of climate change on soil salinization need to be monitored and mapped and, in this sense, remote sensing has been successfully applied to soil salinity monitoring. Although many issues remain to be resolved, some as important as the imbalance between ground-based measurements and satellite data. The main objective of this paper was to determine the influence of environmental factors on salinity from natural causes, and its effect on irrigated agriculture with degraded water. The study was developed on Campo de Cartagena, an intensive water-efficient irrigated area which main fruit tree is citrus (30%), a sensible crop to salinity. Nine representative citrus farms were selected, soil samples were analysed and different remote sensing indices and sets of environmental data were applied. Despite the heterogeneity between variables found by the descriptive analysis of the data, the relationship between farms, soil salinity and environmental data showed that applied salinity spectral indices were valid to detect soil salinity in citrus trees. Also, a set of environmental characterization provided useful information to determine the variables that most influence primary salinity in crops. Although the data extracted from spatial analysis indicated that to apply soil salinity predictive models, other variables related to agricultural management practices must be incorporated.", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "Agricultural", "Salinity", "550", "Degraded water", "Secondary soil salinization", "Crops", "Agriculture", "04 agricultural and veterinary sciences", "Remote sensing", "15. Life on land", "01 natural sciences", "630", "6. Clean water", "12. Responsible consumption", "Soil", "13. Climate action", "Remote Sensing Technology", "11. Sustainability", "Irrigated agriculture", "0401 agriculture", " forestry", " and fisheries", "Environmental Monitoring", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2021.152524"}, {"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.2021.152524", "name": "item", "description": "10.1016/j.scitotenv.2021.152524", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2021.152524"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}, {"id": "10.3390/su14052732", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-24T16:21:48Z", "type": "Journal Article", "created": "2022-02-28", "title": "Progress in Developing Scale-Able Approaches to Field-Scale Water Accounting Based on Remote Sensing", "description": "<p>To increase water productivity and assess water footprints in irrigated systems, there is a need to develop cheap and readily available estimates of components of water balance at fine spatial scales. Recent developments in satellite remote sensing platforms and modelling capacities have opened opportunities to address this need, such as those being developed in the WaterSENSE project. This paper showed how evapotranspiration, soil moisture, and farm-dam water volumes can be quantified based on the Copernicus data from the Sentinel satellite constellation. This highlights distinct differences between energy balance and crop factor approaches and estimates that can be derived from the point scale to the landscape scale. Differences in the results are related to assumptions in deriving evapotranspiration from remote sensing data. Advances in different parts of the water cycle and opportunities for crop detection and yield forecasting mean that crop water productivity can be quantified at field to landscape scales, but uncertainties are highly dependent on input data availability and reference validation data.</p>", "keywords": ["13. Climate action", "water use efficiency; Copernicus satellite data; irrigated agriculture", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2071-1050/14/5/2732/pdf"}, {"href": "https://www.mdpi.com/2071-1050/14/5/2732/pdf"}, {"href": "https://doi.org/10.3390/su14052732"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sustainability", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/su14052732", "name": "item", "description": "10.3390/su14052732", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/su14052732"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-25T00:00:00Z"}}, {"id": "11586/391721", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:57Z", "type": "Journal Article", "created": "2021-12-23", "title": "Use of remote sensing to evaluate the effects of environmental factors on soil salinity in a semi-arid area", "description": "The global water crisis, driven by water scarcity and water quality deterioration, is expected to continue and intensify in dry and overpopulated areas, and will play a critical role in meeting future agricultural demands. Sustainability of agriculture irrigated with low quality water will require a comprehensive approach to soil, water, and crop management consisting of site- and situation-specific preventive measures and management strategies. Other problem related with water quality deterioration is soil salinization. Around 1Bha globally are salinized and soil salinization may be accelerating for several reasons including the changing climate. The consequences of climate change on soil salinization need to be monitored and mapped and, in this sense, remote sensing has been successfully applied to soil salinity monitoring. Although many issues remain to be resolved, some as important as the imbalance between ground-based measurements and satellite data. The main objective of this paper was to determine the influence of environmental factors on salinity from natural causes, and its effect on irrigated agriculture with degraded water. The study was developed on Campo de Cartagena, an intensive water-efficient irrigated area which main fruit tree is citrus (30%), a sensible crop to salinity. Nine representative citrus farms were selected, soil samples were analysed and different remote sensing indices and sets of environmental data were applied. Despite the heterogeneity between variables found by the descriptive analysis of the data, the relationship between farms, soil salinity and environmental data showed that applied salinity spectral indices were valid to detect soil salinity in citrus trees. Also, a set of environmental characterization provided useful information to determine the variables that most influence primary salinity in crops. Although the data extracted from spatial analysis indicated that to apply soil salinity predictive models, other variables related to agricultural management practices must be incorporated.", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "Agricultural", "Salinity", "550", "Degraded water", "Secondary soil salinization", "Crops", "Agriculture", "04 agricultural and veterinary sciences", "Remote sensing", "15. Life on land", "01 natural sciences", "630", "6. Clean water", "12. Responsible consumption", "Soil", "13. Climate action", "Remote Sensing Technology", "11. Sustainability", "Irrigated agriculture", "0401 agriculture", " forestry", " and fisheries", "Environmental Monitoring", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/11586/391721"}, {"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": "11586/391721", "name": "item", "description": "11586/391721", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11586/391721"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Irrigated+agriculture&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=Irrigated+agriculture&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=Irrigated+agriculture&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Irrigated+agriculture&offset=3", "hreflang": "en-US"}], "numberMatched": 3, "numberReturned": 3, "distributedFeatures": [], "timeStamp": "2026-06-25T03:30:02.800874Z"}