{"type": "FeatureCollection", "features": [{"id": "10.1002/ecy.2199", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:14:08Z", "type": "Journal Article", "created": "2018-02-27", "title": "Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe", "description": "Abstract<p>The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation\uffc2\uffa0modelling was clearly higher for the spatial variability of N\uffe2\uff80\uff90 than for C\uffe2\uff80\uff90 and P\uffe2\uff80\uff90related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.</p", "keywords": ["Abiotic component", "Atmospheric sciences", "Physical geography", "Arid", "Climate Change", "Soil Science", "Spatial variability", "Environmental science", "Agricultural and Biological Sciences", "Soil", "Biodiversity Conservation and Ecosystem Management", "Soil texture", "Aridity index", "XXXXXX - Unknown", "Soil water", "FOS: Mathematics", "Pathology", "Climate change", "Biology", "Ecosystem", "Nature and Landscape Conservation", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Soil Fertility", "Ecology", "Geography", "Global Forest Drought Response and Climate Change", "Statistics", "Temperature", "Life Sciences", "Cycling", "Geology", "FOS: Earth and related environmental sciences", "04 agricultural and veterinary sciences", "Plants", "15. Life on land", "Archaeology", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Ecosystem Functioning", "Vegetation (pathology)", "Mathematics", "carbon cycling; climate change; multifunctionality; nitrogen cycling; phosphorous cycling; spatial heterogeneity"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/128150/8/Dur-n_et_al-2018-Ecology.pdf"}, {"href": "https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.2199"}, {"href": "https://doi.org/10.1002/ecy.2199"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ecy.2199", "name": "item", "description": "10.1002/ecy.2199", "href": 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\u0645\u062d\u062f\u0648\u062f \u0639\u0644\u0649 \u0627\u0644\u0646\u062a\u0627\u0626\u062c \u0645\u0642\u0627\u0631\u0646\u0629 \u0628\u0627\u0644\u0643\u062b\u0627\u0641\u0629 \u0627\u0644\u0633\u0627\u0626\u0628\u0629 \u0648\u0632\u0627\u0648\u064a\u0629 \u0627\u0644\u0627\u062d\u062a\u0643\u0627\u0643 \u0627\u0644\u062f\u0627\u062e\u0644\u064a. \u0644\u0645 \u064a\u0643\u0646 \u0644\u0644\u0631\u0633\u0648\u0645 \u0627\u0644\u0625\u0636\u0627\u0641\u064a\u0629 \u0644\u0644\u0643\u062a\u0644\u0629 \u0627\u0644\u062d\u064a\u0648\u064a\u0629 \u0623\u064a \u062a\u0623\u062b\u064a\u0631 \u0643\u0628\u064a\u0631 \u0639\u0644\u0649 \u0639\u0645\u0644\u064a\u0627\u062a \u0627\u0644\u0645\u062d\u0627\u0643\u0627\u0629. \u0641\u064a \u0627\u0644\u062e\u062a\u0627\u0645\u060c \u0627\u0633\u062a\u062c\u0627\u0628\u062a LAPSUS_LS \u0628\u0634\u0643\u0644 \u062c\u064a\u062f \u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0645\u062f\u062e\u0644\u0627\u062a \u0627\u0644\u062a\u0631\u0628\u0629 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"http://aims.fao.org/aos/agrovoc/c_12676", "http://aims.fao.org/aos/agrovoc/c_37897", "Landslide Hazards and Risk Assessment", "pratique culturale", "Biology", "0105 earth and related environmental sciences", "P36 - \u00c9rosion", " conservation et r\u00e9cup\u00e9ration des sols", "Soil science", "montagne", "Mechanical Engineering", "Slope stability", "Modeling", "Botany", "FOS: Earth and related environmental sciences", "15. Life on land", "Roots", "Bulk density", "Agronomy", "Geotechnical engineering", "13. Climate action", "Environmental Science", "Cohesion", "Mathematics"]}, "links": [{"href": "https://doi.org/10.1016/j.ecoleng.2017.08.010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecological%20Engineering", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.ecoleng.2017.08.010", "name": "item", "description": "10.1016/j.ecoleng.2017.08.010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.ecoleng.2017.08.010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-12-01T00:00:00Z"}}, {"id": "10.1016/j.landusepol.2022.106065", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:16:56Z", "type": "Journal Article", "created": "2022-02-28", "title": "Expansion of olive orchards and their impact on the cultivation and landscape through a case study in the countryside of Cordoba (Spain)", "description": "Open Access\u062a\u0645 \u062a\u0639\u0632\u064a\u0632 \u0627\u0633\u062a\u062f\u0627\u0645\u0629 \u0627\u0644\u0646\u0638\u0645 \u0627\u0644\u0632\u0631\u0627\u0639\u064a\u0629 \u0645\u0646 \u062e\u0644\u0627\u0644 \u0627\u0644\u062a\u0634\u0631\u064a\u0639\u0627\u062a \u0639\u0644\u0649 \u0645\u0633\u062a\u0648\u064a\u0627\u062a \u0645\u062e\u062a\u0644\u0641\u0629\u060c \u0648\u0644\u0643\u0646 \u0641\u064a \u0627\u0644\u0648\u0642\u062a \u0646\u0641\u0633\u0647 \u062a\u0639\u0632\u0632 \u0647\u0630\u0647 \u0627\u0644\u0633\u064a\u0627\u0633\u0627\u062a \u0623\u064a\u0636\u064b\u0627 \u0623\u0646\u0638\u0645\u0629 \u0623\u0643\u062b\u0631 \u0625\u0646\u062a\u0627\u062c\u064a\u0629 \u0645\u0646 \u062e\u0644\u0627\u0644 \u062a\u0643\u062b\u064a\u0641 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\u0645\u062d\u062a\u0645\u0644\u0629 \u0644\u062a\u0639\u0632\u064a\u0632 \u062a\u0648\u0641\u064a\u0631 \u062e\u062f\u0645\u0627\u062a \u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0625\u064a\u0643\u0648\u0644\u0648\u062c\u064a.", "keywords": ["Period (music)", "Soil Degradation", "Vascular Flora of Mediterranean Europe and North Africa", "Soil Science", "Orchard", "Plant Science", "Mediterranean", "Horticulture", "Genetic and Environmental Factors in Grapevine Cultivation", "01 natural sciences", "Environmental science", "Agricultural and Biological Sciences", "Pathology", "Ecosystem services", "Landscape elements", "Agroforestry", "Irrigation", "Biology", "0105 earth and related environmental sciences", "2. Zero hunger", "Geography", "Ecology", "Physics", "Common agricultural policy", "Olive groves", "Life Sciences", "Agriculture", "Forestry", "Acoustics", "04 agricultural and veterinary sciences", "15. Life on land", "Soil Erosion and Agricultural Sustainability", "Olive trees", "Agronomy", "Sustainability", "Archaeology", "FOS: Biological sciences", "Shifting cultivation", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Vegetation (pathology)"]}, "links": [{"href": "https://doi.org/10.1016/j.landusepol.2022.106065"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Use%20Policy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.landusepol.2022.106065", "name": "item", "description": "10.1016/j.landusepol.2022.106065", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.landusepol.2022.106065"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2021.152880", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:17:09Z", "type": "Journal Article", "created": "2022-01-06", "title": "Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China", "description": "Open AccessLe d\u00e9veloppement d'un syst\u00e8me pr\u00e9cis de pr\u00e9diction du rendement des cultures \u00e0 grande \u00e9chelle est d'une importance primordiale pour la gestion des ressources agricoles et la s\u00e9curit\u00e9 alimentaire mondiale. L'observation de la Terre fournit une source unique d'informations pour surveiller les cultures \u00e0 partir d'une diversit\u00e9 de gammes spectrales. Cependant, l'utilisation int\u00e9gr\u00e9e de ces donn\u00e9es et de leurs valeurs dans la pr\u00e9diction du rendement des cultures est encore peu \u00e9tudi\u00e9e. Ici, nous avons propos\u00e9 la combinaison de donn\u00e9es environnementales (climat, sol, g\u00e9ographie et topographie) avec de multiples donn\u00e9es satellitaires (indices de v\u00e9g\u00e9tation optiques, fluorescence induite par le soleil (SIF), temp\u00e9rature de surface du sol (LST) et profondeur optique de la v\u00e9g\u00e9tation micro-ondes (VOD)) dans le cadre pour estimer le rendement des cultures de ma\u00efs, de riz et de soja dans le nord-est de la Chine, et leur valeur unique et leur influence relative sur la pr\u00e9diction du rendement ont \u00e9t\u00e9 \u00e9valu\u00e9es. Deux m\u00e9thodes de r\u00e9gression lin\u00e9aire, trois m\u00e9thodes d'apprentissage automatique (ML) et un mod\u00e8le d'ensemble ML ont \u00e9t\u00e9 adopt\u00e9s pour construire des mod\u00e8les de pr\u00e9diction de rendement. Les r\u00e9sultats ont montr\u00e9 que les m\u00e9thodes individuelles de ML surpassaient les m\u00e9thodes de r\u00e9gression lin\u00e9aire, le mod\u00e8le d'ensemble de ML a encore am\u00e9lior\u00e9 les mod\u00e8les de ML uniques. De plus, les mod\u00e8les avec plus d'intrants ont obtenu de meilleures performances, la combinaison de donn\u00e9es satellitaires avec des donn\u00e9es environnementales, qui expliquaient respectivement 72\u00a0%, 69\u00a0% et 57\u00a0% de la variabilit\u00e9 du rendement du ma\u00efs, du riz et du soja, a d\u00e9montr\u00e9 des performances de pr\u00e9diction du rendement sup\u00e9rieures \u00e0 celles des intrants individuels. Alors que les donn\u00e9es satellitaires ont contribu\u00e9 \u00e0 la pr\u00e9diction du rendement des cultures principalement au d\u00e9but de la pointe de la saison de croissance, les donn\u00e9es climatiques ont fourni des informations suppl\u00e9mentaires principalement \u00e0 la pointe de la fin de la saison. Nous avons \u00e9galement constat\u00e9 que l'utilisation combin\u00e9e de l'IVE, du LST et du SIF a am\u00e9lior\u00e9 la pr\u00e9cision du mod\u00e8le par rapport au mod\u00e8le d'IVE de r\u00e9f\u00e9rence. Cependant, les indices de v\u00e9g\u00e9tation bas\u00e9s sur l'optique partageaient des informations similaires et ne fournissaient pas beaucoup d'informations suppl\u00e9mentaires au-del\u00e0 de l'IVE. Les pr\u00e9visions de rendement en cours de saison ont montr\u00e9 que les rendements des cultures peuvent \u00eatre pr\u00e9vus de mani\u00e8re satisfaisante deux \u00e0 trois mois avant la r\u00e9colte. La g\u00e9ographie, la topographie, la VOD, l'IVE, les param\u00e8tres hydrauliques du sol et les param\u00e8tres nutritifs sont plus importants pour la pr\u00e9diction du rendement des cultures.", "keywords": ["Atmospheric sciences", "Climate", "Multi-source satellite data", "Normalized Difference Vegetation Index", "Engineering", "Pathology", "Climate change", "Urban Heat Islands and Mitigation Strategies", "Linear regression", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Ecology", "Geography", "Statistics", "Agriculture", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Aerospace engineering", "Archaeology", "Physical Sciences", "Metallurgy", "Medicine", "Seasons", "Global Vegetation Models", "Biomass Estimation", "Regression analysis", "Vegetation (pathology)", "Crops", " Agricultural", "Environmental Engineering", "Environmental data", "Yield (engineering)", "Zea mays", "Environmental science", "Machine learning", "FOS: Mathematics", "Crop yield", "Biology", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "Predictive modelling", "Food security", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "Materials science", "Yield prediction", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Mathematics"], "contacts": [{"organization": "Zhenwang Li, Lei Ding, Donghui Xu,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2021.152880"}, {"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.2021.152880", "name": "item", "description": "10.1016/j.scitotenv.2021.152880", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2021.152880"}, {"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": "10.1186/s13570-014-0018-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:20:05Z", "type": "Journal Article", "created": "2014-11-24", "title": "Control Of Bush Encroachment In Borana Zone Of Southern Ethiopia: Effects Of Different Control Techniques On Rangeland Vegetation And Tick Populations", "description": "Open AccessA study on effects of bush encroachment control techniques on rangeland productivity and tick population dynamics was conducted in Arero district of Borana zone, southern Ethiopia, for three consecutive years. The study targeted two main and dominant encroaching bush species in Borana rangeland, Acacia drepanolobium and Acacia mellifera, and their effects on some vegetation attributes and tick population dynamics. A hectare of rangeland encroached by these two acacia species was replicated/divided into three plots, and each plot was subdivided into five sub-plots to receive five treatments: cutting at 0.5 m above ground and pouring kerosene on stumps (T1), cutting at 0.5 m above ground and debarking the stumps down into the soil surface (T2), cutting at 0.5 m above ground alone (T3), cutting at 0.5 m above ground and dissecting the stumps (T4) and control (T5). Data on basal and litter covers, soil erosion and compaction, dead and re-sprouted encroaching tree/shrub species and nymph- and adult-stage tick populations were collected before and after treatment applications. The applied treatments significantly influenced (p < 0.05) basal cover, nymph- and adult-stage tick population and the two encroaching tree species. The results of this study showed that T3 and T2 were good in controlling A. drepanolobium in that order. T4 and T2 had a significant effect in controlling A. mellifera in their order. Controlling bush encroachment had also a positive effect in eradicating the tick population. The most dominant grass and non-grass species observed after the control actions were Cenchrus ciliaris, Chrysopogon aucheri, Abutilon hirtum, Pennisetum mezianum, Dyschoriste hildebrandtii, Zaleya pentandra and Eragrostis papposa. Therefore, controlling encroaching tree/shrub species had created a conducive grazing area with palatable herbaceous species for the livestock and unequivocally reduced tick population which play a role in reducing cattle milk production through closing off teats. The management of bush encroachment, if sustained, will contribute in stabilizing rangelands and help minimize the negative effects of feed and food crises in the future.", "keywords": ["0106 biological sciences", "Population", "Lantana", "Management", " Monitoring", " Policy and Law", "01 natural sciences", "Basal area", "Agricultural and Biological Sciences", "Rangeland Degradation", "Sociology", "Agroforestry Systems and Biodiversity Enhancement", "Rangeland Degradation and Pastoral Livelihoods", "Pathology", "Agroforestry", "Biology", "Demography", "0105 earth and related environmental sciences", "2. Zero hunger", "Ecology", "Life Sciences", "Forestry", "Factors Affecting Sagebrush Ecosystems and Wildlife Conservation", "15. Life on land", "Agronomy", "6. Clean water", "FOS: Sociology", "Shrub", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Medicine", "Rangeland", "Vegetation (pathology)", "Tick"], "contacts": [{"organization": "Bikila Negasa, Bedasa Eba, Samuel Tuffa, Barecha Bayissa, Jaldesa Doyo, N. Van Husen,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1186/s13570-014-0018-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Pastoralism", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1186/s13570-014-0018-1", "name": "item", "description": "10.1186/s13570-014-0018-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1186/s13570-014-0018-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-11-25T00:00:00Z"}}, {"id": "10.1371/journal.pone.0153415", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:20:17Z", "type": "Journal Article", "created": "2016-04-12", "title": "Seasonality, Rather Than Nutrient Addition Or Vegetation Types, Influenced Short-Term Temperature Sensitivity Of Soil Organic Carbon Decomposition", "description": "Open AccessLa r\u00e9ponse de la respiration microbienne de la d\u00e9composition du carbone organique du sol (COS) aux changements environnementaux joue un r\u00f4le cl\u00e9 dans la pr\u00e9diction des tendances futures de la concentration de CO2 atmosph\u00e9rique. Cependant, il n'est pas certain qu'il existe une tendance universelle dans la r\u00e9ponse de la respiration microbienne \u00e0 l'augmentation de la temp\u00e9rature et \u00e0 l'ajout de nutriments parmi les diff\u00e9rents types de v\u00e9g\u00e9tation. Dans cette \u00e9tude, les sols ont \u00e9t\u00e9 \u00e9chantillonn\u00e9s au printemps, en \u00e9t\u00e9, en automne et en hiver \u00e0 partir de cinq types de v\u00e9g\u00e9tation dominants, y compris les for\u00eats de pins, de m\u00e9l\u00e8zes et de bouleaux, les arbustes et les prairies, dans la r\u00e9gion de Saihanba, dans le nord de la Chine. Les \u00e9chantillons de sol de chaque saison ont \u00e9t\u00e9 incub\u00e9s \u00e0 1, 10 et 20 \u00b0C pendant 5 \u00e0 7 jours. L'azote (N\u00a0; 0,035 mM sous forme de NH4NO3) et le phosphore (P\u00a0; 0,03 mM sous forme de P2O5) ont \u00e9t\u00e9 ajout\u00e9s aux \u00e9chantillons de sol, et les r\u00e9ponses de la respiration microbienne du sol \u00e0 l'augmentation de la temp\u00e9rature et \u00e0 l'ajout de nutriments ont \u00e9t\u00e9 d\u00e9termin\u00e9es. Nous avons constat\u00e9 une tendance universelle selon laquelle la respiration microbienne du sol augmentait avec l'augmentation de la temp\u00e9rature, ind\u00e9pendamment de la saison d'\u00e9chantillonnage ou du type de v\u00e9g\u00e9tation. La sensibilit\u00e9 \u00e0 la temp\u00e9rature (indiqu\u00e9e par Q10, l'augmentation du taux de respiration avec une augmentation de 10\u00b0C de la temp\u00e9rature) de la respiration microbienne \u00e9tait plus \u00e9lev\u00e9e au printemps et en automne qu'en \u00e9t\u00e9 et en hiver, quel que soit le type de v\u00e9g\u00e9tation. Le Q10 \u00e9tait significativement corr\u00e9l\u00e9 positivement avec la biomasse microbienne et le rapport champignon\u00a0: bact\u00e9rie. La respiration microbienne (ou Q10) n'a pas r\u00e9pondu de mani\u00e8re significative \u00e0 l'addition d'azote ou de phosphore. Nos r\u00e9sultats sugg\u00e8rent que l'apport en nutriments \u00e0 court terme pourrait ne pas modifier le taux de d\u00e9composition du COS ou sa sensibilit\u00e9 \u00e0 la temp\u00e9rature, alors que l'augmentation de la temp\u00e9rature pourrait am\u00e9liorer consid\u00e9rablement la d\u00e9composition du COS au printemps et en automne, par rapport \u00e0 l'hiver et \u00e0 l'\u00e9t\u00e9.", "keywords": ["Biomass (ecology)", "Atmospheric Science", "Microbial population biology", "Larix", "Carbon Dynamics in Peatland Ecosystems", "Forests", "Agricultural and Biological Sciences", "Soil", "Soil water", "Pathology", "Carbon Feedback", "Biomass", "Betula", "Soil Microbiology", "2. Zero hunger", "Ecology", "Q10", "Respiration", "Q", "R", "Temperature", "Life Sciences", "Soil respiration", "04 agricultural and veterinary sciences", "Soil carbon", "Grassland", "Earth and Planetary Sciences", "Physical Sciences", "Respiration rate", "Medicine", "Seasons", "Vegetation (pathology)", "Research Article", "China", "Nitrogen", "Science", "Soil Science", "Environmental science", "Shrubland", "Genetics", "Arctic Permafrost Dynamics and Climate Change", "Soil Carbon Sequestration", "Biology", "Ecosystem", "Soil science", "Soil organic matter", "Soil Fertility", "Bacteria", "Fungi", "Botany", "15. Life on land", "Pinus", "Vegetation Change", "Carbon", "Agronomy", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Nutrient"], "contacts": [{"organization": "Yu-Qi Qian, Fangliang He, Wei Wang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1371/journal.pone.0153415"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PLOS%20ONE", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1371/journal.pone.0153415", "name": "item", "description": "10.1371/journal.pone.0153415", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1371/journal.pone.0153415"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-04-12T00:00:00Z"}}, {"id": "10.3390/rs12244018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:22:04Z", "type": "Journal Article", "created": "2020-12-08", "title": "Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000\u20132017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.</p></article>", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "0207 environmental engineering", "Agricultural drought", "02 engineering and technology", "01 natural sciences", "630", "Environmental science", "remote sensing", "Land data assimilation systems", "Pathology", "assimilation systems", "Biology", "land data assimilation systems", "0105 earth and related environmental sciences", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Water content", "Ecology", "Drought", "Global Forest Drought Response and Climate Change", "Q", "Hydrology (agriculture)", "Geology", "cereal yield", "Remote Sensing in Vegetation Monitoring and Phenology", "FOS: Earth and related environmental sciences", "Remote sensing", "semiarid region", "15. Life on land", "agricultural drought", "Agronomy", "6. Clean water", "Cereal yield", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "[SDE]Environmental Sciences", "Global Drought Monitoring and Assessment", "Environmental Science", "Physical Sciences", "Leaf area index", "Medicine", "Semiarid region", "land data", "Vegetation (pathology)"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://doi.org/10.3390/rs12244018"}, {"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/rs12244018", "name": "item", "description": "10.3390/rs12244018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs12244018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-08T00:00:00Z"}}, {"id": "10.5194/essd-13-3707-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:22:53Z", "type": "Journal Article", "created": "2021-01-07", "title": "C-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)", "description": "<p>Abstract. A better understanding of the hydrological functioning of irrigated crops using remote sensing observations is of prime importance in the semi-arid areas where the water resources are limited. Radar observations, available at high resolution and revisit time since the launch of Sentinel-1 in 2014, have shown great potential for the monitoring of the water content of the upper soil and of the canopy. In this paper, a complete set of data for radar signal analysis is shared to the scientific community for the first time to our knowledge. The data set is composed of Sentinel-1 products and in situ measurements of soil and vegetation variables collected during three agricultural seasons over drip-irrigated winter wheat in the Haouz plain in Morocco. The in situ data gathers soil measurements (time series of half-hourly surface soil moisture, surface roughness and agricultural practices) and vegetation measurements collected every week/two weeks including above-ground fresh and dry biomasses, vegetation water content based on destructive measurements, cover fraction, leaf area index and plant height. Radar data are the backscattering coefficient and the interferometric coherence derived from Sentinel-1 GRDH (Ground Range Detected High resolution) and SLC (Single Look Complex) products, respectively. The normalized difference vegetation index derived from Sentinel-2 data based on Level-2A (surface reflectance and cloud mask) atmospheric effects-corrected products is also provided. This database, which is the first of its kind made available in open access, is described here comprehensively in order to help the scientific community to evaluate and to develop new or existing remote sensing algorithms for monitoring wheat canopy under semi-arid conditions. The data set is particularly relevant for the development of radar applications including surface soil moisture and vegetation parameters retrieval using either physically based or empirical approaches such as machine and deep learning algorithms. The database is archived in the DataSuds repository and is freely-accessible via the DOI:  https://doi.org/10.23708/8D6WQC  (Ouaadi et al., 2020a).                         </p>", "keywords": ["550", "Arid", "Soil Moisture", "0211 other engineering and technologies", "FOS: Mechanical engineering", "02 engineering and technology", "Digital Soil Mapping Techniques", "Normalized Difference Vegetation Index", "630", "Agricultural and Biological Sciences", "Engineering", "Pathology", "GE1-350", "2. Zero hunger", "QE1-996.5", "Vegetation Monitoring", "Water content", "Ecology", "Geography", "Statistics", "Life Sciences", "Hydrology (agriculture)", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Soil Erosion and Agricultural Sustainability", "6. Clean water", "Satellite Observations", "Archaeology", "Physical Sciences", "Leaf area index", "Telecommunications", "Medicine", "Vegetation (pathology)", "Environmental Engineering", "Data set", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Aerospace Engineering", "Soil Science", "Environmental science", "Digital Soil Mapping", "[SDU] Sciences of the Universe [physics]", "Global Soil Information", "FOS: Mathematics", "Biology", "Radar", "Synthetic Aperture Radar Interferometry", "Canopy", "FOS: Environmental engineering", "Soil Properties", "Paleontology", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Surface Deformation Monitoring", "Computer science", "Agronomy", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "Mathematics"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/3707/2021/essd-13-3707-2021.pdf"}, {"href": "https://doi.org/10.5194/essd-13-3707-2021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-13-3707-2021", "name": "item", "description": "10.5194/essd-13-3707-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-13-3707-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-07T00:00:00Z"}}, {"id": "10.5194/gmd-10-3745-2017", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:22:55Z", "type": "Journal Article", "created": "2017-10-12", "title": "A representation of the phosphorus cycle for ORCHIDEE (revision\u00a04520)", "description": "<p>Abstract. Land surface models rarely incorporate the terrestrial phosphorus cycle and its interactions with the carbon cycle, despite the extensive scientific debate about the importance of nitrogen and phosphorus supply for future land carbon uptake. We describe a representation of the terrestrial phosphorus cycle for the ORCHIDEE land surface model, and evaluate it with data from nutrient manipulation experiments along a\uffc2\uffa0soil formation chronosequence in Hawaii.  ORCHIDEE accounts for the influence of the nutritional state of vegetation on tissue nutrient concentrations, photosynthesis, plant growth, biomass allocation, biochemical (phosphatase-mediated) mineralization, and biological nitrogen fixation. Changes in the nutrient content (quality) of litter affect the carbon use efficiency of decomposition and in return the nutrient availability to vegetation. The model explicitly accounts for root zone depletion of phosphorus as a function of root phosphorus uptake and phosphorus transport from the soil to the root surface.  The model captures the observed differences in the foliage stoichiometry of vegetation between an early (300-year) and a late (4.1\uffe2\uff80\uffafMyr) stage of soil development. The contrasting sensitivities of net primary productivity to the addition of either nitrogen, phosphorus, or both among sites are in general reproduced by the model. As observed, the model simulates a preferential stimulation of leaf level productivity when nitrogen stress is alleviated, while leaf level productivity and leaf area index are stimulated equally when phosphorus stress is alleviated. The nutrient use efficiencies in the model are lower than observed primarily due to biases in the nutrient content and turnover of woody biomass.  We conclude that ORCHIDEE is able to reproduce the shift from nitrogen to phosphorus limited net primary productivity along the soil development chronosequence, as well as the contrasting responses of net primary productivity to nutrient addition.                     </p>", "keywords": ["Biomass (ecology)", "Chronosequence", "Organic chemistry", "chronos\u00e9quence", "Plant Science", "mod\u00e8le", "Nitrogen cycle", "01 natural sciences", "Nutrient cycle", "Agricultural and Biological Sciences", "Soil water", "Pathology", "2. Zero hunger", "QE1-996.5", "Global and Planetary Change", "Orchidee", "Ecology", "Physics", "Life Sciences", "Geology", "Phosphorus", "Carbon cycle", "Chemistry", "nutrition", "Physical Sciences", "Medicine", "[SDU.STU.GP] Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph]", "Ecosystem Functioning", "Vegetation (pathology)", "cycle du carbone", "570", "[SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph]", "Nitrogen", "hawai", "Soil Science", "mod\u00e8le orchid\u00e9e", "Environmental science", "vegetation", "phosphore du sol", "Biology", "Ecosystem", "0105 earth and related environmental sciences", "Soil science", "Soil Fertility", "ddc:550", "Global Forest Drought Response and Climate Change", "surface terrestre", "Plant Nutrient Uptake and Signaling Pathways", "15. Life on land", "Agronomy", "hawaii", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Nutrient"]}, "links": [{"href": "https://gmd.copernicus.org/articles/10/3745/2017/gmd-10-3745-2017.pdf"}, {"href": "https://doi.org/10.5194/gmd-10-3745-2017"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/gmd-10-3745-2017", "name": "item", "description": "10.5194/gmd-10-3745-2017", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-10-3745-2017"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-10-12T00:00:00Z"}}, {"id": "10.5194/hess-2019-105", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:22:56Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.                         </p></article>", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.5194/hess-2019-105"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-2019-105", "name": "item", "description": "10.5194/hess-2019-105", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-2019-105"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10.5194/hess-24-1781-2020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:22:57Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "<p>Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\uffe2\uff80\uff89km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\uffe2\uff80\uff89km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\uffe2\uff80\uff932018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\uffe2\uff80\uff932018). The field was seeded for the 2014\uffe2\uff80\uff932015 (S1), 2016\uffe2\uff80\uff932017 (S2) and 2017\uffe2\uff80\uff932018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\uffe2\uff80\uff932016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \uffce\uffb1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \uffce\uffb1PT remains at a mostly constant value (\uffe2\uff88\uffbc\uffe2\uff80\uff890.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\uffe2\uff80\uff89W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\uffe2\uff80\uff89W/m2 for S1, S2, S3 and B1 respectively.                         </p>", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.5194/hess-24-1781-2020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-24-1781-2020", "name": "item", "description": "10.5194/hess-24-1781-2020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-24-1781-2020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10261/271651", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:25:56Z", "type": "Journal Article", "created": "2022-02-28", "title": "Expansion of olive orchards and their impact on the cultivation and landscape through a case study in the countryside of Cordoba (Spain)", "description": "Open Access\u062a\u0645 \u062a\u0639\u0632\u064a\u0632 \u0627\u0633\u062a\u062f\u0627\u0645\u0629 \u0627\u0644\u0646\u0638\u0645 \u0627\u0644\u0632\u0631\u0627\u0639\u064a\u0629 \u0645\u0646 \u062e\u0644\u0627\u0644 \u0627\u0644\u062a\u0634\u0631\u064a\u0639\u0627\u062a \u0639\u0644\u0649 \u0645\u0633\u062a\u0648\u064a\u0627\u062a \u0645\u062e\u062a\u0644\u0641\u0629\u060c \u0648\u0644\u0643\u0646 \u0641\u064a \u0627\u0644\u0648\u0642\u062a \u0646\u0641\u0633\u0647 \u062a\u0639\u0632\u0632 \u0647\u0630\u0647 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\u0627\u0644\u0633\u064a\u0627\u0633\u0627\u062a \u0627\u0644\u0632\u0631\u0627\u0639\u064a\u0629 \u0645\u062a\u0639\u062f\u062f\u0629 \u0627\u0644\u0645\u0633\u062a\u0648\u064a\u0627\u062a \u0643\u0645\u0646\u0627\u0637\u0642 \u0627\u0633\u062a\u0639\u0627\u062f\u0629 \u0645\u062d\u062a\u0645\u0644\u0629 \u0644\u062a\u0639\u0632\u064a\u0632 \u062a\u0648\u0641\u064a\u0631 \u062e\u062f\u0645\u0627\u062a \u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0625\u064a\u0643\u0648\u0644\u0648\u062c\u064a.", "keywords": ["Period (music)", "Soil Degradation", "Vascular Flora of Mediterranean Europe and North Africa", "Soil Science", "Orchard", "Plant Science", "Mediterranean", "Horticulture", "Genetic and Environmental Factors in Grapevine Cultivation", "01 natural sciences", "Environmental science", "Agricultural and Biological Sciences", "Pathology", "Ecosystem services", "Landscape elements", "Agroforestry", "Irrigation", "Biology", "0105 earth and related environmental sciences", "2. Zero hunger", "Geography", "Ecology", "Physics", "Common agricultural policy", "Olive groves", "Life Sciences", "Agriculture", "Forestry", "Acoustics", "04 agricultural and veterinary sciences", "15. Life on land", "Soil Erosion and Agricultural Sustainability", "Olive trees", "Agronomy", "Sustainability", "Archaeology", "FOS: Biological sciences", "Shifting cultivation", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Vegetation (pathology)"]}, "links": [{"href": "https://doi.org/10261/271651"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Use%20Policy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/271651", "name": "item", "description": "10261/271651", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/271651"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "10.60692/7hann-x9205", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:25:31Z", "type": "Journal Article", "created": "2020-12-08", "title": "Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000\u20132017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.</p></article>", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "0207 environmental engineering", "Agricultural drought", "02 engineering and technology", "01 natural sciences", "630", "Environmental science", "remote sensing", "Land data assimilation systems", "Pathology", "assimilation systems", "Biology", "land data assimilation systems", "0105 earth and related environmental sciences", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Water content", "Ecology", "Drought", "Global Forest Drought Response and Climate Change", "Q", "Hydrology (agriculture)", "Geology", "cereal yield", "Remote Sensing in Vegetation Monitoring and Phenology", "FOS: Earth and related environmental sciences", "Remote sensing", "semiarid region", "15. Life on land", "agricultural drought", "Agronomy", "6. Clean water", "Cereal yield", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "[SDE]Environmental Sciences", "Global Drought Monitoring and Assessment", "Environmental Science", "Physical Sciences", "Leaf area index", "Medicine", "Semiarid region", "land data", "Vegetation (pathology)"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://doi.org/10.60692/7hann-x9205"}, {"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": "10.60692/7hann-x9205", "name": "item", "description": "10.60692/7hann-x9205", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/7hann-x9205"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-08T00:00:00Z"}}, {"id": "10.60692/00fqh-scr74", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:25:30Z", "type": "Journal Article", "created": "2022-02-28", "title": "Expansion of olive orchards and their impact on the cultivation and landscape through a case study in the countryside of Cordoba (Spain)", "description": "Open Access\u062a\u0645 \u062a\u0639\u0632\u064a\u0632 \u0627\u0633\u062a\u062f\u0627\u0645\u0629 \u0627\u0644\u0646\u0638\u0645 \u0627\u0644\u0632\u0631\u0627\u0639\u064a\u0629 \u0645\u0646 \u062e\u0644\u0627\u0644 \u0627\u0644\u062a\u0634\u0631\u064a\u0639\u0627\u062a \u0639\u0644\u0649 \u0645\u0633\u062a\u0648\u064a\u0627\u062a \u0645\u062e\u062a\u0644\u0641\u0629\u060c \u0648\u0644\u0643\u0646 \u0641\u064a \u0627\u0644\u0648\u0642\u062a \u0646\u0641\u0633\u0647 \u062a\u0639\u0632\u0632 \u0647\u0630\u0647 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\u0627\u0644\u0633\u064a\u0627\u0633\u0627\u062a \u0627\u0644\u0632\u0631\u0627\u0639\u064a\u0629 \u0645\u062a\u0639\u062f\u062f\u0629 \u0627\u0644\u0645\u0633\u062a\u0648\u064a\u0627\u062a \u0643\u0645\u0646\u0627\u0637\u0642 \u0627\u0633\u062a\u0639\u0627\u062f\u0629 \u0645\u062d\u062a\u0645\u0644\u0629 \u0644\u062a\u0639\u0632\u064a\u0632 \u062a\u0648\u0641\u064a\u0631 \u062e\u062f\u0645\u0627\u062a \u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0625\u064a\u0643\u0648\u0644\u0648\u062c\u064a.", "keywords": ["Period (music)", "Soil Degradation", "Vascular Flora of Mediterranean Europe and North Africa", "Soil Science", "Orchard", "Plant Science", "Mediterranean", "Horticulture", "Genetic and Environmental Factors in Grapevine Cultivation", "01 natural sciences", "Environmental science", "Agricultural and Biological Sciences", "Pathology", "Ecosystem services", "Landscape elements", "Agroforestry", "Irrigation", "Biology", "0105 earth and related environmental sciences", "2. Zero hunger", "Geography", "Ecology", "Physics", "Common agricultural policy", "Olive groves", "Life Sciences", "Agriculture", "Forestry", "Acoustics", "04 agricultural and veterinary sciences", "15. Life on land", "Soil Erosion and Agricultural Sustainability", "Olive trees", "Agronomy", "Sustainability", "Archaeology", "FOS: Biological sciences", "Shifting cultivation", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Vegetation (pathology)"]}, "links": [{"href": "https://doi.org/10.60692/00fqh-scr74"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Use%20Policy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/00fqh-scr74", "name": "item", "description": "10.60692/00fqh-scr74", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/00fqh-scr74"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "10.60692/g4rcv-eqz54", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:25:31Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.</p></article>", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.60692/g4rcv-eqz54"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/g4rcv-eqz54", "name": "item", "description": "10.60692/g4rcv-eqz54", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/g4rcv-eqz54"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "1959.7/uws:63733", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:26:38Z", "type": "Journal Article", "created": "2018-02-27", "title": "Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe", "description": "Abstract<p>The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation\uffc2\uffa0modelling was clearly higher for the spatial variability of N\uffe2\uff80\uff90 than for C\uffe2\uff80\uff90 and P\uffe2\uff80\uff90related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.</p", "keywords": ["Abiotic component", "Atmospheric sciences", "Physical geography", "Arid", "Climate Change", "Soil Science", "Spatial variability", "Environmental science", "Agricultural and Biological Sciences", "Soil", "Biodiversity Conservation and Ecosystem Management", "Soil texture", "Aridity index", "XXXXXX - Unknown", "Soil water", "FOS: Mathematics", "Pathology", "Climate change", "Biology", "Ecosystem", "Nature and Landscape Conservation", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Soil Fertility", "Ecology", "Geography", "Global Forest Drought Response and Climate Change", "Statistics", "Temperature", "Life Sciences", "Cycling", "Geology", "FOS: Earth and related environmental sciences", "04 agricultural and veterinary sciences", "Plants", "15. Life on land", "Archaeology", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Ecosystem Functioning", "Vegetation (pathology)", "Mathematics"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/128150/8/Dur-n_et_al-2018-Ecology.pdf"}, {"href": "https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.2199"}, {"href": "https://doi.org/1959.7/uws:63733"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1959.7/uws:63733", "name": "item", "description": "1959.7/uws:63733", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1959.7/uws:63733"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-01T00:00:00Z"}}, {"id": "2940609395", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:27:22Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.                         </p></article>", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/2940609395"}, {"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": "2940609395", "name": "item", "description": "2940609395", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2940609395"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "3113036323", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:27:39Z", "type": "Journal Article", "created": "2020-12-08", "title": "Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000\u20132017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.</p></article>", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "0207 environmental engineering", "Agricultural drought", "02 engineering and technology", "01 natural sciences", "630", "Environmental science", "remote sensing", "Land data assimilation systems", "Pathology", "assimilation systems", "Biology", "land data assimilation systems", "0105 earth and related environmental sciences", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Water content", "Ecology", "Drought", "Global Forest Drought Response and Climate Change", "Q", "Hydrology (agriculture)", "Geology", "cereal yield", "Remote Sensing in Vegetation Monitoring and Phenology", "FOS: Earth and related environmental sciences", "Remote sensing", "semiarid region", "15. Life on land", "agricultural drought", "Agronomy", "6. Clean water", "Cereal yield", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "[SDE]Environmental Sciences", "Global Drought Monitoring and Assessment", "Environmental Science", "Physical Sciences", "Leaf area index", "Medicine", "Semiarid region", "land data", "Vegetation (pathology)"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://doi.org/3113036323"}, {"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": "3113036323", "name": "item", "description": "3113036323", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3113036323"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-08T00:00:00Z"}}, {"id": "34998760", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-13T16:27:58Z", "type": "Journal Article", "created": "2022-01-06", "title": "Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China", "description": "Open AccessLe d\u00e9veloppement d'un syst\u00e8me pr\u00e9cis de pr\u00e9diction du rendement des cultures \u00e0 grande \u00e9chelle est d'une importance primordiale pour la gestion des ressources agricoles et la s\u00e9curit\u00e9 alimentaire mondiale. L'observation de la Terre fournit une source unique d'informations pour surveiller les cultures \u00e0 partir d'une diversit\u00e9 de gammes spectrales. Cependant, l'utilisation int\u00e9gr\u00e9e de ces donn\u00e9es et de leurs valeurs dans la pr\u00e9diction du rendement des cultures est encore peu \u00e9tudi\u00e9e. Ici, nous avons propos\u00e9 la combinaison de donn\u00e9es environnementales (climat, sol, g\u00e9ographie et topographie) avec de multiples donn\u00e9es satellitaires (indices de v\u00e9g\u00e9tation optiques, fluorescence induite par le soleil (SIF), temp\u00e9rature de surface du sol (LST) et profondeur optique de la v\u00e9g\u00e9tation micro-ondes (VOD)) dans le cadre pour estimer le rendement des cultures de ma\u00efs, de riz et de soja dans le nord-est de la Chine, et leur valeur unique et leur influence relative sur la pr\u00e9diction du rendement ont \u00e9t\u00e9 \u00e9valu\u00e9es. Deux m\u00e9thodes de r\u00e9gression lin\u00e9aire, trois m\u00e9thodes d'apprentissage automatique (ML) et un mod\u00e8le d'ensemble ML ont \u00e9t\u00e9 adopt\u00e9s pour construire des mod\u00e8les de pr\u00e9diction de rendement. Les r\u00e9sultats ont montr\u00e9 que les m\u00e9thodes individuelles de ML surpassaient les m\u00e9thodes de r\u00e9gression lin\u00e9aire, le mod\u00e8le d'ensemble de ML a encore am\u00e9lior\u00e9 les mod\u00e8les de ML uniques. De plus, les mod\u00e8les avec plus d'intrants ont obtenu de meilleures performances, la combinaison de donn\u00e9es satellitaires avec des donn\u00e9es environnementales, qui expliquaient respectivement 72\u00a0%, 69\u00a0% et 57\u00a0% de la variabilit\u00e9 du rendement du ma\u00efs, du riz et du soja, a d\u00e9montr\u00e9 des performances de pr\u00e9diction du rendement sup\u00e9rieures \u00e0 celles des intrants individuels. Alors que les donn\u00e9es satellitaires ont contribu\u00e9 \u00e0 la pr\u00e9diction du rendement des cultures principalement au d\u00e9but de la pointe de la saison de croissance, les donn\u00e9es climatiques ont fourni des informations suppl\u00e9mentaires principalement \u00e0 la pointe de la fin de la saison. Nous avons \u00e9galement constat\u00e9 que l'utilisation combin\u00e9e de l'IVE, du LST et du SIF a am\u00e9lior\u00e9 la pr\u00e9cision du mod\u00e8le par rapport au mod\u00e8le d'IVE de r\u00e9f\u00e9rence. Cependant, les indices de v\u00e9g\u00e9tation bas\u00e9s sur l'optique partageaient des informations similaires et ne fournissaient pas beaucoup d'informations suppl\u00e9mentaires au-del\u00e0 de l'IVE. Les pr\u00e9visions de rendement en cours de saison ont montr\u00e9 que les rendements des cultures peuvent \u00eatre pr\u00e9vus de mani\u00e8re satisfaisante deux \u00e0 trois mois avant la r\u00e9colte. La g\u00e9ographie, la topographie, la VOD, l'IVE, les param\u00e8tres hydrauliques du sol et les param\u00e8tres nutritifs sont plus importants pour la pr\u00e9diction du rendement des cultures.", "keywords": ["Atmospheric sciences", "Climate", "Multi-source satellite data", "Normalized Difference Vegetation Index", "Engineering", "Pathology", "Climate change", "Urban Heat Islands and Mitigation Strategies", "Linear regression", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Ecology", "Geography", "Statistics", "Agriculture", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Aerospace engineering", "Archaeology", "Physical Sciences", "Metallurgy", "Medicine", "Seasons", "Global Vegetation Models", "Biomass Estimation", "Regression analysis", "Vegetation (pathology)", "Crops", " Agricultural", "Environmental Engineering", "Environmental data", "Yield (engineering)", "Zea mays", "Environmental science", "Machine learning", "FOS: Mathematics", "Crop yield", "Biology", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "Predictive modelling", "Food security", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "Materials science", "Yield prediction", "Satellite", "13. 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