{"type": "FeatureCollection", "features": [{"id": "10.1109/JURSE.2017.7924594", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:18:23Z", "type": "Journal Article", "created": "2017-05-12", "title": "Spatial distribution of sensible and latent heat flux in the URBANFLUXES case study city Basel (Switzerland)", "description": "Turbulent sensible and latent heat fluxes are calculated by a combined method using micrometeorological approaches (the Aerodynamic Resistance Method ARM), Earth Observation (EO) data and GIS-Techniques. The spatial distributions of turbulent heat fluxes were analyzed for 22 for the city of Basel (Switzerland), covering all seasons and different meteorological conditions. Seasonal variations in heat fluxes are strongly dependent on meteorological conditions, i.e. air temperature, water vapor saturation deficit and wind speed. The agreement of measured fluxes (by the Eddy Covariance method) with modeled fluxes in the weighted source area of the flux towers is moderate due to known drawbacks in the modelling approach and uncertainties inherent to EC measurements, particularly also in urban areas.", "keywords": ["H2020 URBANFLUXES", "13. Climate action", "Sensible Heat Flux", "11. Sustainability", "0211 other engineering and technologies", "Urban Remote Sensing", "02 engineering and technology", "Latent Heat Flux", "7. Clean energy", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://xplorestaging.ieee.org/ielx7/7919506/7924526/07924594.pdf?arnumber=7924594"}, {"href": "https://doi.org/10.1109/JURSE.2017.7924594"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2017%20Joint%20Urban%20Remote%20Sensing%20Event%20%28JURSE%29", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1109/JURSE.2017.7924594", "name": "item", "description": "10.1109/JURSE.2017.7924594", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1109/JURSE.2017.7924594"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-03-01T00:00:00Z"}}, {"id": "10.3390/rs12071181", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:20:55Z", "type": "Journal Article", "created": "2020-04-08", "title": "Multi-Scale Evaluation of the TSEB Model over a Complex Agricultural Landscape in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm\u22122 and 0.79 and 82.0 Wm\u22122 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm\u22122), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm\u22122). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.</p></article>", "keywords": ["covariance system", "eddy covariance system", "550", "latent heat flux; sensible heat flux; two-source energy balance; eddy covariance system; scintillometer", "Science", "Q", "0207 environmental engineering", "02 engineering and technology", "15. Life on land", "sensible heat flux", "two-source energy balance", "7. Clean energy", "01 natural sciences", "[SDV.EE] Life Sciences [q-bio]/Ecology", " environment", "latent heat flux", "13. Climate action", "[SDV.EE]Life Sciences [q-bio]/Ecology", "14. Life underwater", "eddy", "environment", "scintillometer", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/7/1181/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/7/1181/pdf"}, {"href": "https://doi.org/10.3390/rs12071181"}, {"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/rs12071181", "name": "item", "description": "10.3390/rs12071181", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs12071181"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-04-07T00:00:00Z"}}, {"id": "10.4995/raet.2015.2310", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:21:18Z", "type": "Journal Article", "created": "2015-06-26", "title": "Seguimiento de los flujos de calor sensible y calor latente en vid mediante la aplicaci\u00f3n del balance de energ\u00eda METRIC", "description": "<p><p>En este trabajo se presenta el seguimiento de los flujos de energ\uffc3\uffada en un cultivo de vid bajo riego, obtenidos\uffc2\uffa0a partir del modelo de balance de energ\uffc3\uffada METRIC (Allen et al., 2007b). Este modelo resulta operativo al utilizar un\uffc2\uffa0m\uffc3\uffa9todo de calibraci\uffc3\uffb3n interna definido a partir de la selecci\uffc3\uffb3n de p\uffc3\uffadxeles con valores extremos dentro de la escena. De\uffc2\uffa0esta manera se obtuvieron mapas de radiaci\uffc3\uffb3n neta (Rn), flujo de calor en suelo (G), calor sensible (H), calor latente\uffc2\uffa0(LE), evapotranspiraci\uffc3\uffb3n (ET) y coeficiente de cultivo (Kc). Estos valores fueron validados con registros obtenidos en el\uffc2\uffa0sitio, utilizando una torre de flujos turbulentos (covarianza de torbellinos). El RMSE fue 43 W m<sup>-2</sup>,33 W m<sup>-2</sup>, 55 W m<sup>-2</sup>\uffc2\uffa0y\uffc2\uffa040 W m<sup>-2</sup>\uffc2\uffa0en Rn, G, H y LE, los cuales en t\uffc3\uffa9rminos relativos representan un 8%, 29 %, 21% y 20% respectivamente. A\uffc2\uffa0escala diaria el RMSE para la ET fue de 0,58 mm d\uffc3\uffada<sup>-1</sup>, con un valor de Kc m\uffc3\uffa1ximo y estable de 0,42\uffc2\uffb10,08. Estos resultados\uffc2\uffa0permiten considerar que el m\uffc3\uffa9todo es adecuado y operativo para el seguimiento de la evapotranspiraci\uffc3\uffb3n y\uffc2\uffa0c\uffc3\uffa1lculo de las necesidades h\uffc3\uffaddricas del vi\uffc3\uffb1edo evaluado.</p></p>", "keywords": ["Coeficiente de cultivo", "Latent heat", "Geography (General)", "Evapotranspiration", "calor latente", "Calor latente", "0211 other engineering and technologies", "Energy balance", "02 engineering and technology", "15. Life on land", "Vid", "7. Clean energy", "01 natural sciences", "calor sensible", "13. Climate action", "Crop coefficient", "G1-922", "Balance de energ\u00eda", "coeficiente de cultivo", "Evapotranspiraci\u00f3n", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.4995/raet.2015.2310"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Revista%20de%20Teledetecci%C3%B3n", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.4995/raet.2015.2310", "name": "item", "description": "10.4995/raet.2015.2310", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.4995/raet.2015.2310"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-06-26T00:00:00Z"}}, {"id": "10.5194/hess-2019-105", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:21:50Z", "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": "2026-07-26T16:21:50Z", "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": "2940609395", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:53Z", "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": "3015719051", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:26:03Z", "type": "Journal Article", "created": "2020-04-08", "title": "Multi-Scale Evaluation of the TSEB Model over a Complex Agricultural Landscape in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm\u22122 and 0.79 and 82.0 Wm\u22122 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm\u22122), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm\u22122). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.</p></article>", "keywords": ["covariance system", "eddy covariance system", "550", "latent heat flux; sensible heat flux; two-source energy balance; eddy covariance system; scintillometer", "Science", "Q", "0207 environmental engineering", "02 engineering and technology", "15. Life on land", "sensible heat flux", "two-source energy balance", "01 natural sciences", "7. Clean energy", "[SDV.EE] Life Sciences [q-bio]/Ecology", " environment", "latent heat flux", "13. Climate action", "[SDV.EE]Life Sciences [q-bio]/Ecology", "14. Life underwater", "eddy", "environment", "scintillometer", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/7/1181/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/7/1181/pdf"}, {"href": "https://doi.org/3015719051"}, {"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": "3015719051", "name": "item", "description": "3015719051", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3015719051"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-04-07T00:00:00Z"}}, {"id": "10.60692/g4rcv-eqz54", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:24:12Z", "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. 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