Remote Sensing of Regional Soil Moisture
Pause, Marion
Remote Sensing of Regional Soil Moisture - Basel MDPI - Multidisciplinary Digital Publishing Institute 2022 - 1 electronic resource (426 p.)
Open Access
Requests for regional soil moisture observations are increasing to parameterize complex hydrological models, to assess the impact of land-use changes, and to develop climate adaption strategies in the agricultural sector. Spatial land-use patterns have an impact on the soil water balance and groundwater recharge. Soil moisture is therefore a key parameter for the long-term monitoring and development of sustainable land-management and landscape design strategies that mitigate regional water scarcity and droughts. For example, the spatial organization of hedges or tree rows related to open land and wind direction avoids soil erosion, limits local evaporation, and increases local soil water storage. Since the early 1980s, satellite missions have been designed to monitor proxies for soil moisture, mainly at the national and global scale, with a relatively coarse pixel resolution and low accuracy. The local effects of weather and climate are very dynamic in space and time. Thus, a strong need exists for more accurate, regional-scale remote sensing products for soil moisture. The transfer of existing, proof-of-concept algorithms to region-specific monitoring frameworks is urgent. This Special Issue provides an overview of current developments on remote sensing-based soil moisture observations that are applicable at a regional scale. The compendium of research papers demonstrates the benefits of concurrently utilizing multi-source remote sensing data and in situ measurements through: - Using additional data and site-specific knowledge; - Combining empirical and physical approaches; - Developing concepts to deal with mixed pixels.
Creative Commons
English
books978-3-0365-2957-8 9783036529578 9783036529561
10.3390/books978-3-0365-2957-8 doi
History of engineering & technology
instrument development hyperspectral spectroradiometry LiDAR soil regional soil moisture in situ network AMSR2 FY3B evaluation EVI SST disaggregation soil moisture DISPATCH Intermediate spatial resolution SMAP geostationary validation SEVIRI thermal infrared land surface temperature downscaling advanced scatterometer (ASCAT) soil moisture active passive (SMAP) random forest low-cost sensor AMSR-E the microwave polarization difference index surface soil moisture regional scale vegetation traits multi-sensor approach wetland environmental monitoring remote sensing geostatistics gap-filling mesonet ESA CCI SM ASTER imagery soil moisture content thermal inertia model serial dual-source model surface component temperature shadow impact multi-model coupling optimal solution method ESA CCI residual soil moisture evapotranspiration trend rainfall variability CHIRPS theta probe Sentinel-1A NDVI modified Dubois model Sentinel-1/2 Landsat-8 GF-1 vegetation water content Oh Dubois IEM WCM SSRT SAR LAI wheat Sentinel-1 support vector machine ordinary least square regression time series Mongolia MODIS relative soil moisture Chinese Loess Plateau ATI TVDI
Remote Sensing of Regional Soil Moisture - Basel MDPI - Multidisciplinary Digital Publishing Institute 2022 - 1 electronic resource (426 p.)
Open Access
Requests for regional soil moisture observations are increasing to parameterize complex hydrological models, to assess the impact of land-use changes, and to develop climate adaption strategies in the agricultural sector. Spatial land-use patterns have an impact on the soil water balance and groundwater recharge. Soil moisture is therefore a key parameter for the long-term monitoring and development of sustainable land-management and landscape design strategies that mitigate regional water scarcity and droughts. For example, the spatial organization of hedges or tree rows related to open land and wind direction avoids soil erosion, limits local evaporation, and increases local soil water storage. Since the early 1980s, satellite missions have been designed to monitor proxies for soil moisture, mainly at the national and global scale, with a relatively coarse pixel resolution and low accuracy. The local effects of weather and climate are very dynamic in space and time. Thus, a strong need exists for more accurate, regional-scale remote sensing products for soil moisture. The transfer of existing, proof-of-concept algorithms to region-specific monitoring frameworks is urgent. This Special Issue provides an overview of current developments on remote sensing-based soil moisture observations that are applicable at a regional scale. The compendium of research papers demonstrates the benefits of concurrently utilizing multi-source remote sensing data and in situ measurements through: - Using additional data and site-specific knowledge; - Combining empirical and physical approaches; - Developing concepts to deal with mixed pixels.
Creative Commons
English
books978-3-0365-2957-8 9783036529578 9783036529561
10.3390/books978-3-0365-2957-8 doi
History of engineering & technology
instrument development hyperspectral spectroradiometry LiDAR soil regional soil moisture in situ network AMSR2 FY3B evaluation EVI SST disaggregation soil moisture DISPATCH Intermediate spatial resolution SMAP geostationary validation SEVIRI thermal infrared land surface temperature downscaling advanced scatterometer (ASCAT) soil moisture active passive (SMAP) random forest low-cost sensor AMSR-E the microwave polarization difference index surface soil moisture regional scale vegetation traits multi-sensor approach wetland environmental monitoring remote sensing geostatistics gap-filling mesonet ESA CCI SM ASTER imagery soil moisture content thermal inertia model serial dual-source model surface component temperature shadow impact multi-model coupling optimal solution method ESA CCI residual soil moisture evapotranspiration trend rainfall variability CHIRPS theta probe Sentinel-1A NDVI modified Dubois model Sentinel-1/2 Landsat-8 GF-1 vegetation water content Oh Dubois IEM WCM SSRT SAR LAI wheat Sentinel-1 support vector machine ordinary least square regression time series Mongolia MODIS relative soil moisture Chinese Loess Plateau ATI TVDI