TY  - GEN
AU  - Pause,Marion
AU  - Wöhling,Thomas
AU  - Schulz,Karsten
AU  - Jagdhuber,Thomas
AU  - Schrön,Martin
AU  - Pause,Marion
AU  - Wöhling,Thomas
AU  - Schulz,Karsten
AU  - Jagdhuber,Thomas
AU  - Schrön,Martin
TI  - Remote Sensing of Regional Soil Moisture
SN  - books978-3-0365-2957-8
PY  - 2022///
CY  - Basel
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - History of engineering & technology
KW  - bicssc
KW  - instrument development
KW  - hyperspectral
KW  - spectroradiometry
KW  - LiDAR
KW  - soil
KW  - regional soil moisture
KW  - in situ network
KW  - AMSR2
KW  - FY3B
KW  - evaluation
KW  - EVI
KW  - SST
KW  - disaggregation
KW  - soil moisture
KW  - DISPATCH
KW  - Intermediate spatial resolution
KW  - SMAP
KW  - geostationary
KW  - validation
KW  - SEVIRI
KW  - thermal infrared
KW  - land surface temperature
KW  - downscaling
KW  - advanced scatterometer (ASCAT)
KW  - soil moisture active passive (SMAP)
KW  - random forest
KW  - low-cost sensor
KW  - AMSR-E
KW  - the microwave polarization difference index
KW  - surface soil moisture
KW  - regional scale
KW  - vegetation traits
KW  - multi-sensor approach
KW  - wetland
KW  - environmental monitoring
KW  - remote sensing
KW  - geostatistics
KW  - gap-filling
KW  - mesonet
KW  - ESA CCI SM
KW  - ASTER imagery
KW  - soil moisture content
KW  - thermal inertia model
KW  - serial dual-source model
KW  - surface component temperature
KW  - shadow impact
KW  - multi-model coupling
KW  - optimal solution method
KW  - ESA CCI
KW  - residual soil moisture
KW  - evapotranspiration
KW  - trend
KW  - rainfall variability
KW  - CHIRPS
KW  - theta probe
KW  - Sentinel-1A
KW  - NDVI
KW  - modified Dubois model
KW  - Sentinel-1/2
KW  - Landsat-8
KW  - GF-1
KW  - vegetation water content
KW  - Oh
KW  - Dubois
KW  - IEM
KW  - WCM
KW  - SSRT
KW  - SAR
KW  - LAI
KW  - wheat
KW  - Sentinel-1
KW  - support vector machine
KW  - ordinary least square regression
KW  - time series
KW  - Mongolia
KW  - MODIS
KW  - relative soil moisture
KW  - Chinese Loess Plateau
KW  - ATI
KW  - TVDI
N1  - Open Access
N2  - 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
UR  - https://mdpi.com/books/pdfview/book/4934
UR  - https://directory.doabooks.org/handle/20.500.12854/78840
ER  -