LEADER 03957nam 2200877z- 450 001 9910367754003321 005 20231214133505.0 010 $a3-03921-603-1 035 $a(CKB)4100000010106177 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/58175 035 $a(EXLCZ)994100000010106177 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRemote Sensing of Evapotranspiration (ET) 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 electronic resource (240 p.) 311 $a3-03921-602-3 330 $aEvapotranspiration (ET) is a critical component of the water and energy balances, and the number of remote sensing-based ET products and estimation methods has increased in recent years. Various aspects of remote sensing of ET are reported in the 11 papers published in this book. The major research areas covered by this book include inter-comparison and performance evaluation of widely used one- and two-source energy balance models, a new dual-source model (Soil Plant Atmosphere and Remote Sensing Evapotranspiration, SPARSE), and a process-based model (ETMonitor); assessment of multi-source (e.g., remote sensing, reanalysis, and land surface model) ET products; development or improvement of data fusion frameworks to predict continuous daily ET at a high spatial resolution (field-scale or 30 m) by fusing the advanced spaceborne thermal emission reflectance radiometer (ASTER), the moderate resolution imaging spectroradiometer (MODIS), and Landsat data; and investigating uncertainties in ET estimates using an ET ensemble composed of several land surface models and diagnostic datasets. The effects of the differences between ET products on water resources and ecosystem management were also investigated. More accurate ET estimates and improved understanding of remotely sensed ET products are crucial for maximizing crop productivity while minimizing water losses and management costs. 517 $aRemote Sensing of Evapotranspiration 610 $aEddy-covariance 610 $asurface energy balance model 610 $aevapotranspiration 610 $aOklahoma Mesonet 610 $aChi river basin 610 $aSADFAET 610 $aa stratification method 610 $aecosystem management 610 $aprocess-based model 610 $aheterogeneous conditions 610 $aland surface temperature 610 $aETMonitor 610 $amodel 610 $alatent heat flux 610 $amulti-source 610 $awater resources management 610 $aremote sensing 610 $aET 610 $afusion 610 $aGoogle Earth Engine 610 $awater stress 610 $acomponent temperature decomposition 610 $adata fusion 610 $aMun river basin 610 $aMurrumbidgee River catchment 610 $aremote-sensing 610 $aThailand 610 $auncertainty 610 $afield-scale 610 $apartition 610 $aland surface model 610 $atwo-source energy balance model 610 $aSurface Energy Balance System 610 $aChina 610 $aevapotranspiration partitioning 610 $ayield 610 $acalibration 610 $aunmixing-based method 610 $aLandsat 8 610 $aeddy covariance observations 610 $aMETRIC 610 $aMODIS 610 $asurface energy balance algorithm for land (SEBAL) 610 $aWest Africa 610 $aMPDI-integrated SEBS 610 $aSTARFM 610 $amulti-source satellite data 700 $aGowda$b Prasanna$4auth$01326368 702 $aWagle$b Pradeep$4auth 906 $aBOOK 912 $a9910367754003321 996 $aRemote Sensing of Evapotranspiration (ET)$93037387 997 $aUNINA