Reprint

Remote Sensing of Evapotranspiration (ET)

Edited by
October 2019
240 pages
  • ISBN978-3-03921-602-4 (Paperback)
  • ISBN978-3-03921-603-1 (PDF)

This book is a reprint of the Special Issue Remote Sensing of Evapotranspiration (ET) that was published in

Engineering
Environmental & Earth Sciences
Summary

Evapotranspiration (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.

Format
  • Paperback
License
© 2019 by the authors; CC BY-NC-ND license
Keywords
component temperature decomposition; evapotranspiration partitioning; two-source energy balance model; surface energy balance algorithm for land (SEBAL); evapotranspiration; yield; remote sensing; heterogeneous conditions; evapotranspiration; eddy covariance observations; latent heat flux; a stratification method; multi-source; China; evapotranspiration; field-scale; STARFM; unmixing-based method; MPDI-integrated SEBS; remote sensing; surface energy balance model; calibration; METRIC; Google Earth Engine; evapotranspiration; water stress; model; partition; remote-sensing; ET; Thailand; ETMonitor; land surface temperature; Mun river basin; Chi river basin; MODIS; Surface Energy Balance System; Oklahoma Mesonet; Eddy-covariance; evapotranspiration; fusion; multi-source satellite data; Landsat 8; MODIS; SADFAET; evapotranspiration; uncertainty; land surface model; West Africa; evapotranspiration; remote sensing; Murrumbidgee River catchment; water resources management; ecosystem management; data fusion; evapotranspiration partitioning; land surface model; process-based model; water stress