Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach

Muhammad Sarfraz Khan; Umar Waqas Liaqat; Jongjin Baik; Minha Choi

doi:10.1016/j.agrformet.2018.01.022

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Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach

Muhammad Sarfraz Khan Umar Waqas Liaqat Jongjin Baik Minha Choi

Year: 2018 Journal: Agricultural and Forest Meteorology Vol: 252 Pages: 256-268 Publisher: Elsevier BV

DOI: 10.1016/j.agrformet.2018.01.022

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Keywords:

Evapotranspiration Mean squared error Environmental science Collocation (remote sensing) Scale (ratio) Data assimilation Random forest Measurement uncertainty Statistics Remote sensing Mathematics Computer science Meteorology Machine learning Ecology Cartography Geography

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Plant Water Relations and Carbon Dynamics

Physical Sciences → Environmental Science → Global and Planetary Change

Hydrology and Watershed Management Studies

Physical Sciences → Environmental Science → Water Science and Technology

Soil and Unsaturated Flow

Physical Sciences → Engineering → Civil and Structural Engineering

Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach

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