Work

High-resolution surface and rootzone soil moisture over US cropland: A novel framework assimilating multi-source remote sensing data, machine learning, and the Layered Green and Ampt Infiltration with Redistribution model

Year: 2025

Type: article

Source: Remote Sensing of Environment

DOI: 10.1016/j.rse.2025.115167

Authors: Shuohao Cai, Yijia Xu, Zhengwei Yang, Wade T. Crow, Zhou Zhang, Jiali Shang, Jiangui Liu, Peter La Follette, Chris Reberg-Horton, Harry Schomberg, Steven Mirsky, Brian Davis, Sarah Seehaver, Alexis Correira, Andrea Basche, Ashley Waggoner, Charles Ellis, Dara Park, Danielle D. Treadwell, David Campbell, Deann Presley, Esleyther L. Henriquez Inoa, Heather Darby, Jared Adam, Jarrod Miller, Joseph Haymaker, John Wallace, Julia Gaskin, Kipling S. Balkcom, Lindsey Ruhl, Mark Reiter, Matthew Ruark, Michael Flessner, Cynthia Sias, Payton Davis, Peter Tomlinson, Richard G. Smith, Nicholas D. Warren, Ryan Dierking, Shalamar Armstrong, Tauana Almeida, Jingyi Huang

Language: English

Topic: Soil Moisture and Remote Sensing

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Zero hunger, Life on land, Climate action

Open Access status: green

Funders: U.S. Department of Agriculture, Wisconsin Alumni Research Foundation, University of Wisconsin-Madison, University of Minnesota, University of Florida, Office of the Vice Chancellor for Research and Graduate Education, University of Wisconsin-Madison

Awards: G6020433021, G6878459849

OpenAlex ID: W4417076413

FWCI: 1.456

Cites: 58

Cited by: 5

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