Addressing challenges for mapping irrigated fields in subhumid temperate regions by integrating remote sensing and hydroclimatic data

Remote Sensing

Volumn 11, Issue 3, 2019, Pages

  Xu, Tianfang ^a,b   Deines, Jillian M ^b,c   Kendall, Anthony D ^b   Basso, Bruno ^b   Hyndman, David W ^b  

^a Utah State University   (United States)

^b MICHIGAN STATE UNIVERSITY   (United States)

^c STANFORD UNIVERSITY   (United States)

Author keywords

Irrigation mapping; Random forest; Remote sensing; Subhumid region

Indexed keywords

CROPS; DECISION TREES; GROUNDWATER; IRRIGATION; LEARNING SYSTEMS; MAPPING;

HIGH-RESOLUTION MAPPING; IRRIGATION WATERS; MACHINE LEARNING METHODS; RAIN FED AGRICULTURE; RANDOM FORESTS; SPATIAL AND TEMPORAL PATTERNS; SUBHUMID REGIONS; TEMPERATE REGIONS;

REMOTE SENSING;

EID: 85061397655     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs11030370     Document Type: Article

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