Remote Sensing-based Estimation
Remote Sensing-Based Estimation is a methodological approach that belongs to the genus of environmental monitoring techniques and is differentiated by its reliance on satellite or aerial sensor data to infer biophysical parameters, specifically Leaf Area Index, through empirical, physical, or machine learning models.
761
Publications
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Citations
3.1K
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Institutions
Publications per year
2017–2026
391
Parents
761
Novel algorithms for remote estimation of vegetation fraction
Anatoly A. Gitelson, Yoram J. Kaufman, Robert J. Stark et al. · Remote Sensing of Environment · 2002 · 2.1K citations
Remote estimation of canopy chlorophyll content in crops
Anatoly A. Gitelson, Andrés Viña, Verónica Ciganda et al. · Geophysical Research Letters · 2005 · 1.6K citations · Full text
Agriculture, Agronomy, Crop Sciences +17
Emmett W. Chappelle, Moon S. Kim, J. E. McMurtrey · Remote Sensing of Environment · 1992 · 828 citations
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Chinese Academy of Sciences
Beijing, China
40 h-index
332 publications
19.4K citations
University of Nebraska–Lincoln
Lincoln, United States
28 h-index
95 publications
39.9K citations
University of Chinese Academy of Sciences
Beijing, China
26 h-index
115 publications
5K citations
State Key Laboratory of Remote Sensing Science
Beijing, China
21 h-index
119 publications
11.1K citations
Wuhan University
Wuhan, China
21 h-index
84 publications
5.8K citations
University of Maryland, College Park
College Park, United States
20 h-index
28 publications
3K citations
Institute of Remote Sensing and Digital Earth
Beijing, China
20 h-index
94 publications
5.5K citations

Beijing Normal University
Beijing, China
19 h-index
113 publications
8.1K citations
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124 publications · 5.7K citations
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67 publications · 11.9K citations
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40 publications · 2.5K citations
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28 publications · 2.4K citations
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15 publications · 1.6K citations
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