Cited by 197Remote-Sensing Image ClassificationFlood Risk Assessment and ManagementHydrology and Watershed Management Studies

An approach for global monitoring of surface water extent variations in reservoirs using MODIS data

Open access
Khandelwal, Ankush, Karpatne, Anuj, Marlier, Miriam E., Kim, Jongyoun, Lettenmaier, Dennis P., Kumar, Vipin·2017·Remote Sensing of Environment

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Crossref · 10.1016/j.rse.2017.05.039

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65 of 65 references verified0 citation errors · 0 not checkable

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Authors
Khandelwal, A., Karpatne, A., Marlier, M. E., Kim, J., Lettenmaier, D. P., & Kumar, V.
Affiliations
  • University of Minnesota (US)
  • University of California, Los Angeles (US)
Corresponding author
Kumar, Vipin
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2017-12
Volume
202
Pages
113-128
ISSN
0034-4257 (ISSN-L)
OpenAlex
W2722058651
Cited by
197
References
65
Citations by year
2026: 15 · 2025: 13 · 2024: 19 · 2023: 18 · 2022: 40 · 2021: 30 · 2020: 31 · 2019: 16 · 2018: 9 · 2017: 6
FWCI
14.08
Type
journal article
Language
en
Open access
Locations
Remote Sensing of Environment (acceptedVersion)
Funders
  • NSF (1029711, NNX13AK45A)
  • University of Minnesota
Topics
  • Physical Sciences › Engineering › Media Technology › Remote-Sensing Image Classification
  • Physical Sciences › Environmental Science › Global and Planetary Change › Flood Risk Assessment and Management
  • Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
Keywords
reservoir surface area, surface water extent, MODIS, satellite radar altimetry, supervised classification, Landsat, freshwater resources

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