Forest Structural Variable Estimation is a methodological framework within remote sensing that enables the quantification of forest structural attributes, such as canopy height, biomass, and vertical stratification, by differentiating spectral, spatial, and textural information derived from airborne or satelliteborne sensor data.
155
Publications
10.2K
Citations
580
Authors
244
Institutions
Publications per year
2017–2026
61
Parents
Publications
155
Lidar Remote Sensing for Forestry
Ralph Dubayah, Jason Drake · Journal of Forestry · 2000 · 642 citations · Full text
1–5 of 155
Authors
580
- NC
6
h-index
- XS
5
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- JEJohan E. S. Fransson
Swedish University of Agricultural Sciences, Sweden
4 publications · 404 citations
4
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- LC
4
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- JH
4
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1–5 of 580
Institutions
244
University of Helsinki
Helsinki, Finland
7 h-index
15 publications
553 citations
Jet Propulsion Laboratory
Pasadena, United States
7 h-index
10 publications
861 citations
Swedish University of Agricultural Sciences
Uppsala, Sweden
6 h-index
20 publications
1.6K citations
Canadian Forest Service
Ottawa, Canada
6 h-index
9 publications
886 citations
University of British Columbia
Vancouver, Canada
6 h-index
15 publications
1.5K citations
Nanjing Forestry University
Nanjing, China
5 h-index
28 publications
1.1K citations
Goddard Space Flight Center
Greenbelt, United States
5 h-index
6 publications
179 citations
Natural Resources Canada
Ottawa, Canada
5 h-index
8 publications
681 citations
1–8 of 244
Venues
- Remote Sensing of Environment
21 publications · 2.5K citations
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- Remote Sensing
19 publications · 700 citations
16
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- ISPRS Journal of Photogrammetry and Remote Sensing
10 publications · 499 citations
10
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- IEEE Transactions on Geoscience and Remote Sensing
9 publications · 924 citations
9
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- International Journal of Applied Earth Observation and Geoinformation
JAG · 7 publications · 367 citations
7
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1–5