Remote Sensing-based Density Estimation
Remote Sensing-Based Density Estimation is a methodological framework within stand density estimation that utilizes remotely sensed data, such as aerial or satellite imagery, to quantitatively infer vegetation density through spatial, spectral, and structural analysis of canopy cover and plant biomass distribution.
68
Publications
2.8K
Citations
198
Authors
98
Institutions
Publications per year
2017–2026
27
Parents
68
1–5 of 68
198
2
h-index
University of California, Los Angeles, United States
2 publications · 52 citations
2
h-index
2
h-index
2
h-index
Gorgan University of Agricultural Sciences and Natural Resources, Iran
2 publications · 88 citations
2
h-index
1–5 of 198
98
National Institute for Environmental Studies
Tsukuba, Japan
3 h-index
8 publications
316 citations

Hokkaido University
Sapporo, Japan
3 h-index
5 publications
220 citations
Central University of Jharkhand
Ranchi, India
2 h-index
4 publications
125 citations

Université de Sherbrooke
Sherbrooke, Canada
2 h-index
3 publications
160 citations
Nanjing University
Nanjing, China
2 h-index
9 publications
234 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
1 publications
55 citations
Birla Institute of Technology, Mesra
Ranchi, India
2 h-index
4 publications
95 citations

Universitas Gadjah Mada
Yogyakarta, Indonesia
2 h-index
4 publications
48 citations
1–8 of 98
8 publications · 361 citations
8
h-index
5 publications · 184 citations
6
h-index
JAG · 2 publications · 149 citations
3
h-index
3 publications · 206 citations
3
h-index
2 publications · 131 citations
2
h-index
1–5