Mapping Forest Ecosystem Biomass Density for Xiangjiang River Basin by Combining Plot and Remote Sensing Data and Comparing Spatial Extrapolation Methods

• Published in: Remote sensing (Basel, Switzerland) Vol. 9; no. 3; p. 241
• Main Authors: Zhu, Jia, Huang, Zhihong, Sun, Hua, Wang, Guangxing
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2017
• Subjects: Algorithms; Biomass; Carbon cycle; Density; Ecosystems; Forest biomass; Forest ecosystems; Forests; Heterogeneity; improved kNN algorithm; Interpolation; K-nearest neighbors algorithm; Landsat; Landsat satellites; leave-one-out cross-validation; logistic regression; Mapping; multivariate linear regression; Regression models; Remote sensing; River basins; River ecology; Rivers; Satellite imagery; Spatial data; Spatial distribution; Spatial heterogeneity; Terrestrial ecosystems; Xiangjiang River Basin; China; Xiangjiang River

The distribution of forest biomass in a river basin usually has obvious spatial heterogeneity in relation to the locations of the upper and lower reaches of the basin. In the subtropical region of China, a large amount of forest biomass, comprising diverse forest types, plays an important role in ma...