Multispectral Remote Sensing Data Are Effective and Robust in Mapping Regional Forest Soil Organic Carbon Stocks in a Northeast Forest Region in China
Accurately mapping the spatial distribution information of soil organic carbon (SOC) stocks is a key premise for soil resource management and environment protection. Rapid development of satellite remote sensing provides a great opportunity for monitoring SOC stocks at a large scale. In this study,...
Main Authors: | Shuai Wang, Jinhu Gao, Qianlai Zhuang, Yuanyuan Lu, Hanlong Gu, Xinxin Jin |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-01-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/3/393 |
Similar Items
-
Predicting Soil Organic Carbon and Soil Nitrogen Stocks in Topsoil of Forest Ecosystems in Northeastern China Using Remote Sensing Data
by: Shuai Wang, et al.
Published: (2020-03-01) -
Hyperspectral remote sensing of tropical and sub-tropical forests /
by: Kalacska, Margaret, et al.
Published: (2008) -
Hyperspectral remote sensing of tropical and sub-tropical forests [electronic resource] /
by: Kalacska, Margaret, et al.
Published: (2008) -
Estimation of Aboveground Carbon Stocks in Forests Based on LiDAR and Multispectral Images: A Case Study of Duraer Coniferous Forests
by: Rina Su, et al.
Published: (2023-05-01) -
Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China
by: Shuai Wang, et al.
Published: (2023-01-01)