Estimation of Subtropical Forest Aboveground Biomass Using Active and Passive Sentinel Data with Canopy Height
Forest biomass is closely related to carbon sequestration capacity and can reflect the level of forest management. This study utilizes four machine learning algorithms, namely Multivariate Stepwise Regression (MSR), K-Nearest Neighbors (k-NN), Artificial Neural Network (ANN), and Random Forest (RF),...
Saved in:
Main Authors: | Yi Wu, Yu Chen, Chunhong Tian, Ting Yun, Mingyang Li |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/17/14/2509 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Large-scale ecological engineering increases forest canopy height in Loess Plateau from 1985 to 2020
by: Mengxue Liu, et al.
Published: (2025-12-01) -
A spatially comprehensive canopy cover dataset derived from NASA’s ice, cloud and land elevation satellite-2 (ICESat-2) for the state of Alabama, USAThe Open Science Framework
by: Lana L. Narine, et al.
Published: (2025-10-01) -
Deforestation in the Special Nature Reserve Gornje Podunavlje: Insights from PlanetScope, Sentinel-2 and Landsat-8 remote sensing data
by: Nikolić Ratko R.
Published: (2025-01-01) -
A subregional shallow water bathymetry derivation method for coral reef using ICESat-2 and Sentinel-2 combined with sediment information
by: Caixiang Xu, et al.
Published: (2025-08-01) -
Use of GLOBE observer citizen science data to validate continental-scale canopy height maps derived from ICESat-2 and GEDI
by: Mei-Kuei Lu, et al.
Published: (2025-07-01)