Aboveground Biomass in Tajikistan

Published: 22 May 2025| Version 1 | DOI: 10.17632/rjphh3yxs4.1
Contributors:
Lyna H, Shuang He, Huping Ye, Xiaohan Liao, Dalai Dalai Bayin, Mekhrovar Okhonniyozov, Mustafo Safarov

Description

We develop a dynamic sampling scale-up method for AGB estimation by integrating multi-source data from Sentinel-2 MSI, Unmanned Aerial Vehicle (UAV), and ground observations. Initially, UAV and Sentinel-2 multispectral images are separately combined with ground-measured data for feature interaction analysis and factors selection. Subsequently, eight machine-learning models are constructed and optimized for AGB estimation at different scales. The dynamic sampling scale-up algorithm based on UAV and ground data enhances AGB estimation accuracy based on the optimal models.

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Steps to reproduce

See the paper for specific reproduction details: "Estimation of Aboveground Biomass in Tajikistan Based on Upscaling Extrapolation of UAV and Sentinel-2 Multi-Source Data Synergy"

Institutions

Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences

Categories

Remote Sensing, Biomass

Funding

National Centre for Research and Development

2023YFB3905700

National Centre for Research and Development

2019YFE0126500

Shenzhen Science and Technology Innovation Commission

KJZD20230923115210021

Licence