Aboveground Biomass in Tajikistan

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.

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

  Beijing, Beijing

Categories

Funders

• National Centre for Research and Development

  Mazovia, Poland

  Grant ID: 2023YFB3905700
• National Centre for Research and Development

  Mazovia, Poland

  Grant ID: 2019YFE0126500
• Shenzhen Science and Technology Innovation Commission

  Guangdong, China

  Grant ID: KJZD20230923115210021

Licence