Mapping Temperate Savanna in Northeastern China Through Integrating UAV and Satellite Imagery

Abstract Temperate savannas are globally distributed ecosystems that play a crucial role in regulating the global carbon cycle and significantly contribute to human livelihoods. This study aims to develop a novel method for identifying temperate savannas and to map their distribution in Northeastern...

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Bibliographic Details
Main Authors: Xiaoya Li, Tao Duan, Kaijie Yang, Bin Yang, Chunmei Wang, Xin Tian, Qi Lu, Feng Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-05012-w
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Summary:Abstract Temperate savannas are globally distributed ecosystems that play a crucial role in regulating the global carbon cycle and significantly contribute to human livelihoods. This study aims to develop a novel method for identifying temperate savannas and to map their distribution in Northeastern China. To achieve this objective, Unmanned Aerial Vehicle (UAV) imagery was integrated with Sentinel-2 and Sentinel-1 satellite imagery using Random Forest  (RF) regression and Classification and Regression Tree (CART) algorithms. The training and validation datasets were derived from UAV imagery covering a ground area of 5 × 107m2. The proposed method achieved an overall accuracy of 0.82 in identifying temperate savanna in Northeastern China, covering a total area of 1.7 × 1011 m2. The resulting map significantly improves understanding of the spatial distribution and extent of temperate savannas. The developed methodology establishes a framework for assessing regional and global savanna distributions in future studies.
ISSN:2052-4463