ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1573438
This article is part of the Research TopicForest Landscape Restoration (FLR) and Carbon Storage DynamicsView all articles
Spatial heterogeneity of forest carbon stocks in the Xiangjiang River Basin urban agglomeration: analysis and assessment based on the Multiscale Geographically Weighted Regression (MGWR) model
Provisionally accepted
Yingfeng Kuang1
Xiaolong Chen2*- 1Macau University of science and Technology, macao, China
- 2Macao Polytechnic University, Macau, Macao, SAR China
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PurposeUrban forests are crucial for mitigating global warming and achieving carbon neutrality. This study aims to analyze the spatialheterogeneity of forest carbon stocks in the Xiangjiang River Basin urban agglomeration. By comparing the ordinary least squares (OLS)model and four geographically weighted regression (GWR) models, we aim to provide a reliable method for estimating large-scale forestcarbon stocks and support the construction of the Xiangjiang River Basin forest urban agglomeration.MethodUsing data from the tenthcontinuous forest resource inventory and climate data in Hunan Province, five key variables were identified: average breast diameter, standdensity, average age, average tree height, and average annual precipitation. The OLS and four GWR models (including MGWR) wereconstructed using SPSS V27 and MGWR 2.2 software. The MGWR (Gaussian) model was selected as optimal based on model fit andindependent sample tests.ResultsThe GWR models outperformed the OLS model in terms of fit and prediction accuracy. The MGWR modelbest captured spatial heterogeneity, estimating the forest carbon stock at 31.162 t/hm², with higher values in the central areas and lowervalues in the periphery. This pattern provides a scientific basis for managing and protecting forest resources in the region.ConclusionThisstudy effectively reflects the spatial relationship between forest carbon stocks and key variables, enhancing the accuracy of large-scalecarbon stock distribution. The findings highlight the importance of forest carbon stocks in the Xiangjiang River Basin for regional ecologicalsecurity and climate change mitigation, offering valuable insights for forest resource management.
Keywords: Xiangjiang River basin, Urban agglomeration, GWR model, MGWR model, forest carbon storage, Spatial heterogeneity
Received: 09 Feb 2025; Accepted: 13 May 2025.
Copyright: © 2025 Kuang and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiaolong Chen, Macao Polytechnic University, Macau, Macao, SAR China
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