基于GEE的中国亚热带森林退化时空特征及驱动因素分析

李正艳; 张爱竹; 孙根云

doi:10.11834/jrs.20263155

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基于GEE的中国亚热带森林退化时空特征及驱动因素分析
Spatial and temporal characteristics and drivers of forest degradation in subtropical China based on GEE
2026年30卷第5期页码：1262-1272
收稿：2024-05-15，

纸质出版：2026-05-07
DOI： 10.11834/jrs.20263155
稿件说明：

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李正艳，张爱竹，孙根云.2026.基于GEE的中国亚热带森林退化时空特征及驱动因素分析.遥感学报，30（5）： 1262-1272 DOI： 10.11834/jrs.20263155.

Li Z Y，Zhang A Z and Sun G Y. 2026. Spatial and temporal characteristics and drivers of forest degradation in subtropical China based on GEE. National Remote Sensing Bulletin， 30（5）：1262-1272 DOI： 10.11834/jrs.20263155.

摘要

森林资源在应对全球气候变化、维系生物多样性、实现生态文明建设等领域发挥着关键作用。中国亚热带森林占全国总量的44%，保护亚热带森林资源对于实现中国可持续发展目标具有重要意义。然而近30年来，自然条件变化和人类活动的的叠加，对亚热带森林构成了严重威胁。为明确中国亚热带森林退化趋势，本研究利用中国年度土地覆盖数据CLCD（Annual China Land Cover Dataset）长时序遥感产品，结合掩膜提取、莫兰指数和交互作用探测等分析方法，基于谷歌地球引擎GEE（Google Earth Engine）遥感云计算平台分析了1990—2020年中国亚热带森林退化的时空分布特征及其驱动因素。结果表明：（1）1990年以来，中国亚热带森林退化面积达2539.63万hm

，相当于全国森林总量的17.96%，其中38%转变为耕地和草地；（2）空间呈东北向西南递增，分布呈高值、低值、高低、低高聚类且具有一定的空间自相关性；（3）退化主要在海拔2250 m以下、坡度小于50°的地区，区域海拔与坡度均呈倒U型分布，波峰分别出现在150 m和8°；（4）单驱动因素对于退化的影响并不明显，但坡度与人均GDP共同作用对1990—2019年中国亚热带森林退化影响

值高达0.96。

Abstract

Forests represent one of the most critical natural resources in the pursuit of global sustainability

fulfilling indispensable roles in climate regulation

biodiversity conservation

and the promotion of ecological civilization. In China

subtropical forests account for approximately 44% of the nation’s total forest coverage

highlighting their essential function in maintaining regional ecological security and supporting national sustainable development goals. Over the past three decades

however

the accelerating convergence of natural stressors and anthropogenic interventions has resulted in the severe and widespread degradation of these fragile ecosystems. To investigate meticulously the spatiotemporal evolution and underlying mechanisms of forest degradation across subtropical China

this study leveraged a multidimensional analytical framework that incorporated the annual China land cover dataset

a high—resolution

longitudinally consistent remote sens

ing product

with geospatial computational modeling on the Google Earth Engine platform. A comprehensive suite of methodologies

including spectral index—based mask extraction

spatial autocorrelation analysis by using global and local Moran’s

indices

and geographical detector modeling

was employed to quantify individual and interactive driver influences that spanned the period from 1990 to 2020. The analysis yields several critical and nuanced insights. (1) Since 1990

the cumulative degraded forest area in subtropical China has amounted to 25.3963 million ha

equivalent to 17.96% of the country’s total forest inventory. Within this degraded area

38% has been transformed into cropland and grassland

illustrating the profound effects of agricultural expansion and economic development on forest cover change. (2) Spatially

the degradation exhibits a pronounced increasing gradient from northeastern to southwestern subregions

with cartographic patterns revealing significant clustering behavior

specifically high-high clusters (hotspots of degradation)

low-low clusters (coldspots)

and spatial outliers

such as high-low and low-high associations. These patterns

validated through local indicators of spatial association

indicate not only regional aggregation of forest loss but also strong spatial dependency

which is characteristic of environmentally contagious degradation processes. (3) Topographic analysis indicates that forest degradation occurs predominantly at elevations below 2

250 m and on slopes less than 50°. The distribution of the degradation area relative to elevation and slope manifests a distinct inverted U—shape

peaking at 150 m and 8°

respectively. This condition suggests that moderate terrain

which is characterized by higher accessibility and suitability for human modification

is most susceptible to ecological disturbance. (4) While individual biophysical and socioeconomic factors

including slope

aspect

population density

and gross domestic product (GDP) per capita

monstrate limited explanatory power when considered in isolation

their pairwise interactions exhibit substantially stronger influences. The interaction between slope and GDP per capita is particularly salient

with a q—value of 0.96 in geographical detector analysis

underscoring the synergistic effect of economic development and terrain conditions in driving forest degradation. The current study elucidates the complex

multifaceted nature of forest degradation in subtropical China

weaving topographic

economic

and demographic factors into an integrated explanatory framework. It emphasizes the necessity of adopting holistic forest governance strategies that harmonize economic development with ecological preservation and advocates for regionally differentiated conservation policies. The findings provide a robust scientific foundation for enhancing spatial planning

guiding ecological restoration initiatives

and facilitating sustainable forest management practices across subtropical China in an era of rapid global change.

关键词

Keywords

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