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粤港澳大湾区人类流动活动对植被变化的非线性影响。

The Nonlinear Impact of Mobile Human Activities on Vegetation Change in the Guangdong-Hong Kong-Macao Greater Bay Area.

机构信息

Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China.

MNR Technology Innovation Center of Territorial & Spatial Big Data, MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Guangdong Key Laboratory of Urban Informatics, Shenzhen 518060, China.

出版信息

Int J Environ Res Public Health. 2023 Jan 19;20(3):1874. doi: 10.3390/ijerph20031874.

Abstract

Vegetation is essential for ecosystem function and sustainable urban development. In the context of urbanization, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), as the typical urban-dominated region, has experienced a remarkable increase in social and economic activities. Their impact on vegetation is of great significance but unclear, as interannual flow data and linear methods have limitations. Therefore, in this study, we used human and vehicle flow data to build and simulate the indices of mobile human activity. In addition, we used partial least squares regression (PLSR), random forest (RF), and geographical detector (GD) models to analyze the impact of mobile human activities on vegetation change. The results showed that indices of mobile human and vehicle flow increased by 1.43 and 7.68 times from 2000 to 2019 in the GBA, respectively. Simultaneously, vegetation increased by approximately 64%, whereas vegetation decreased mainly in the urban areas of the GBA. Vegetation change had no significant linear correlation with mobile human activities, exhibiting a regression coefficient below 0.1 and a weight of coefficients of PLSR less than 40 between vegetation change and all the factors of human activities. However, a more significant nonlinear relationship between vegetation change and driving factors were obtained. In the RF regression model, vegetation decrease was significantly affected by mobile human activity of vehicle flow, with an importance score of 108.11. From the GD method, vegetation decrease was found to mainly interact with indices of mobile human and vehicle inflow, and the highest interaction force was 0.82. These results may support the attainment of sustainable social-ecological systems and global environmental change.

摘要

植被对生态系统功能和可持续城市发展至关重要。在城市化背景下,粤港澳大湾区(GBA)作为典型的城市主导地区,社会经济活动显著增加。这些活动对植被的影响非常重要,但目前尚不清楚,因为年际流量数据和线性方法存在局限性。因此,在本研究中,我们使用人流和车流数据来构建和模拟移动人类活动指数。此外,我们使用偏最小二乘回归(PLSR)、随机森林(RF)和地理探测器(GD)模型来分析移动人类活动对植被变化的影响。结果表明,2000 年至 2019 年期间,GBA 的移动人流和车流指数分别增加了 1.43 倍和 7.68 倍。同时,植被增加了约 64%,而植被减少主要发生在 GBA 的城区。植被变化与移动人类活动之间没有显著的线性相关关系,PLSR 模型中植被变化与所有人类活动因素之间的回归系数低于 0.1,系数权重小于 40。然而,植被变化与驱动因素之间存在更为显著的非线性关系。在 RF 回归模型中,植被减少与车流的移动人类活动显著相关,重要性评分为 108.11。从 GD 方法来看,植被减少主要与移动的人流和车流流入指数相互作用,相互作用力最高为 0.82。这些结果可能支持实现可持续的社会-生态系统和全球环境变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5345/9914965/64d589f8153a/ijerph-20-01874-g001.jpg

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