Determining Socioeconomic Drivers of Urban Forest Fragmentation with Historical Remote Sensing Images
Document Type
Article
Publication Date
9-1-2013
Department
Coastal Sciences, Gulf Coast Research Laboratory
Abstract
Urban forests are valuable resources in coupled human and natural urban systems where green spaces are essential in maintaining ecological benefits and services of the landscape. In southern coastal China, the Shenzhen Special Economic Zone (SEZ) was established as a new city in 1979 and developed to be a megacity from an agriculture-dominated landscape. To quantify the land-use change during this rapid urbanization process and explore the underline drivers, nine sets of Landsat images from 1973 through 2005 were used to calculate the landscape metrics of forest patches. We found that the forest in Shenzhen SEZ had been restored to 85.85% of pre-urbanization coverage by 2005, but was characterized with smaller, isolated patches across the landscape. The changes in patch density, distribution, and shape during the 30-year study period were nonlinear and defined by episodic periods. The stepwise multiple regression models with socioeconomic drivers provided further explanation for fragmentation rates in patch density, distribution, and shape, with modeled R-squared of 0.837, 0.759, and 0.985 and P-values of 0.011, 0.035, and 0.004, respectively. Among the drivers, urban structure change, industry-related economic booming, and the increase of migrant resident population triggered the urban forest fragmentation while the significantly increased income of city residents drove the de-fragmentation trend. The artificial forestation showed some but a limited role in mitigating forest fragmentation. (C) 2013 Elsevier B.V. All rights reserved.
Publication Title
Landscape and Urban Planning
Volume
117
First Page
57
Last Page
65
Recommended Citation
Gong, C.,
Yu, S.,
Joesting, H.,
Chen, J.
(2013). Determining Socioeconomic Drivers of Urban Forest Fragmentation with Historical Remote Sensing Images. Landscape and Urban Planning, 117, 57-65.
Available at: https://aquila.usm.edu/fac_pubs/7783