20190315
Author :
Chongfeng Gonga, Shixiao Yua, Heather Joesting, Jiquan Chen
Chongfeng Gonga, Shixiao Yua, Heather Joesting, Jiquan Chen
Title : Determining socioeconomic drivers of urban forest fragmentation
with historical remote sensing images
Journal : Landscape and Urban Planning
Comment :
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.
They found that the forest in Shen-zhen 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.
Comment :
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.
They found that the forest in Shen-zhen 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.
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