Vegetation Cover Pattern in Fujian and Jiangxi Provinces and Its Driving Mechanism Based on Geographically Weighted Regression Model

QI Wen, QIU Bing-wen, FAN Zhan-ling

Journal of Changjiang River Scientific Research Institute ›› 2016, Vol. 33 ›› Issue (12) : 138-143.

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Journal of Changjiang River Scientific Research Institute ›› 2016, Vol. 33 ›› Issue (12) : 138-143. DOI: 10.11988/ckyyb.20150765
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Vegetation Cover Pattern in Fujian and Jiangxi Provinces and Its Driving Mechanism Based on Geographically Weighted Regression Model

  • QI Wen1,2, QIU Bing-wen1,2, FAN Zhan-ling1,2
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Abstract

Researching the pattern of vegetation cover is of great significance for the sustainable development of eco-environment.In this article, the characteristics of vegetation cover pattern and its driving mechanism were investigated and analyzed using geographically weighted regression (GWR) model based on vegetation cover index data of 30m resolution.Fujian Province and Jiangxi Province were selected as study area, and natural and human factors were considered in the analysis. Research results revealed that 1) in Fujian and Jiangxi provinces, topography is a main factor affecting the vegetation cover degree which has the strongest correlation with elevation within the range of [100,300) m and [300,500) m respectively, and weak correlation with slope gradient, above 25 ℃ and 10 ℃ respectively; 2) the correlation between vegetation cover degree and distance from river for the two provinces differ greatly. In Jiangxi Province, the mainstream is surrounded by towns and cropland, while in Fujian Province, the mainstream is surrounded by towns and woodland; 3) the distance to residence at 5 km and 4 km has the weakest correlation with vegetation cover degree in Jiangxi and Fujian, respectively.

Key words

geographically weighted regression model / Fujian and Jiangxi Provinces / vegetation index / natural vegetation cover pattern / driving mechanism

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QI Wen, QIU Bing-wen, FAN Zhan-ling. Vegetation Cover Pattern in Fujian and Jiangxi Provinces and Its Driving Mechanism Based on Geographically Weighted Regression Model[J]. Journal of Changjiang River Scientific Research Institute. 2016, 33(12): 138-143 https://doi.org/10.11988/ckyyb.20150765

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