Abstract
Ecological degradation caused by rapid urbanisation has presented great challenges in southern China. Fractional vegetation cover (FVC) has long been the most common and sensitive index to describe vegetation growth and to monitor vegetation degradation. However, most of the studies have failed to adequately explore the complexity of the relationship between fractional vegetation cover (FVC) and impact factors. In this research, we first constructed a Semi-parametric Geographically Weighted Regression (SGWR) model to analyse both the stationary and nonstationary spatial relationships between FVC and driving factors in Guangdong province in southern China on a county level. Then, climate, topographic, land cover, and socio-economic factors were introduced into the model to distinguish impacts on FVC from 2000–2015. Results suggest that the positive and negative effects of rainfall and elevation coefficients alternated, and local urban land and population estimates indicated a negative association between FVC and the modelled factors in each period. The SGWR FVC make significantly improves performance of the geographically weighted regression and ordinary least squares models, with adjusted R2 higher than 0.78. The findings of this research demonstrated that, although urbanisation in the Pearl River Delta in Guangdong has encroached on the regional vegetation cover, the total vegetation area remained unchanged with the implementation of protection policies and regulations.
Highlights
Vegetation plays an important role in the energy balance and water cycle and biochemical cycles in global climate change studies [1]
The increasing by economic develvoegpemtatieonntc.ovTerhagee lion wFosFhaVnCshoinwsZthheughreaatiimrepfloretacntcse tahttaechleadrgbyetnheugmovberenmr eonft itosluarnbadn s in the prefecture and the persistentgnreeengiangtiavned veengevtaitrioonnpmroteecntitoan;lthaengdreeencinogleoffgecitcaalsloereffmeecdtiasteos feceolcoogincaol mandicendvierovnemleonpt ment in the Pearl damage caused by economic development
Significance is defined using the adjusted critical t value equated with an original significance level of 0.05, which addresses the issue of multiple hypothesis testing and multiple testing issue in Geographically Weighted Regression (GWR) [36,37]
Summary
Vegetation plays an important role in the energy balance and water cycle and biochemical cycles in global climate change studies [1]. Numerous studies demonstrate that vegetation information provides detailed information on global change and has important practical significance for the analysis and evaluation of the regional ecological environment [2,3,4]. Knowledge of associated driving factors helps optimise ecological layout and restoration. Socio-economic factors significantly impact FVC and primarily include the destruction of the regional ecological environment and deforestation caused by population growth and economic poverty, and the increase of FVC because of the Grain for Green policy [17,18]. To better understand the regional FVC with different factors, bivariate-partial correlation analysis and piecewise linear regression were applied to the exploring the relationship between FVC with various climatic and human-induced factors [19]. The principal drivers of FVC in Guangdong remain undetermined
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