Remote sensing and GIS-based analysis of urban dynamics and modelling of its drivers, the case of Pingtan, China

Environment, Development and Sustainability(2018)

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摘要
Understanding the urban land dynamics and its causes is critical to manage and predict both urban development and its associated environmental qualities. However, little is known and documented about the historical urban land dynamics in Pingtan. By integrating remote sensing, geographic information systems and statistical analysis, this study aims to quantify and map the spatiotemporal urban dynamics using Landsat imageries in four timespans (1984, 1996, 2007 and 2017) along with driving factors. It specifically addressed urban expansion intensity, forms of expansion, transitions, nature of landscape and modelled socioeconomic drivers. The results revealed that urban land expanded by 18.19% (57.55 km 2 ) during 1984–2017 and its intensity of expansion was rapid (≥ 0.5). The expanded area was mainly originated from farmland (70.3%) followed by shrub land, water bodies and grassland (21.8% altogether). Metrics of urban landscape revealed a continuous increase in shape irregularity and size variability among patches. The level of fragmentation also increased from 1984 to 2007. However, from 2007 onward, patches’ aggregation started to prevail. Urban expansion was significantly driven by socioeconomic factors (variable importance in the projection > 1) like urban population, GDP from different sectors, income and road constructions. Policies of economic development and spatial planning laws also affected urban expansion. Although urban densification showed an upward trend, urban expansion was dominant. Leapfrog and edge expansion together accounts > 80% of newly expanded urban areas. Hence, a big challenge in the future will be how to limit urban expansion, promote its densification and manage associated environmental impacts sustainably in the face of dynamic socioeconomic and policy factors.
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关键词
Urban expansion,Density,Transitions,Landscape,PLSR model
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