Spatiotemporal changes of coastal land use land cover and its drivers in Shanghai, China between 1989 and 2015

OCEAN & COASTAL MANAGEMENT(2023)

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摘要
The coastal zone, an ecotone that provides vital diverse ecosystem services, is one of the most ecologically fragile and sensitive areas on the Earth. It has been strongly influenced by human activities and climate change. Thus, understanding the spatiotemporal changes of land use land cover in the coast is an essential prerequisite for the comprehensive evaluation of coastal ecosystems and the promotion of sustainable development. This study investigated the spatial and temporal changes of land use land cover in the coastal zone of mainland Shanghai by using high spatial resolution aerial images, and the associated driving factors obtained from statistical yearbooks between 1989 and 2015. Our results show that the total land area in the coastal zone exhibited an increasing trend at an annual rate of 7.6% on average. The coastal urban land use also experienced substantial increases, with the degree of urban expansion reaching 42.1% in 2015. The coastal urbanization was at the cost of natural and semi-natural lands. Nearly 64.4% of agricultural land, 24.4% of ocean area within the buffer, 84.9% of fresh water, and 92.8% of the tidal flat had been converted to urban land during 1989–2015. The gradient analysis of land use land cover change along the north-to-south coastal line revealed the spatiotemporal patterns of total land, urbanization degree, and natural and semi-natural lands. The majority of the socioeconomic factors influenced land use land cover change in the coastal zone, positively contributing to the increase of public facilities’ use of land, but negatively affecting the freshwater areas. These findings can provide insights for decision-making in the future for coastal land use land cover planning and management in Shanghai.
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关键词
Coastal zone,Socioeconomic factors,Urbanization,Spatiotemporal pattern,Gradient analysis,Partial least square regression,Canonical correlation analysis
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