Description

Understanding the state of wetland ecosystems and their changes at the national and local levels is critical for wetland conservation, management, decision-making, and policy development practices. This study analyzed the wetlands in Shanghai, a province-level city, using remote sensing, image processing, and geographic information systems (GIS) techniques based on the Chinese national wetland inventory procedure and standards. FORMOSAT imagery acquired in 2012 and Navy nautical charts of the Yangtze estuarine area were used in conjunction with object-oriented segmentation, expert interpretation, and field validation to determine wetland status. Landsat imagery from 1985, 1995, 2000, 2003 and 2013 as well as social-economic data collected from 1985 to 2013 were used to further assess wetland changes. In 2013, Shanghai contained 376970.6 ha of wetlands, and 78.8% of all wetlands were in marine or estuarine systems. Estuarine waters comprised the single largest wetland category. Between the first national wetland inventory in 2003 and the second national wetland inventory in 2013, Shanghai lost 50519.1 ha of wetlands, amounting to a mean annual loss rate of 1.2% or an 11.8% loss over the decade. Declines were proportionately higher in marine and estuarine wetlands, with an annual loss of 1.8%, while there was a sharp increase of 1882.6% in constructed water storage areas for human uses. Diking, filling, impoundment and reclamation, which are all attributable to the economic development and urbanization associated with population increases, were the major factors that explained the gain and loss of wetlands. Additional factors affecting wetland losses and gains include sediment trapping by the hydropower system, which reduces supply to the estuary and erodes wetlands, and sediment trapping by the jetties, spur dikes, and diversion bulwark associated with a navigation channel deepening project, which has the converse effect, increasing saltmarsh wetland area at Jiuduansha shoal by three times between 2000 and 2013.

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