Paper
26 July 2007 Wetland change in the rapidly urbanizing area: take Nanjing as an example
Lianyi Zhou, Nan Jiang, Mo Zhao, Shen Wang, Xin Liu
Author Affiliations +
Abstract
The degradation and loss of the regional wetland of urbanization is a more and more concerned question in the whole world. This paper takes Nanjing as an example, adopting five Nanjing area Landsat MSS and TM data: 1979, 1986, 1996, 2000, 2004, combining historical data, land use and field observation, adopting decision tree method to extract Nanjing wetland. We analyze time and space changed characteristic of Nanjing wetland. The result shows: in 1979-2004, the wetlands of Nanjing changed obviously on the time and space. The total amount drops to 363.66 km2 from 397.91 km2, reduce 34.25km2 together. The delta wetland has little change, but it is the largest in proportion of all kinds of Nanjing wetland by 2004. The river wetland in the rural is the greatest one that has changed in every wetland type. In suburban areas, lake and river wetland change frequently because of urban spawl. The wetland area of lake has little change in the urban, but more suburban wetland transferred to urban wetland so the amount of increase in 2000-2004 are greater than 1979-2000. Every stage, there are some Nanjing wetland (except the delta) to transfer to urban construction land and so loss. In the space change characteristic, the rural wetland is continuously substituted by the suburban and urban wetland. It is usually the main area where wetlands are interfered with around new urban area and communication lines. The wetlands are usually interfered by noise, rubbish, and pollution. We should include the development of population and traffic system in the wetland change predicting in future planning. So can we meet wetland management's demands more effectively.
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Lianyi Zhou, Nan Jiang, Mo Zhao, Shen Wang, and Xin Liu "Wetland change in the rapidly urbanizing area: take Nanjing as an example", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67522O (26 July 2007); https://doi.org/10.1117/12.760784
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KEYWORDS
Earth observing sensors

Landsat

Remote sensing

Image classification

Image processing

Ecology

Ecosystems

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