Shoreline mapping with cellular automata and the shoreline progradation analysis in Shanghai, China from 1979 to 2008
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ORIGINAL PAPER
Shoreline mapping with cellular automata and the shoreline progradation analysis in Shanghai, China from 1979 to 2008 Yongjiu Feng & Yan Liu & Dan Liu
Received: 21 August 2013 / Accepted: 23 June 2014 # Saudi Society for Geosciences 2014
Abstract This paper presents a cellular automata (CA) algorithm to extract shorelines from remote sensing images by analysing the edge directional information of the images. Using this algorithm, the tide-coordinated shorelines along the entire coast in Shanghai Municipality of China were extracted and analysed using the multi-temporal Landsat TM images from 1979 to 2008. The shorelines of four sub-regions, including the mainland and three islands (Changxing, Hengsha and Chongming) were analysed along with six areas experiencing drastic shoreline changes. The results show a total progradation of 551.7 km2 along the coastal area of Shanghai over the past 30 years, due to both long-term sediment deposition and short-term land reclamation. Furthermore, both horizontal and vertical displacements along the shorelines were identified. Fractal analyses between the length of the shorelines and the spatial resolution of the images achieved goodness-of-fit (R2) values above 0.6 for the shorelines of the entire Shanghai as well as for each of the four subregions, indicating that the relationship between the length of the shorelines and the spatial resolution of the images accord with the power laws. The fractal dimension values indicate that the shorelines of both Changxing and Chongming Islands were getting regular. The paper also demonstrates that the CA-based shoreline extractor can detect Y. Feng : D. Liu College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China Y. Feng The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources (Shanghai Ocean University), Ministry of Education, Shanghai 201306, China Y. Liu (*) School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane QLD 4072, Australia e-mail: [email protected]
shoreline information of both artificial and muddy coasts from remote sensing images. The shoreline extraction and change analysis tool is valuable not only for shoreline mapping but also for comprehensive coastal management. Keywords Shoreline mapping . Shoreline progradation . Remote sensing . Cellular automata . Fractal . Shanghai
Introduction The coastal zone is the transitional band area between land and sea. Although this area occupies less than 15 % of the Earth’s land surface, it accommodates more than 60 % of the world’s population (Delhez and Barth 2011). Moreover, most of the social and economic activities around the world are carried out within the coastal zone with high intensity of land development (Paterson et al. 2010). The intensive development within the coastal zone has induced an increasing number of ecological and environmental problems, which have drawn much attention by coastal managers, policy makers, academic communities and the public (Liu et al. 2010; Sy
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