Temporal-spatial variations and driving factors analysis of coastal reclamation in China. (15th May 2017)

• Record Type: Journal Article
• Authors: Meng, Weiqing; Hu, Beibei; He, Mengxuan; Liu, Baiqiao; Mo, Xunqiang; Li, Hongyuan; Wang, Zhongliang; Zhang, Yu
• Is Part Of: Estuarine, coastal and shelf science. Volume 191(2017)
• Page Start: 39
• Page End: 49
• Publication Date: 2017-05-15
• Subjects: Coastal reclamation -- Coastal wetlands -- Driving factors -- Coastal management -- China; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2017.04.008
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: Coastal reclamation is the gain of land from the sea or coastal wetlands for agricultural purposes, industrial use or port expansions. Large-scale coastal land reclamation can have adverse effects on the coastal environment, including loss of marine habitats and deterioration of coastal water quality. In recent decades, coastal land reclamation has occurred extensively to meet the increasing needs of rapid economic development and urbanization in China. The overall objective of this study is to understand the coastal reclamation status of China from 1979 to 2014 and analyzed its driving factors for mitigating negative ecological effects. The data of coastal reclamation were done with the ERDAS Imagine V9.2 platform and ArcGIS software based on remote images including Landsat, SPOT, ZY-2 and ZY-3. Potential driving factors for sea reclamation were selected based on statistics bulletins and the knowledge of experts in coastal management. In order to understand the relationships among possible impact factors and coastal reclamation, the Partial Least-Squares Regression models was constructed. The analysis results indicated that the total area of reclamation was 11162.89 km 2 based on remote sensing images between 1979 and 2014. Shandong Province is the largest reclamation area, reaching 2736.54 km 2, and the reclamation is mainly concentrated in Zhejiang, Jiangsu and Liaoning, where the reclamation areas were all more than 1000 km 2 . According to the remote sensing images, there are three coastal reclamation hotspot regions including Bohai bay (in which is located Liaoning, Tianjin and Hebei), Jiangsu province coastal area and Hangzhou bay (in Zhejiang province). A large scale land reclamation plan of more than 5880 km 2 has been made by local government and 2469 km 2 has approved by the State Council. From the analyzed results, there is a significant collinearity between these indicators, and no significant correlation between the area of reclamation and selected indicators. Economic development and employees in marine industries have weak positive correlation and correspondingly, the area of cultivated land (ACL) had a negative correlation. Because of the weak correlation, there is an assumption that economic development, outcome of coastal reclamation and population growth were not only was the direct driving factor, but also the outcome of coastal reclamation and population growth was not the direct driving indicator. Construction land quota and huge economic returns to local government may be the direct driving factors according to our field investigation. To resolve the contradiction between the need for land and coastal wetland conservation, it is recommended that China should establish a special management agency and coordination mechanisms, reconsidered the implementation of the reclamation plans and projects that have been approved, enhance law enforcement and increase penalties and strengthen public participation in reclamation management. Highlights: The total area of reclamation between 1979 and 2014 was 11162.89 km 2 . A large scale land reclamation plan of more than 2469 km 2 has been approved. Economic development not only was the direct driving factor, but also the outcome of the coastal reclamation. Population growth was not the direct driving indicator. Construction land quotas and huge economic returns may be the direct driving factors.