We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Spatial Distribution and Differentiation Analysis of Coastal Aquaculture in China Based on Remote Sensing Monitoring.
- Authors
Meng, Dan; Yang, Xiaomei; Wang, Zhihua; Liu, Yueming; Zhang, Junyao; Liu, Xiaoliang; Liu, Bin
- Abstract
Multiple datasets related to pond and marine aquaculture have been published using diverse remote sensing technologies, yet a comprehensive dataset detailing spatial distribution on both land and sea sides is lacking. Firstly, a meticulous comparison of datasets which we selected related to aquaculture ponds and marine, ensuring consistency in trends. Subsequently, the datasets published by our team were edited and integrated to illustrate aquaculture activities on both sides of China's coastal zone. Finally, a spatial differentiation of coastal aquaculture in major provinces was analyzed. This analysis also utilizes the types of coastline and statistical data, guiding coordinated resource management efforts. The results unveil a distinctive spatial distribution pattern, concentrating aquaculture in the northern regions—Bohai Sea, Jiangsu, Fujian, and Pearl River coasts in Guangdong. The provinces rich in aquaculture resources, such as Shandong, Guangdong, and Liaoning, exhibit extensive coastlines. However, remote sensing monitoring suggests an underestimation of Liaoning's marine aquaculture compared to statistical yearbook data. Furthermore, southern provinces like Guangdong and Fujian exhibit significantly higher aquaculture output than Liaoning. Zhejiang leads in fishing output. The paper outlines the future development direction of coastal aquaculture, emphasizing a strategic, integrated land–sea approach for sustainable development.
- Subjects
LIAONING Sheng (China); GUANGDONG Sheng (China); FUJIAN Sheng (China); INTEGRATED coastal zone management; REMOTE sensing; AQUACULTURE; MARICULTURE; COASTS; SUSTAINABLE development; COASTAL development
- Publication
Remote Sensing, 2024, Vol 16, Issue 9, p1585
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs16091585