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广东省沿海城市人工水产养殖基地变化——基于2015—2019年Sentinel-1数据的实证研究
引用本文:黄森文,韦春竹.广东省沿海城市人工水产养殖基地变化——基于2015—2019年Sentinel-1数据的实证研究[J].热带地理,2021,41(3):622-634.
作者姓名:黄森文  韦春竹
作者单位:1.中山大学 测绘科学与技术学院,广东 珠海 519000;2.中山大学 地理科学与规划学院,广州 510275;3.南方海洋科学与工程广东省实验室,广东 珠海 519000
基金项目:广州市基础与应用基础研究项目(202102020592);国家自然科学基金项目(42001178);南方海洋科学与工程广东省实验室(珠海)创新团队建设项目(311021018)
摘    要:基于Google Earth Engine云计算平台以及哨兵1号雷达遥感影像等数据,对广东省14个沿海城市2015—2019年规则的陆上人工水产养殖基地进行面向对象方法提取,并对其空间分布变化趋势、高密度分布区域进行定量分析,对该类规则的水产养殖用地面积与各个城市经济发展之间的关系进行分析。对规则人工水产养殖基地的分类结果显示:基于雷达遥感影像提取水产养殖基地具有较高的精度,总体精度为90.5%,Kappa系数为0.81;分类结果表明:2015—2019年内广东省规则的陆上人工养殖基地总面积呈上升趋势,其中陆地岸线5 km范围内集中了80%的规则人工水产养殖基地,海湾和江河入海口的规则水产养殖用地密度最高、规模最大。对比不同城市间的分布模式亦可发现,汕头、潮州、珠海、中山、深圳、湛江、阳江的水产养殖用地向陆地岸线集中效应最强,汕尾、广州、揭阳、江门次之,茂名、东莞、惠州集中程度最低。总体而言,广东省各个沿海城市的水产养殖用地整体上呈现扩张趋势,规则水产养殖基地面积的增长与水产养殖产值呈现出显著的相关性,这进一步说明了人工水产养殖基地的用地扩张依然是目前广东省提高水产养殖产值的主要途径,这样的扩张趋势给海岸带的湿地、耕地和城市用地的分布和可持续利用带来了极大的挑战。

关 键 词:水产养殖用地  哨兵1号  Google  Earth  Engine  面向对象分类  广东省  
收稿时间:2020-07-13

Spatial-Temporal Changes in Aquaculture Ponds in Coastal Cities of Guangdong Province: An Empirical Study Based on Sentinel-1 Data during 2015-2019
Senwen Huang,Chunzhu Wei.Spatial-Temporal Changes in Aquaculture Ponds in Coastal Cities of Guangdong Province: An Empirical Study Based on Sentinel-1 Data during 2015-2019[J].Tropical Geography,2021,41(3):622-634.
Authors:Senwen Huang  Chunzhu Wei
Institution:1.School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519000, China;2.School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;3.Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), Zhuhai 519000, China
Abstract:Guangdong Province has the largest extent of coastal aquaculture in China. Quantitative analysis of the spatial distribution pattern and evolution trend of on-land artificial aquaculture bases in the coastal areas of Guangdong Province has great significance for exploring the sustainable development approach of freshwater aquaculture in the region. Based on the Google Earth Engine cloud computing platform, Sentinel-1 SAR imagery, and other data, this study extracted the artificial aquaculture bases of the 14 coastal cities in Guangdong Province from 2015 to 2019 using an object-oriented method, implemented quantitative analysis on its spatial distribution trend and high-density distribution area, and analyzed the relationship between these aquaculture bases and city economic growth. The classification results of the regular artificial aquaculture bases in this study showed that the extraction of aquaculture bases based on radar remote sensing imagery had high accuracy, with an overall accuracy of 90.5% and a kappa coefficient of 0.81. The results also showed that the total area of artificially regulated aquaculture bases in Guangdong Province had an upward trend from 2015 to 2019, with a net increase of 163.1 km2. The three cities with the largest net area growth were Jiangmen, Zhongshan, and Guangzhou. Using a grid with 1 km resolution to study the density dynamics, the density of aquaculture land in most areas was found to have increased, especially in high-density areas. Among these, 80% of the artificial aquaculture bases were concentrated within 5 km of the coastline, and the bays and river inlets had the highest densities and largest areas of aquaculture land. A comparison of the distribution patterns among different cities showed that the cities with the most concentrated aquaculture land within the land boundary were Shantou, Chaozhou, Zhuhai, Zhongshan, Shenzhen, Zhanjiang, and Yangjiang, followed by Shanwei, Guangzhou, Jieyang, and Jiangmen, and that Maoming, Dongguan, and Huizhou were the least concentrated. In terms of economy, the proportion of aquaculture industry in the regional GDP declined in more than half of the cities, increased in only Yangjiang, and remained unchanged in the others. In addition to the fact that Guangdong Province's economic development focuses on secondary and tertiary industries, this result may also be related to the government's ongoing ecological restoration actions, which have restricted aquaculture land use. In general, aquaculture land in the coastal cities in Guangdong Province showed an overall trend of expansion. Moreover, the growth in area of regular aquaculture bases showed a significant correlation with the value of aquaculture production, further indicating that land expansion of artificial aquaculture bases continued to be the main method for increasing the value of aquaculture production in Guangdong Province. Such an expansion trend poses a great challenge to the distribution and sustainable use of wetlands, cropland, and urban land in the coastal zone.
Keywords:aquaculture ponds  Sentinel-1  Google Earth Engine  Object-oriented classification  Guangdong Province  
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