Study on spatial distribution characteristics of islandsin Guangdong-Hong Kong-Macao Greater Bay Area

doi:10.3969/j.issn.1001-909X.2020.02.008

Abstract

Abstract: The island is one of the core contents of the value of marine resources development and utilization. In order to reasonably develop, utilize and protect island resources in Guangdong-Hong Kong-Macao Greater Bay Area and optimize the industry structures and arrangement on islands, from the perspective of the spatial distribution of island resources, the role of islands in the development of the key platforms in Guangdong-Hong Kong-Macao Greater Bay Area was explored. The spatial distribution characteristics of islands in Guangdong-Hong Kong-Macao Greater Bay Area were investigated by application of ArcGIS software platform, Nuclear Density Estimation Method, Lorenz Curve and Gini Coefficient calculation based on the statistical data of 850 islands coordinates and land areas, which have been listed in the China Seas Island Standards Directory. The results show that the distribution type of islands in Guangdong-Hong Kong-Macao Greater Bay Area tends to be concentrated and presents the overall band distribution, the characteristics of local group distribution in space. The islands in Guangdong-Hong Kong-Macao Greater Bay Area have shaped the western part of the bay area and 4 obvious gathering areas,Including Dapeng Bay-Daya Bay Area, Kyushu Islands Area, Wanshan-Jia Peng Islands Area, Chuanshan Islands Area. The islands in Guangdong-Hong Kong-Macao Greater Bay Area are mainly coastal islands and the area distribution of islands is characterized by an imbalance, with a Gini coefficient of 0.58.

Key words: Guangdong-Hong Kong-Macao Greater Bay Area, island, spatial distribution, Kernel Density Estimation, Average Nearest Neighbor, Gini Coefficient

CLC Number:

TANG Ling, YANG Muzhuang, WANG Yinxia, GAO Yang, TIAN Song, DONG Di. Study on spatial distribution characteristics of islandsin Guangdong-Hong Kong-Macao Greater Bay Area[J]. Journal of Marine Sciences, 2020, 38(2): 74-80.

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