Extraction and pattern analysis of dike-pond based on Gaofen-2 satellite image

doi:10.14088/j.cnki.issn0439-8114.2023.06.029

Abstract

Abstract: For the purpose of analyzing the dike-pond pattern in Guangdong-Hong Kong-Macao Greater Bay Area, the rule-based classification method to extract the dike-pond from GF-2 satellite image was used. Then the dike-pond pattern was measured through Weighted Aggregation and Closeness （WAC） metric. The results showed that the overall accuracy of extraction was 92.25% by sample point test, and 80.25% by sample region test. The sample region test could capture the difference in different dike-pond types, and was more suitable than the sample point test to assess the accuracy of high-resolution images classification. The extraction result showed that there were 14.06 km² dike-ponds in Longjiang Town. Among them regular ponds accounted for 58.46%, mainly distributed in the central and northern parts of the town. Their pattern exhibited compactness, which was convenient for expanding aquaculture and then increasing income. Irregular ponds accounted for 41.54%, mainly distributed in the eastern and western parts of the town. Their pattern was less compact, which was conducive to planting and promoted water-land interaction.

Key words: dike-pond, object-oriented classification, Gaofen-2, spatial pattern

CLC Number:

P237

JIANG Hai-tao, ZHOU Jin-hao, LI Xin-ru, LIN Jing-hua, HUANG Shao-fang, LIU Hou-hai, ZHONG Zhi-yi. Extraction and pattern analysis of dike-pond based on Gaofen-2 satellite image[J]. HUBEI AGRICULTURAL SCIENCES, 2023, 62(6): 157-162.

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