Comparative analysis of wetland landscape pattern in Tumen River Estuary of China, DPR Korea and Russia based on Chinese high resolution images

doi:10.3969/j.issn.1001-909X.2017.02.009

Abstract

Abstract: Tumen River is one of the most important international rivers in China. Because of the differences in the policy, economy and culture, there are many differences in the wetland landscape among Chinese, Russian and DPR Korean wetlands in Tumen River Estuary. Taking GF-1 and GF-2 images as the data sources and according to the wetland classification of national standard, the classification system of wetlands in Tumen River Estuary was set up, which included lake, river, marsh, tidal flat, pit, paddy field and reservoir. The Tumen River Estuary wetland information was extracted by visual interpretation, and then the status and differences among Chinese, Russian and DPR Korean wetlands were analyzed. By the means of Fragstats software, the landscape pattern indexes, such as NP, LPI, MPS, SHAPE, FRAC, SHDI and SHEI were used to analyze the characteristics of wetland landscape pattern in Tumen River Estuary. The results show:(1)The total area of wetlands in the study area is 39 503.38 hm², which is dominated by marsh and lake, and is presented as an aggregate distribution pattern close to the Japan Sea.(2)The wetland area of Russia is the largest, followed by those of DPR Korea and China. The disturbance is serious in that of DPR Korea.(3)The landscape fragmentation of wetland in DPR Korea is most serious, followed by those of China and Russia. Because of the serious development of paddy field, the landscape regulation degree is highest in DPR Korean wetland. The diversity of Chinese wetland is more abundant than those of other countries.

Key words: Tumen River Estuary wetland, remote sensing monitoring, comparative analysis, GF remote sensing image

CLC Number:

WU Chun-guo, LI xiao-min , JIA Yuan-xu, MA Yi, ZHU Wei-hong. Comparative analysis of wetland landscape pattern in Tumen River Estuary of China, DPR Korea and Russia based on Chinese high resolution images[J]. Journal of Marine Sciences, 2017, 35(2): 82-90.

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