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author:

Xue, Mei (Xue, Mei.) [1] | Chen, YunZhi (Chen, YunZhi.) [2] (Scholars:陈芸芝) | Tian, Xin (Tian, Xin.) [3] | Yan, Min (Yan, Min.) [4] | Zhang, ZhaoPeng (Zhang, ZhaoPeng.) [5]

Indexed by:

EI Scopus

Abstract:

Monitoring the marine aquaculture plays an important role in the management of marine fisheries, and also provides a valid method to evaluate the expansion intensity of the mariculture. In this context, different periods (2003, 2005, 2008, 2011, 2013, 2014 and 2016) of Landsat satellite data were collected and supervised classification method support vector machine (SVM) method was applied to extracted marine aquaculture in the Sansha Bay. Finally, different expansion indicators were used to evaluate the expansion intensity of mariculture in the study area. The results showed that: (1) the area of cage and algae culture increased rapidly, with the annual rates of expansion in 2.2×104 km2 and 9.3×104 km2 respectively from 2003 to 2016; (2) The total marine aquaculture reached 160×104 km2 in 2016, more than 21.2% of the planned mariculture; (3) Cage culture expanded from the coast of mainland and island to the deep sea, but the algae culture expanded more obviously and almost covered the sea, and the expansion intensity of cage and algae culture varied greatly at different periods. © 2018 IEEE.

Keyword:

Algae Aquaculture Geology Marine biology Monitoring Remote sensing Support vector machines

Community:

  • [ 1 ] [Xue, Mei]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry Education, Fuzhou University, Gongye Road 525, Fuzhou; 350002, China
  • [ 2 ] [Xue, Mei]Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Yiheyuanhou, Beijing; 100091, China
  • [ 3 ] [Chen, YunZhi]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry Education, Fuzhou University, Gongye Road 525, Fuzhou; 350002, China
  • [ 4 ] [Tian, Xin]Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Yiheyuanhou, Beijing; 100091, China
  • [ 5 ] [Yan, Min]Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Yiheyuanhou, Beijing; 100091, China
  • [ 6 ] [Zhang, ZhaoPeng]Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Yiheyuanhou, Beijing; 100091, China

Reprint 's Address:

  • 陈芸芝

    [chen, yunzhi]key laboratory of spatial data mining and information sharing of ministry education, fuzhou university, gongye road 525, fuzhou; 350002, china

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Year: 2018

Volume: 2018-July

Page: 7866-7869

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 10

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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