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Evaluating the Effectiveness of Conservation on Mangroves: A Remote Sensing-Based Comparison for Two Adjacent Protected Areas in Shenzhen and Hong Kong, China

M. Jia,Mingyue Liu,Zongming Wang,Dehua Mao,C. Ren,H. Cui

Published 2016 in Remote Sensing

ABSTRACT

Mangroves are ecologically important ecosystems and globally protected. The purpose of this study was to evaluate the effectiveness of mangrove conservation efforts in two adjacent protected areas in China that were under the management policies of the Ramsar Convention (Mai Po Marshes Nature Reserve (MPMNR), Hong Kong) and China’s National Nature Reserve System (Futian Mangrove National Nature Reserve (FMNNR), Shenzhen). To achieve this goal, eleven Landsat images were chosen and classified, areal extent and landscape metrics were then calculated. The results showed that: from 1973–2015, the areal extent of mangroves in both reserves increased, but the net change for the MPMNR (281.43 hm2) was much higher than those of the FMNNR (101.97 hm2). In general, the area-weighted centroid of the mangroves in FMNNR moved seaward by approximately 120 m, whereas in the MPMNR, the centroid moved seaward even farther (410 m). Although both reserves saw increased integrality and connectivity of the mangrove patches, the patches in the MPMNR always had higher integrality than those in the FMNNR. We concluded that the mangroves in the MPMNR were more effectively protected than those in the FMNNR. This study may provide assistance to the formulation of generally accepted criteria for remote sensing-based evaluation of conservation effectiveness, and may facilitate the development of appropriate mangrove forest conservation and management strategies in other counties.

PUBLICATION RECORD

  • Publication year

    2016

  • Venue

    Remote Sensing

  • Publication date

    2016-07-29

  • Fields of study

    Geography, Computer Science, Environmental Science

  • Identifiers
    DOI 10.3390/rs8080627
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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