Mangrove Mapping and Change Detection in Ca Mau Peninsula, Vietnam, Using Landsat Data and Object-Based Image Analysis

    Authors

    N. T. Son; C. F. Chen; N. B. Chang; C. R. Chen; L. Y. Chang;B. X. Thanh

    Comments

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    Abbreviated Journal Title

    IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens.

    Keywords

    Change analysis; Landsat data; mangroves; object-based image analysis; (OBIA); REMOTE-SENSING TECHNIQUES; CHANGE-VECTOR ANALYSIS; FOREST CHANGE; DETECTION; COVER CHANGE; CENTRAL-AMERICA; SATELLITE DATA; URBAN FRINGE; CLASSIFICATION; SEGMENTATION; VEGETATION; Engineering, Electrical & Electronic; Geography, Physical; Remote; Sensing; Imaging Science & Photographic Technology

    Abstract

    Mangrove forests provide important ecosystem goods and services for human society. Extensive coastal development in many developing countries has converted mangrove forests to other land uses without regard to their ecosystem service values; thus, the ecosystem state of mangrove forests is critical for officials to evaluate sustainable coastal management strategies. The objective of this study is to investigate the multidecadal change in mangrove forests in Ca Mau peninsula, South Vietnam, based on Landsat data from 1979 to 2013. The data were processed through four main steps: 1) data preprocessing; 2) image processing using the object-based image analysis (OBIA); 3) accuracy assessment; and 4) multitemporal change detection and spatial analysis of mangrove forests. The classification maps compared with the ground reference data showed the satisfactory agreement with the overall accuracy higher than 82%. From 1979 to 2013, the area of mangrove forests in the study region had decreased by 74%, mainly due to the boom of local aquaculture industry in the study region. Given that mangrove reforestation and afforestation only contributed about 13.2% during the last three decades, advanced mangrove management strategies are in an acute need for promoting environmental sustainability in the future.

    Journal Title

    Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing

    Volume

    8

    Issue/Number

    2

    Publication Date

    1-1-2015

    Document Type

    Article

    Language

    English

    First Page

    503

    Last Page

    510

    WOS Identifier

    WOS:000352277100007

    ISSN

    1939-1404

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