Land cover and land use change related to shrimp farming in coastal areas of Quang Ninh, Vietnam using remotely sensed data

被引:0
|
作者
Thuyet D. Bui
Stefan W. Maier
Chris M. Austin
机构
[1] Charles Darwin University,Research Institute for the Environment and Livelihoods
[2] Monash University,School of Science
[3] Research Institute for Aquaculture No.1,Center for Environment and Disease Monitoring in Aquaculture
来源
关键词
Mangrove; Shrimp farm; Land cover; Land use; Landsat ETM+; ALOS AVNIR-2;
D O I
暂无
中图分类号
学科分类号
摘要
Rapid development of shrimp farming may lead to unrecognized and undesirable changes of land cover/land use patterns in coastal areas. Of special concern is the loss of mangrove forest in coastal areas such as Quang Ninh, Vietnam, which is adjacent to the World Heritage-listed Ha Long Bay. Understanding the status and changes of land cover/land use for coastal shrimp farms and mangrove forests can support environmental protection and decision-making for sustainable development in coastal areas. Within this context, this paper uses the 1999/2001 Landsat ETM+ and the 2008 ALOS AVNIR-2 imagery to investigate the contraction and expansion of shrimp farms and mangrove forests in coastal areas of Ha Long and Mong Cai, which now have a high concentration of intensive and semi-intensive shrimp farms. Images were separately analyzed and classified before using post-classification comparisons to detect land cover/land use changes in the study area. The results of this study found that the area of mangrove forest has been reduced by an estimated 927.5 ha in Ha Long and 1,144.4 ha in Mong Cai, while shrimp farming areas increased by an estimated 1,195.9 and 1,702.5 ha, respectively, over the same period. The majority of shrimp farms in Mong Cai were established at the expense of mangrove forest (49.4 %) while shrimp farms in Ha Long were mainly constructed on areas previously occupied by bare ground (46.5 %) and a significant proportion also replaced mangroves (23.9 %). The remarkable rate of mangrove loss and shrimp farming expansion detected in this study, over a relatively short time scale indicate that greater awareness of environmental impacts of shrimp farm expansion is required if this industry is to be sustainable, the important estuarine and coastal marine ecosystems are to be protected over the long term, and the capturing and storing of carbon in mangrove systems are to be enhanced for global climate change mitigation and for use as carbon offsets.
引用
收藏
页码:441 / 455
页数:14
相关论文
共 50 条
  • [31] Evaluating the use of publicly available remotely sensed land cover data for areal interpolation
    Lin, Jie
    Cromley, Robert G.
    Civco, Daniel L.
    Hanink, Dean M.
    Zhang, Chuanrong
    GISCIENCE & REMOTE SENSING, 2013, 50 (02) : 212 - 230
  • [32] Using remotely sensed data in Google Earth Engine to investigate water surface temperature at shrimp farms in the climate change context: a case study at Mong Cai City, Quang Ninh Province, Vietnam
    Bui, Thuyet D.
    AQUACULTURE INTERNATIONAL, 2024, 32 (05) : 6273 - 6286
  • [33] Land cover change and multiple remotely sensed datasets consistency in China
    Wang, Hui
    Cai, Liping
    Wen, Xiaojin
    Fan, Donglin
    Wang, Yuejun
    ECOSYSTEM HEALTH AND SUSTAINABILITY, 2022, 8 (01)
  • [34] Land cover pattern optimization for local ecological security using remotely sensed data
    Chen, Yunhao
    Li, Xiaobing
    Shi, Peijun
    Gong, Adu
    Dou, Wen
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2006, 27 (9-10) : 2003 - 2010
  • [35] Automatic land cover analysis for Tenerife by supervised classification using remotely sensed data
    Keuchel, J
    Naumann, S
    Heiler, M
    Siegmund, A
    REMOTE SENSING OF ENVIRONMENT, 2003, 86 (04) : 530 - 541
  • [36] Monitoring land use/cover changes using remotely sensed imagery in Isfahan, Iran
    Nadoushan, Mozhgan Ahmadi
    Abari, Maryam Foroughi
    Radnezhad, Hadi
    Sadeghi, Masoumeh
    INDIAN JOURNAL OF GEO-MARINE SCIENCES, 2017, 46 (03) : 538 - 544
  • [37] Assessment of Machine Learning Algorithms for Land Cover Classification Using Remotely Sensed Data
    Park, Jeongmook
    Lee, Yongkyu
    Lee, Jungsoo
    SENSORS AND MATERIALS, 2021, 33 (11) : 3885 - 3902
  • [38] Soft classifications for the mapping of land cover from remotely sensed data
    Foody, GM
    APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION, 1998, 3455 : 23 - 34
  • [39] Variations in land cover area estimated from remotely sensed data
    Yang, WL
    Merchant, JW
    IGARSS '96 - 1996 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM: REMOTE SENSING FOR A SUSTAINABLE FUTURE, VOLS I - IV, 1996, : 2315 - 2317
  • [40] Remotely sensed vegetation cover in the land data assimilation systems project
    Cosgrove, BA
    Houser, PR
    IGARSS 2001: SCANNING THE PRESENT AND RESOLVING THE FUTURE, VOLS 1-7, PROCEEDINGS, 2001, : 2079 - 2081