Detection of the impervious surfaces expansion using SPOT-5 and Sentinel-2 data: a case study in Ho Chi Minh city

http://jmes.humg.edu.vn/en/archives?article=913
  • Affiliations:

    1 Trường Đại học Tài nguyên và Môi trường Thành phố Hồ Chí Minh, Việt Nam;
    2 Khoa Trắc địa - Bản đồ và Quản lý đất đai, Trường Đại học Mỏ - Địa chất, Việt Nam;
    3 Trường Đại học Đồng Tháp, Việt Nam;
    4 Sở Tài Nguyên và Môi Trường Tỉnh Thái Bình, Việt Nam

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  • Received: 25th-Feb-2018
  • Revised: 3rd-Apr-2018
  • Accepted: 27th-Apr-2018
  • Online: 27th-Apr-2018
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Abstract:

Ho Chi Minh city is known as a quick urbanization area of Vietnam. Meanwhile, impervious surfaces to be known as the key to identify the urbanization and urban sustainable development as well as planning of natural resources. Using satellite data for detecting the impervious surfaces expansion is effective mothod and assurance of reliability for large areas. In this study, temporal SPOT-5 and Sentinel- 2 data acquired in 2002, 2009 and 2016 were classified for four classes including open water, vegetation, barren and impervious surface area using KNN classifier algorithm by eCognition software. Results of the study showed that information of the impervious surfaces can determine the urban area expansion. In particular, the impervious surfaces area of Ho chi Minh City, Vietnam increased rapidly between 2002 and 2016. The results showed that 2615.86 ha (36.88%) of total vegetation area was converted to impervious surfaces area. The extraction of the impervious surfaces using remote sensing data is to provide valuable information to the local city planners for understanding the impacts of urban planning policy to urban sustainable development

How to Cite
Pham, T.Van, Nguyen, T.Van, Nguyen, L.Huu and Nguyen, H.Duc 2018. Detection of the impervious surfaces expansion using SPOT-5 and Sentinel-2 data: a case study in Ho Chi Minh city (in Vietnamese). Journal of Mining and Earth Sciences. 59, 2 (Apr, 2018).