04. Establishment of the impervious surfaces map using Sentinel-2 data: a case study in Ho Chi Minh City

Tùng Phạm Văn


Ho Chi Minh city is known as a quick urbanization area in Vietnam. Meanwhile, impervious surfaces to be known as the key to identify the urbanization, urban sustainable development as well as planning of natural resources. Using satellite data to create the impervious surface map is an effective method and assurance of reliability for large areas. In this study, temporal Sentinel-2 data acquired in 2021 were classified for four classes including open water, vegetation, barren, and impervious surface area using the KNN classifier algorithm by eCognition software. The accuracy of the classification of land cover and impervious surfaces was evaluated in order to affirms the effectiveness and reliability of the classification method. The area of impervious surfaces in 2021 was compared with those in 2002, 2009 and 2016 to see the expansion of the impervious surface area related to the urbanization of Ho Chi Minh city. Results of this study therefore will support policy makers in developing planning policies for sustainable development of the urban area there.

Full text article

Generated from XML file


[1]. Chester L Arnold Jr, C James Gibbons (1996). Impervious surface coverage: the emergence of a key environmental indicator. Journal of the American planning Association 62, 243.
[2]. Liqin Cao, Pingxiang Li, Liangpei Zhang, Xiong Xu (2012). Estimating impervious surfaces using the fuzzy ARTMAP. Geomatics and Information Science of Wuhan University 37, 1236.
[3]. Russell G Congalton (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote sensing of environment 37, 35.
[4]. Xuefei Hu, Qihao Weng (2011). Impervious surface area extraction from IKONOS imagery using an object-based fuzzy method. Geocarto International 26, 3.
[5]. John R Jensen (1995). Introductory Digital Image Processing: A Remote Sensing Perspective.
[6]. James M Keller, Michael R Gray, James A Givens (1985). A fuzzy k-nearest neighbor algorithm. IEEE transactions on systems, man, and cybernetics, 580.
[7]. Ivan Lizarazo (2010). Fuzzy image regions for estimation of impervious surface areas. Remote Sensing Letters 1, 19.
[8]. Dengsheng Lu, Guiying Li, Wenhui Kuang, Emilio Moran (2014). Methods to extract impervious surface areas from satellite images. International Journal of Digital Earth 7, 93.
[9]. Dengsheng Lu, Emilio Moran, Scott Hetrick (2011). Detection of impervious surface change with multitemporal Landsat images in an urban - rural frontier. ISPRS Journal of Photogrammetry and Remote Sensing 66, 298.
[10]. Dengsheng Lu, Qihao Weng (2004). Spectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM + imagery. Photogrammetric Engineering & Remote Sensing 70, 1053.
[11]. D. Pairman, McNeill, S., and Belliss, S., (2010). Impervious Surface Mapping for the Auckland Region.
[12]. Carmen Quintano, Alfonso Fernández-Manso, Yosio E Shimabukuro, Gabriel Pereira (2012). Spectral unmixing. International Journal of Remote Sensing 33, 5307.
[13]. Thomas Schueler (1994). The importance of imperviousness. Watershed protection techniques 1, 100.
[14]. J Tang, L Wang, SW Myint (2007). Improving urban classification through fuzzy supervised classification and spectral mixture analysis. International Journal of Remote Sensing 28, 4047.
[15]. Phạm Văn Tùng, Nguyễn Văn Trung, Nguyễn Hữu Long, Nguyễn Đức Hùng (2018). Quan trắc sự mở rộng bề mặt không thấm sử dụng dữ liệu ảnh vệ tinh SPOT-5 và Sentinel-2 ở khu vực thành phố Hồ Chí Minh. Tạp chí Khoa học Kỹ thuật Mỏ - Địa chất 59, 69.
[16]. Qihao Weng, Xuefei Hu (2008). Medium spatial resolution satellite imagery for estimating and mapping urban impervious surfaces using LSMA and ANN. IEEE Transactions on Geoscience and Remote Sensing 46, 2397.
[17]. Changshan Wu, Alan T Murray (2003). Estimating impervious surface distribution by spectral mixture analysis. Remote sensing of Environment 84, 493.
[18]. Xinyu Zheng, Zhoulu Yu, Weijiu Ao, Youfu Wang, Amir Reza Tahmassebi, Shucheng You, Jinsong Deng, Ke Wang (2014). Rural impervious surfaces extraction from Landsat 8 imagery and rural impervious surface index. Land Surface Remote Sensing II, International Society for Optics and Photonics, 926030.
[19]. Hongwei Zhu, Otman Basir (2005). An adaptive fuzzy evidential nearest neighbor formulation for classifying remote sensing images. IEEE Transactions on Geoscience and Remote Sensing 43, 1874.


Tùng Phạm Văn
pvtung@hcmunre.edu.vn (Primary Contact)
Phạm Văn, T. (2021). 04. Establishment of the impervious surfaces map using Sentinel-2 data: a case study in Ho Chi Minh City. Science Journal of Natural Resources and Environment, (38), 30–38. Retrieved from https://tapchikhtnmt.hunre.edu.vn/index.php/tapchikhtnmt/article/view/360

Article Details

Similar Articles

1 2 3 4 5 6 7 > >> 

You may also start an advanced similarity search for this article.

01. Monitoring mining activities by using satellite imagery data and UAV images: a case study in Yen Bai province

Huệ Lê Minh, Hiên Vũ Thị Thanh, Thảo Đỗ Thị Phương
Abstract View : 39
Download :20

11. Study on the application of geospatial technology to build 3D geographic data for smart cities

Trung Nguyễn Văn, Làn Phạm Thị, Sơn Tống Sĩ, Hà Lê Thị Thu, Nam Nguyễn Văn
Abstract View : 87
Download :32