Abstract—Built-up areas play a significant type of land use associated with the urbanization. Classifying the built-up area by using satellite image, is also a high demand for a relevant organization to investigate the urban sprawl. This study aims to develop an index used to classify the built-up areas accurately. In order to achieve the aim of the study, two objectives were intensively studied to compare the results from several indices used to appropriately classify the built-up areas from satellite data of Landsat 8. The second objective is to develop a built-up area index which is suitable for classifying the built-up areas. This study considers the two study areas, Bangkachao and Bangkok International Airport, which encounter the rapid urbanization. This study employs a satellite image of Landsat 8 OLI (Operational Land Imager (OLI). The Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI) were intensively examined to present a BUI map correspondingly. On the other hand, Modified Normalized Difference Water Index (MNDWI) was tested to separate the water areas and wetlands from the built-up areas distinctively. Furthermore, the Modified Built-Up Index (MBUI) were developed based on the integration between the MNDWI and BUI map. As a result, it is clearly shown that the MBUI provides more accurate results of built-up area classification than the BUI. Also, the MBUI presents 82-83% accuracy of both study areas, which are higher than the BUI map. It is to say that MBUI can be employed to classify the built-up areas of the study areas accurately.
Index Terms—Built-up index, modified built-up index, GIS, remote sensing.
W. Prasomsup is with Institute of Survey Engineering, Faculty of Engineering and Architecture, Rajamangala University of Technology Isan, Nakhon Ratchasima Province, Thailand (e-mail: email@example.com).
P. Piyatadsananon, W. Aunphoklang, and A. Boonrang are with School of Geoinformatics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima Province, Thailand.
Cite: W. Prasomsup, P. Piyatadsananon, W. Aunphoklang, and A. Boonrang, "Extraction Technic for Built-up Area Classification in Landsat 8 Imagery," International Journal of Environmental Science and Development vol. 11, no. 1, pp. 15-20, 2020.Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).