EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY
Accurate information about the built-up area in a city or town is essential for urban planners for proper planning of urban infrastructure facilities and other basic amenities. The normalized difference indices available in literature for built-up area extraction are mostly based on moderate resolut...
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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doaj-61ff046853e24c25ac2a0c29741cdae32020-11-24T21:51:49ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342018-10-01XLII-4-W916516910.5194/isprs-archives-XLII-4-W9-165-2018EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERYS. Vigneshwaran0S. Vasantha Kumar1School of Civil and Chemical Engineering, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, IndiaSchool of Civil and Chemical Engineering, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, IndiaAccurate information about the built-up area in a city or town is essential for urban planners for proper planning of urban infrastructure facilities and other basic amenities. The normalized difference indices available in literature for built-up area extraction are mostly based on moderate resolution images such as Landsat Thematic Mapper (TM) and enhanced TM (ETM+) and may not be applicable for high resolution images such as Sentinel-2A. In the present study, an attempt has been made to extract the built-up area from Sentinel-2A satellite data of Chennai, India using normalized difference index (NDI) with different band combinations. It was found that the built-up area was clearly distinguishable when the index value ranges between −0.29 and −0.09 in blue and near-infrared (NIR) band combination. Post extraction editing using Google satellite imagery was also attempted to improve the extraction results. The results showed an overall accuracy of 90% and Kappa value of 0.785. Same approach when applied for another area also yields good results with overall accuracy of 92% and Kappa value of 0.83. As the proposed approach is simple to understand, yields accurate results and requires only open source data, the same can be used for extracting the built-up area using Sentinel-2A and Google satellite imagery.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W9/165/2018/isprs-archives-XLII-4-W9-165-2018.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
S. Vigneshwaran S. Vasantha Kumar |
spellingShingle |
S. Vigneshwaran S. Vasantha Kumar EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
S. Vigneshwaran S. Vasantha Kumar |
author_sort |
S. Vigneshwaran |
title |
EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY |
title_short |
EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY |
title_full |
EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY |
title_fullStr |
EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY |
title_full_unstemmed |
EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY |
title_sort |
extraction of built-up area using high resolution sentinel-2a and google satellite imagery |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2018-10-01 |
description |
Accurate information about the built-up area in a city or town is essential for urban planners for proper planning of urban infrastructure facilities and other basic amenities. The normalized difference indices available in literature for built-up area extraction are mostly based on moderate resolution images such as Landsat Thematic Mapper (TM) and enhanced TM (ETM+) and may not be applicable for high resolution images such as Sentinel-2A. In the present study, an attempt has been made to extract the built-up area from Sentinel-2A satellite data of Chennai, India using normalized difference index (NDI) with different band combinations. It was found that the built-up area was clearly distinguishable when the index value ranges between −0.29 and −0.09 in blue and near-infrared (NIR) band combination. Post extraction editing using Google satellite imagery was also attempted to improve the extraction results. The results showed an overall accuracy of 90% and Kappa value of 0.785. Same approach when applied for another area also yields good results with overall accuracy of 92% and Kappa value of 0.83. As the proposed approach is simple to understand, yields accurate results and requires only open source data, the same can be used for extracting the built-up area using Sentinel-2A and Google satellite imagery. |
url |
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W9/165/2018/isprs-archives-XLII-4-W9-165-2018.pdf |
work_keys_str_mv |
AT svigneshwaran extractionofbuiltupareausinghighresolutionsentinel2aandgooglesatelliteimagery AT svasanthakumar extractionofbuiltupareausinghighresolutionsentinel2aandgooglesatelliteimagery |
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