EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY

被引:14
作者
Vigneshwaran, S. [1 ]
Kumar, S. Vasantha [1 ]
机构
[1] VIT, Sch Civil & Chem Engn, Vellore, Tamil Nadu, India
来源
INTERNATIONAL CONFERENCE ON GEOMATIC & GEOSPATIAL TECHNOLOGY (GGT 2018): GEOSPATIAL AND DISASTER RISK MANAGEMENT | 2018年 / 42-4卷 / W9期
关键词
Built-up area; Extraction; Normalized Difference Index; High Resolution Satellite Imagery; Sentinel-2A; Google Satellite Imagery; INDEX;
D O I
10.5194/isprs-archives-XLII-4-W9-165-2018
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
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.
引用
收藏
页码:165 / 169
页数:5
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