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      <JournalTitle>International Journal of Engineering, Science and</JournalTitle>
      <Volume-Issue>Volume 6, Issue 8,</Volume-Issue>
      <Season>December 2017 (Special Issue)</Season>
      <ArticleType>Engineering, Science and Mathematics</ArticleType>
      <ArticleTitle>Study of normalized difference built-up (NDBI) index in automatically mapping urban areas from Landsat TM imagery.</ArticleTitle>
          <FirstName>Hari Krishna Karanam* and Victor</FirstName>
      <Abstract>The Visakhapatnam city lies on the eastern part of India and the urban sprawl in Visakhapatnam town was analyzed using multi-temporal Landsat TM data from 2005 to 2015. Spectral indices namely Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI) and Built-up Index (BUI) were generated from the Landsat TM bands covering visible Red (R), Near Infrared (NIR) and Short Wave Infrared (SWIR) wave-length regions. Spectral variations in built-up, open spaces, urban vegetation and water areas were studied by generating two-dimensional spectral plots of NDBI and BUI.  Remote sensing images are mainly used for monitoring and detecting the land cover changes that occur frequently in urban and sub-urban areas as a consequence of incessant urbanization. The conversion of satellite imagery into land cover map using the existing methods of manual interpretation and parametric image classification digitally is a lengthy process. Normalized Difference Built-up Index (NDBI) which is used for mapping built-up areas automatically. This method main advantage is the unique spectral response of built-up area and other land covers. Built-up area can be effectively mapped through arithmetic manipulation of re-coded Normalized Difference Vegetation Index (NDVI) and NDBI images derived from TM imagery.  This NDBI method is applied to Vishakaptanam Area in this paper and the mapped area results at accuracy of 93.9% indicates that it can be used to fulfill the mapping objective reliably and efficiently. Comparing NDBI with the maximum likelihood classification method, this NDBI method is able to serve as a worthwhile alternative for quickly and objectively mapping built-up areas.</Abstract>
      <Keywords>Difference Vegetation Index, Normalized Difference Built-up Index, Built-up Index and Spectral variations</Keywords>
        <Abstract>https://ijesm.co.in/ubijournal-v1copy/journals/abstract.php?article_id=4243&amp;title=Study of normalized difference built-up (NDBI) index in automatically mapping urban areas from Landsat TM imagery.</Abstract>