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Published: 25-04-2018
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Urban areas became a challenge to be studied, both visually and digitally. Supervised classification using remote sensing imagery to differentiate between built up and non-built-up area used to be leading in digital studies of urban land area. The next generation used index transformation for automatic urban data extraction. The extraction of urban built land can be automatically done with NDBI and also ups and downs experienced. The weakness of NDBI is not separating the built up and bare land. The previous research provide opportunities for continued research in terms of increasing accuracy particularly using index transformation. The study objective is to obtain the maximum accuracy of the merging of NDBI, NDVI, MNDWI, NDWI, and SAVI that involved in urban area. The merging of the index is using four formulas, the merging of two indexes, then three indexes, then four indexes and then five indexes. The merging of the five indexes is either by addition, subtraction, or multiplication in the experiment in this study. The result showed merger NDBI and MNDWI produce the highest accuracy of 90.30% either by multiplication (overlay) or reduction. Application of SAVI, NDBI, and NDWI also gives worthy effect for extracting urban built up areas and has 85.72% mapping accuracy.


built up extraction, remote sensing, index transformation

  1. Iswari Nur Hidayati  Scopus Sinta
    Student of Doctorate Program in Faculty of Geography, Gadjah Mada University, Indonesia Faculty of Geography, Gadjah Mada University, Indonesia
  2. R Suharyadi 
  3. Projo Danoedoro  Scopus Sinta
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