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Nicolas Christanto
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Computer Science & IT Mathematics Other

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IMPERVIOUS AREA ESTIMATION of BOGOR USING LANDSAT-7 ETM+ Nicolas Christanto
Jurnal Ilmu Komputer dan Sistem Informasi Vol 2, No 1 (2014): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v2i1.3178

Abstract

Classification percentage of impervious surface area is a technique for classifying the percentage of impervious contained in an image. The purpose to determine how much impervious surface in examined area. The image used is satellite image from Landsat-7 ETM+. The method used in this design is Principal Component Regression (PCR). PCR will optimize the variables that           have an important role in the formation of the model classifier. The input used is the value of pixel grayscale of each image and also the values of NDVI and NDBI. The output of the program in the form of thematic maps and impervious percentage of the image under study. However, the percentange of error from the program is not known, because there is no accurate data on the percentage of impervious. Key Words:PCR, Impervious Surface Area, Regression, Remote Sensing.
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