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All Journal Indonesian Journal of Geography Geo Media: Majalah Ilmiah dan Informasi Kegeografian Majalah Geografi Indonesia JURNAL AGROTEKNOLOGI Forum Geografi GEA, Jurnal Pendidikan Geografi MAJALAH ILMIAH GLOBE UNM Geographic Journal BHUMI: Jurnal Agraria dan Pertanahan GEOGRAPHIA: Jurnal Pendidikan dan Penelitian Geografi Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Iswari Nur Hidayati
Departement Of Geographic Information Science, Faculty Of Geography, Gadjah Mada University
Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences Other

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Journal : Forum Geografi

 1 
Developing an Extraction Method of Urban Built-Up Area Based on Remote Sensing Imagery Transformation Index Hidayati, Iswari Nur; Suharyadi, R; Danoedoro, Projo
Forum Geografi Vol 32, No 1 (2018): July 2018
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v32i1.5907

Abstract

Studying urban areas using remote sensing imagery has become a challenge, both visually and digitally. Supervised classification, one of the digital classification approaches to differentiate between built-up and non-built-up area, used to be leading in digital studies of urban area. Then the next generation uses index transformation for automatic urban data extraction. The extraction of urban built-up land can be automatically done with NDBI although it has one limitation on separating built-up land and bare land. The previous studies provide opportunities for further research to increase the accuracy of the extraction, particularly using index transformation. This study aims to obtain the maximum accuracy of the extraction by merging several indices including NDBI, NDVI, MNDWI, NDWI, and SAVI. The merging of the indices is using four stages: merging of two indices, three indices, four indexes and five indices. Several operations were experimented to merge the indices, either by addition, subtraction, or multiplication. The results show that merging NDBI and MNDWI produce the highest accuracy of 90.30% either by multiplication (overlay) or reduction. Application of SAVI, NDBI, and NDWI also gives a good effect for extracting urban built-up areas and has 85.72% mapping accuracy.
A COMPARATIVE STUDY OF VARIOUS INDICES FOR EXTRACTION URBAN IMPERVIOUS SURFACE OF LANDSAT 8 OLI Hidayati, Iswari Nur; Suharyadi, R
Forum Geografi Vol 33, No 2 (2019): December 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i2.9179

Abstract

Impervious surface is one of the major land cover types of urban and suburban environment. Conversion of rural landscapes and vegetation area to urban and suburban land use is directly related to the increase of the impervious surface area. The impervious surface expansion is straight-lined with decreasing green spaces in urban areas. Impervious surface is one of indicator for detecting urban heat islands. This study compares various indices for mapping impervious surfaces using Landsat 8 OLI imagery by optimizing the different spectral characteristics of Landsat 8 OLI imagery. The research objectives are (1) to apply various indices for impervious surface mapping and (2) identifies impervious surfaces in urban areas based on multiple indices and provide recommendations and find the best index for mapping impervious surface in urban areas. In addition to utilizing the index, land use supervised classification method, maximum likelihood classification used for extracting built-up, and non-built-up areas. Accuracy assessment of this research used field data collection as primary data for calculating kappa coefficient, producer accuracy, and user accuracy. The study can also be extended to find the land surface temperature and correlate the impervious surface extraction data with urban heat islands.
A Comparative Study of various Indices for extraction urban impervious surface of Landsat 8 OLI Iswari Nur Hidayati; R Suharyadi
Forum Geografi Vol 33, No 2 (2019): December 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i2.9179

Abstract

Impervious surface is one of the major land cover types of urban and suburban environment. Conversion of rural landscapes and vegetation area to urban and suburban land use is directly related to the increase of the impervious surface area. The impervious surface expansion is straight-lined with decreasing green spaces in urban areas. Impervious surface is one of indicator for detecting urban heat islands. This study compares various indices for mapping impervious surfaces using Landsat 8 OLI imagery by optimizing the different spectral characteristics of Landsat 8 OLI imagery. The research objectives are (1) to apply various indices for impervious surface mapping and (2) identifies impervious surfaces in urban areas based on multiple indices and provide recommendations and find the best index for mapping impervious surface in urban areas. In addition to utilizing the index, land use supervised classification method, maximum likelihood classification used for extracting built-up, and non-built-up areas. Accuracy assessment of this research used field data collection as primary data for calculating kappa coefficient, producer accuracy, and user accuracy. The study can also be extended to find the land surface temperature and correlate the impervious surface extraction data with urban heat islands.
Developing an Extraction Method of Urban Built-Up Area Based on Remote Sensing Imagery Transformation Index Iswari Nur Hidayati; R Suharyadi; Projo Danoedoro
Forum Geografi Vol 32, No 1 (2018): July 2018
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v32i1.5907

Abstract

Studying urban areas using remote sensing imagery has become a challenge, both visually and digitally. Supervised classification, one of the digital classification approaches to differentiate between built-up and non-built-up area, used to be leading in digital studies of urban area. Then the next generation uses index transformation for automatic urban data extraction. The extraction of urban built-up land can be automatically done with NDBI although it has one limitation on separating built-up land and bare land. The previous studies provide opportunities for further research to increase the accuracy of the extraction, particularly using index transformation. This study aims to obtain the maximum accuracy of the extraction by merging several indices including NDBI, NDVI, MNDWI, NDWI, and SAVI. The merging of the indices is using four stages: merging of two indices, three indices, four indexes and five indices. Several operations were experimented to merge the indices, either by addition, subtraction, or multiplication. The results show that merging NDBI and MNDWI produce the highest accuracy of 90.30% either by multiplication (overlay) or reduction. Application of SAVI, NDBI, and NDWI also gives a good effect for extracting urban built-up areas and has 85.72% mapping accuracy.
Co-Authors Achmad Fadhilah Alke Caroline Helena Maru Andita, Aning Arlindita, Yazinka Puri Emilya Nurjani Eni Susanti Eni Susanti Fathilda, Intan Khaeruli Gian Felix Ramadhan Herdiansyah Herdiansyah Magiswari, Vabbereina Jasmineputeri Prima Widayani Projo Danoedoro Projo Danoedoro Projo Danoedoro Projo Danoedoro R Suharyadi R. Suharyadi Rahmatika, Iklila Renita, Ermie Suharyadi, R Suharyadi, R Westi Utami Wuri Handayani