OBIA CLASSIFICATION AND BUILT-UP LAND INDICES NDBI FOR ESTIMASTION OF SETTLEMENT DENSITY IN PONTIANAK CITY
(1) Staff Departemen Remote Sensing Earthline, Gadjah Mada University.
Abstract
Settlement density data is very important because the density of settlements is one of the main indicators of slum settlement in Pontianak City. The one of way to obtain settlement density information is to use remote sensing data like satellite imagery or aerial photo. This is a problem considering the budget and more time to get high resolution satellite imagery and extract the information we want.
The one method for the detection of settlements using Landsat 8 satellite imagary is the built-up land indices NDBI (Normalized Difference Build-up Index). Objective of this research is build spatial model of settlement density in Pontianak City using built-up land indices NDBI (Normalized Difference Build-up Index), moreover combining with OBIA Classification (Object Base Image Analysis).
The results of this research indicate that built-up land indices NDBI has a value of determination (R2) is high that is equal to 0.628 and has a strong correlation of 0.792 to the density of settlements calculated from aerial photo. The spatial model of settlement density estimation has a R2 of 0.75 and a RMSE value of 5.10Keywords
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REFERENCE
Asy-syakur, Abd Rahman. Adnyana, I Wayan Sandi. Arthana, I Wayan Arthana. Nuarsa, I Wayan. 2012. Enhanced Built-Up and Bareness Index (EBBI) for Mapping Built-Up and Bare Land in an Urban Area. Remote Sensing, 4, pp.2957-2970.
BAPPEDA Kota Pontianak. 2015. Perkembangan Demografi dan Perekonomian Kota Pontianak. http://bappeda.pontianakkota.go.id/berita-31-perkembangan-demografi-dan-perekonomian-kota-pontianak.html. Diakses: 19/04/17
BAPPEDA Kota Pontianak. 2015. Habis MDGs Terbitlah Target 100-0-100: Era Baru Mewujudkan Permukiman Layak Huni dan Berkelanjutan di Kota Pontianak. http://bappeda. pontianakkota.go.id/berita-45-habis-mdgs-terbitlah-target-1000100--era-baru-mewujudkan-permukiman-layak-huni-dan-berkelanjutan-di-kota-pontianak.html. Diakses: 19/04/17
Bhatti, Saad Saleem & Tripathi, Nitin Kumar. 2014. Built-up area extraction using Landsat 8 OLI imagery. GIScience & Remote Sensing, 2014 Vol. 51, No. 4, 445–467
Danoedoro, Projo. 2012. Pengantar Penginderaan Jauh Digital. Yogyakarta : Penerbit Andi
Peraturan Daerah Kota Pontianak Nomor 2 Tahun 2013 Tentang Rencana Tata Ruang Wilayah (RTRW) Tahun 2013- 2033
Putra, Akbar Cahyadhi Pratama. 2016. Pemetaan Kerapatan Kanopi Hutan Mangrove Menggunakan Citra Landsat 8 OLI Di Wilayah Pengelolaan (Resort Grajagan), Taman Nasional Alas Purwo, Kabupaten Banyuwangi, Jawa Timur. Skripsi. Program Studi Kartografi dan Penginderaan Jauh, Fakultas Geografi, Universitas Gadjah Mada
Sari, Kartika Indah. 2015. Kampung Beting Pontianak, Kalimantan Barat. http://kampungnesia.org/beritakampung-beting-pontianak-kalimantan-barat.html.Diakses: 30/04/17
Soemarwoto, Otto. 1991. Analisis Dampak Lingkungan. Yogyakarta: Gadjah Mada University Press.
Suwarsono and Khomarudin, M Rokhis. 2014. Deteksi Wilayah Permukiman Pada Bentuklahn Vulkanik Menggunakan Citra Landsat-8 OLI Berdasarkan Parameter Normalized Difference Build-up Index (NDBI). Prosiding Seminar Nasional Penginderaan Jauh 2014
U.S. Geological Survey. 2013. Landsat Processing Details. http://landsat. usgs.gov/Landsat8_Using_Product.php Diakses: 01/04/17
Zha, Yong, Gao, Jingqing. & Ni, S. 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing. 24(3), pp. 583−594.
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