APLIKASI MODEL AR4 PADA PEMETAAN JENIS PENGGUNAAN/TUTUPAN LAHAN MENGGUNAKAN CITRA LANDSAT 8

Akhbar Akhbar, Ida Arianingsih

Abstract


The research aims to develop applications AR4 models as a new model in the extraction of the object area in the medium resolution Landsat 8 image in providing land mapping database for the purposes of planning, evaluation and monitoring of the type of use / land cover. Descriptive method was used to assess the value of the object land spectral on based spectral bands Landsat 8 image transformation results. Image transformation using AR4 models, namely a multiband image analysis model developed by Akhbar et.al., in 2013 using Landsat 7 ETM+ and SPOT 5 XS. Research is now put through trials on the AR4 models Landsat 8 image in the same location as a previous study, in the district (Sigi, Donggala, Parigi Moutong) and Palu City with an area of 99,141.12 hectares. Geographically, located at coordinates 119 ° 48 '39.67 "E - 120 ° 1' 2.99" E and 0 ° 42 '5.11" S - 1 ° 5' 15.76" S. Generated imagery Landsat 8 AR4 models with the conformity / suitability of land ≥90% between objects on the image of the transformation and the 50 sample sites tested in the field. So that the AR4 models image of Landsat 8 including the excellent category is used in mapping the type of use / land cover.


Keywords


Landsat 8, AR4 Model, Extraction, Mapping, Use/Land Cover

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References


Abellera, L.V. 2005. Application of Knowledge-Based Classification Techniques and Geographic Information Systems (GIS) on Satellite Imagery for Stormwater Management. A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Civil Engineering. Los, Angeles, University of California.

Akhbar, 2014. Pemodelan Sistem Analisis Penggunaan Lahan Berbasis Data Citra Satelit. Disertasi Program Doktoral Ilmu-ilmu Pertanian. Program Pascasarjana Universitas Tadulako, Palu

Akhbar, M. Basir, B. E. Somba and Golar, 2013. AR4-50 Model, The Extraction of Spectral Values Into Remote Sensing Image Data-Based Land Use Class. Agrivita, Journal of Agricultural Science (AJAS), “35 (3)”, 255-262.

Akhbar, M. Basir, B. E. Somba and Golar, 2014. Transformation of Satellite Image Data In Class Modeling of Land Use/Cover Of Agriculture and Forestry In Tropical Area. International Journal of Environmental Sciences (IJES), “4 (5)”, 945-955.

Arymurti, A.M. dan S. Setiawan, 1992. Pengantar Pengolahan Citra. Penerbit PT Elex Media Komputindo. Kelompok Gramedia. Jakarta

Danoedoro, P. 2012. Pengantar Penginderaan Jauh Digital. Penerbit Andi. Yogyakarta

Kamal, M dan S. Arjasakusuma, 2010. Ekstraksi Informasi Penutup Lahan Menggunakan Spektrometer Lapangan Sebagai Masukan Endmember pada Data Hiperspektral Resolusi Sedang. Jurnal Ilmiah Geomatika-Bakosurtanal, “16 (2)”, 12-22.

Lillesand, T.M., dan R.W. Keifer. 1999. Penginderaan Jauh dan Interpretasi Citra. Penerjemah Dulbahri, Prapto Suhartono, Hartono, Suharyadi. Gajah Mada University Press. Yogyakarta

Lu, D., E. Moran, S. Hetrick, dan G. Li. 2011. Mapping Impervious Surface Distribution with the Integration of Landsat TM and QuickBird Images in a Complex Urban–Rural Frontier in Brazil. In: Advances of Environmental Remote Sensing to Monitor Global Changes. Ni-Bin Chang (ed.), CRC Press/Taylor and Francis, 277-296.

Sutanto, 1994. Penginderaan jauh, Jilid I, Fakultas Geografi Universitas Gajah Mada. Gajah Mada University Press, Yogyakarta.


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