Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)

Evaluated from remote sensing perspective, urban region is a real district heterogeneous, what gives reflectance from different some land cover type and material. The limitation of the spatial resolution from middle resolution sensor such as Landsat requires analysis at level sub-pixel. Mixture pixe...

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Main Author:	Nurlina Nurlina
Format:	Article
Language:	English
Published:	Lambung Mangkurat University Press 2017-03-01
Series:	Jurnal Fisika Flux
Subjects:	mnf, ppi, endmember, linear spectral mixture analysis
Online Access:	https://ppjp.ulm.ac.id/journal/index.php/f/article/view/3045

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author	Nurlina Nurlina
author_facet	Nurlina Nurlina
author_sort	Nurlina Nurlina
collection	DOAJ
description	Evaluated from remote sensing perspective, urban region is a real district heterogeneous, what gives reflectance from different some land cover type and material. The limitation of the spatial resolution from middle resolution sensor such as Landsat requires analysis at level sub-pixel. Mixture pixel in remote sensing data is one of the source of error in accuracy assessment result in conventional classification. This research tries to apply Linear Spectral Mixture Analysis (LSMA) method to detect land cover change (vegetation, impervious surface, bare soil and water) at level sub-pixel in Banjarbaru City based on Landsat temporal data. LSMA is approach with analysis sub-pixel which can give information of the fraction in each pixel, so that is a potential solution to classify one pixel. Maximum Likelihood Classifier applied as comparable from LSMA. Accuracy assessment to this method use a higher spatial resolution IKONOS image. Some processing phases applied in this research to increase the accuration, are Atmospheric Correction, Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The percentage of each land cover component in each pixel shown by fraction image from method LSMA with RMS Error average is 0,016 indicated that each endmember land cover has been dissociated well with small deviation standard. The accuration test result of abundance for each endmember using IKONOS image equal to 95%, indicates that LSMA have a high accuration to detect the endmember land cover at level sub-pixel.
first_indexed	2024-12-21T03:42:22Z
format	Article
id	doaj.art-d05f671ca0364434b8351cd419f0ee23
institution	Directory Open Access Journal
issn	1829-796X 2541-1713
language	English
last_indexed	2024-12-21T03:42:22Z
publishDate	2017-03-01
publisher	Lambung Mangkurat University Press
record_format	Article
series	Jurnal Fisika Flux
spelling	doaj.art-d05f671ca0364434b8351cd419f0ee232022-12-21T19:17:11ZengLambung Mangkurat University PressJurnal Fisika Flux1829-796X2541-17132017-03-016111610.20527/flux.v6i1.30452774Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)Nurlina Nurlina0Program Studi Fisika, FMIPA, Universitas Lambung MangkuratEvaluated from remote sensing perspective, urban region is a real district heterogeneous, what gives reflectance from different some land cover type and material. The limitation of the spatial resolution from middle resolution sensor such as Landsat requires analysis at level sub-pixel. Mixture pixel in remote sensing data is one of the source of error in accuracy assessment result in conventional classification. This research tries to apply Linear Spectral Mixture Analysis (LSMA) method to detect land cover change (vegetation, impervious surface, bare soil and water) at level sub-pixel in Banjarbaru City based on Landsat temporal data. LSMA is approach with analysis sub-pixel which can give information of the fraction in each pixel, so that is a potential solution to classify one pixel. Maximum Likelihood Classifier applied as comparable from LSMA. Accuracy assessment to this method use a higher spatial resolution IKONOS image. Some processing phases applied in this research to increase the accuration, are Atmospheric Correction, Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The percentage of each land cover component in each pixel shown by fraction image from method LSMA with RMS Error average is 0,016 indicated that each endmember land cover has been dissociated well with small deviation standard. The accuration test result of abundance for each endmember using IKONOS image equal to 95%, indicates that LSMA have a high accuration to detect the endmember land cover at level sub-pixel.https://ppjp.ulm.ac.id/journal/index.php/f/article/view/3045mnf, ppi, endmember, linear spectral mixture analysis
spellingShingle	Nurlina Nurlina Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya) Jurnal Fisika Flux mnf, ppi, endmember, linear spectral mixture analysis
title	Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)
title_full	Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)
title_fullStr	Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)
title_full_unstemmed	Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)
title_short	Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)
title_sort	analisis spektral campuran linier untuk deteksi tutupan lahan di daerah perkotaan menggunakan data satelit landsat etm studi kasus kota banjarbaru dan sekitarnya
topic	mnf, ppi, endmember, linear spectral mixture analysis
url	https://ppjp.ulm.ac.id/journal/index.php/f/article/view/3045
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Analisis Spektral Campuran Linier untuk Deteksi Tutupan Lahan di Daerah Perkotaan menggunakan Data Satelit Landsat ETM+ (Studi Kasus Kota Banjarbaru dan Sekitarnya)

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