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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Abstract: Evaluated from remote sensing perspective, urban region is a realdistrict heterogeneous, what gives reflectance from different some land covertype and material. The limitation of the spatial resolution from middle resolutionsensor such as Landsat requires analysis at level sub-pixel. Mixture pixel inremote sensing data is one of the source of error in accuracy assessment result in conventional classification. This research tries to apply Linear Spectral MixtureAnalysis (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 giveinformation 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 theaccuration, are Atmospheric Correction, Minimum Noise Fraction (MNF) andPixel Purity Index (PPI). The percentage of each land cover component in eachpixel shown by fraction image from method LSMA with RMS Error average is 0,016 indicated that each endmember land cover has been dissociated well withsmall deviation standard. The accuration test result of abundance for eachendmember using IKONOS image equal to 95%, indicates that LSMA have a high accuration to detect the endmember land cover at level sub-pixel.
Keywords: MNF, PPI, endmember, linear spectral mixture analysis
Penulis: Nurlina
Kode Jurnal: jpfisikadd090075

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Jp Fisika dd 2009