KAJIAN JARINGAN SYARAF TIRUAN BERBASIS CITRA ASTER VNIR DAN SWIR UNTUK KLASIFIKASI PENUTUP DAN PENGGUNAAN LAHAN DI KECAMATAN KATINGAN TENGAH, KABUPATEN KATINGAN, PROVINSI KALIMANTAN TENGAH
The availability of an accurate data with an appropriate scale and accuracy of the landcover and landuse of Katingan Tengah District is very critical. This accurate data will be used as the base for taking a long-term planning decision. Central Kalimantan is a very large areal, therefore spatial dat...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2013
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| Summary: | The availability of an accurate data with an appropriate scale and accuracy of
the landcover and landuse of Katingan Tengah District is very critical. This accurate
data will be used as the base for taking a long-term planning decision. Central
Kalimantan is a very large areal, therefore spatial data processing with remote sensing
method is considered better than the terrestrial inventory method. Terrestrial method
takes more time, more cost, and more energy. Artificial Neural Network (ANN)
method is one of remote sensing methods that is expected to give a better accuracy for
landcover and landuse. The good side about this method is its capability in spectral
and non-spectral data combination. ANN does not require normal distribution of
spectral training samples. This algorithm is also able to overcome the problem of mix
pixels.
The objectives of this study are : ( 1 ) To find out how accurate the ANN
method and the non-spectral data for landuse identification |
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