AGRIVITA, Journal of Agricultural Science
Vol 35, No 3 (2013)

AR4-50 MODEL, THE EXTRACTOR OF SPECTRAL VALUES INTO REMOTE SENSING IMAGE DATA-BASED LAND USE CLASS

Akhbar Akhbar (Unknown)
Muhammad Basir (Unknown)
Bunga Elim Somba (Unknown)
Golar Golar (Unknown)



Article Info

Publish Date
12 May 2014

Abstract

This study attempted to develop an extraction model of spectral values ​​of land objects into land use/land cover classes on remote sensing image in the provision of land database for planning, evaluation, and monitoring in agriculture and forestry. This study employed an Isodata method and Knowledge-Based Systems (KBS) using the Landsat 7 ETM+ image in the coverage area of ​​117,799.06 ha, and the SPOT 5 XS image in the coverage area of ​​113,241.37 ha in Palu, Sigi and Donggala. The study found two image models labelled as AR4-50 and SBP-AR4-50. The separability image AR4-50 model has an average capability for separating land object pixels which are statistically 1811.98 to 1972.08 (moderate-good), with the class accuracy of land use/land cover using the image homogeneity model of SBP-AR4-50, which is totally (confusion matrix) 72.15% -87.17%, the accuracy level of land map generator for agricultural land/forestry is in good-excellent category on the Landsat 7 ETM+ and SPOT 5 XS images. Keywords: Image, Class, Land Use, Model, Separability, Homogeneity.

Copyrights © 2013






Journal Info

Abbrev

AGRIVITA

Publisher

Subject

Agriculture, Biological Sciences & Forestry

Description

AGRIVITA Journal of Agricultural Science is a peer-reviewed, scientific journal published by Faculty of Agriculture Universitas Brawijaya Indonesia in collaboration with Indonesian Agronomy Association (PERAGI). The aims of the journal are to publish and disseminate high quality, original research ...