Ar4-50 Model, the Extractor of Spectral Values Into Remote Sensing Image Data-based Land Use Class

Abstract

Th is study attempted to develop a n extraction model of spectral values ​​of land objects into land use/land cover classes o n remote sensing image in the provision of land database f or 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 s eparability 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 U se , Model , Separability , Homogeneity . Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:Table Normal; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:Calibri,sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:Times New Roman; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Times New Roman; mso-bidi-theme-font:minor-bidi;}