IDENTIFIKASI DAN KLASIFIKASI PERUNTUKAN LAHAN MENGGUNAKAN CITRA ASTER (Landuse Identification and Classification Using ASTER Multispectral Data)

Indarto Indarto, Arif Faisol


Abstract


ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) is classified as new sensor based on the TERRA satellite developed in the recent years. ASTER has been developed to provide image for monitoring environmental phenomenon. ASTER data offer more option for spatial resolution (60m, 30m and 15m) and more spectral resolution that suppose sufficient to capture main nomenclature of land use than usual imagery (e.g.: Landsat TM). This article shows the process of image treatment, classification, and interpretation of ASTER data to classify land use at Sampean Watershed. Two method of classification (supervised and unsupervised) are then compared to obtain the best classification. Methodology comprise of: pre-processing, survey, classification and interpretation. Classification is conducted using un-supervised and supervised methods. The classification results of these two methods are then compared to digital map (peta RBI). Supervised classification identified 7 main features of land use, while un-supervised classification only identified 3 main class of land use. The works show that supervised classification enhances the number of land use features identified and classified.


Keywords


ASTER , land use.

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