Accuracy Improvement For Remote Sensing Based Lithological Mapping By Using Randomisation And Categorical Coincidence - Rio Priandri Nugroho; Mohamad Roviansah (Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN), 2020)
Remote sensing based lithological mapping is commonly applied in the field of earth science as it requires less resource in contrast with real field work. Limitation regarding low accuracy is a challenge that should be tackled in applying remote-sensing based classification. In this paper, an attempt to improve overall accuracy of image classification using randomisation and categorical coincidence analysis was performed. It yielded final majority classification map which has higher overall accuracy compared to the overall accuracy of the population average and the overall accuracy of the map created by including all training data.