Detection of Sangeang Api Volcanic Ash Cloud Based on VBICA-SVM method

Abstract

Abstract. Volcanic ash cloud can threaten the safety of aviation transportation. The current detection of the volcanic ash cloud mainly depends on the remote sensing images. Independent component analysis (ICA) and support vector machine (SVM) have very strong complementary to each other in the volcanic ash cloud detection. Taking the moderate resolution imaging spectroradiometer (MODIS) images of Indonesia Sangeang Api volcanic ash clouds as data source on May 30, 2014, this paper propose the variable Bayesian ICA and SVM (VBICA-SVM) method for detection of the volcanic ash cloud, which is based on the analysis of the physical properties of volcanic ash cloud and the absorption spectral characteristics in the scope of thermal infrared bands. The result shows that the VBICA-SVM method can effectively detect the spatial distribution of the volcanic ash clouds, and has great potential applications in the ash cloud monitoring and disaster mitigation.