A Bag-of-Words framework for natural disaster evaluation on Sentinel-2 image

Abstract

The machine learning algorithms are an essential tool to measure the impact that severe weather has on the environment. Addressing the land cover changes generated by extreme natural phenomena, in this paper, we present the ability of the bag-of-words (BoW) framework for change detection in remote sensing images. Regarding this, we used Sentinel-2 images related to two case studies: the massive bushfires from Kangaroo Island, on January 2020, and 2019 Midwestern U.S floods. Our experimental results demonstrated that the proposed methodology can achieve promising performance for both fires and floods scenarios.