AUTOMATED DETECTION OF COLLAPSED BUILDINGS WITH USE OF OPTICAL AND SAR IMAGES, CASE STUDY: IZMIR EARTHQUAKE ON OCTOBER 30TH, 2020
Keywords: Earthquake, Optical Satellite Image, SAR, Google Colab, ICEYE, MAXAR
Abstract. In this study, we have analysed the optical and SAR images both to detect the collapsed building automatically with the use of the cloud-based programming environment Google Colab Cloud environment. We have used the existing digital map of buildings which were provided by Here Maps Company, for each building feature, the histograms were generated both for optical and SAR images, the unmatched histograms on the optical image were mainly the destroyed buildings and newly established tent areas for the people who lost their homes. In the method, the most recent (before and after) optical images of the earthquake zone are taken. Some pre-processing steps were performed including principal component analysis, K-Means clustering. Then, the statistical values of area overlap with the building vectors are calculated and the threshold values are determined. SAR images are used to refine the results. he used optical satellite images are Worldview images with 30 cm GSD, and for SAR images, Sentinel 1 C band and ICEYE X band SAR images are used. Sentinel 1 and ICEYE images are provided from ESA.