Disaster Risk Assessment of Fluvial and Pluvial Flood Using the Google Earth Engine Platform: a Case Study for the Filyos River Basin

Abstract

AbstractThe aim of this study is to conduct a risk analysis of fluvial and pluvial flood disasters, focusing on the vulnerability of those residing in the river basin in coastal regions. However, there are numerous factors and indicators that need to be considered for this type of analysis. Swift and precise acquisition and evaluation of such data is an arduous task, necessitating significant public investment. Remote sensing offers unique data and information flow solutions in areas where access to information is restricted. The Google Earth Engine (GEE), a remote sensing platform, offers strong support to users and researchers in this context. A data-based and informative case study has been conducted to evaluate the disaster risk analysis capacity of the platform. Data on three factors and 17 indicators for assessing disaster risk were determined using coding techniques and web geographic information system (web GIS) applications. The study focused on the Filyos River basin in Turkey. Various satellite images and datasets were utilized to identify indicators, while land use was determined using classification studies employing machine learning algorithms on the GEE platform. Using various applications, we obtained information on ecological vulnerability, fluvial and pluvial flooding analyses, and the value of indicators related to construction and population density. Within the scope of the analysis, it has been determined that the disaster risk index (DRI) value for the basin is 4. This DRI value indicates that an unacceptable risk level exists for the 807,889 individuals residing in the basin.