Building Flood Resilience Through Flood Risk Assessment with Optical and Microwave Remote Sensing

Floods, which cause extensive environmental and socioeconomic devastation, are among the most prevalent hazards worldwide. Over the past few decades, the intensity, total number of occurrences, and damaging impact of floods have significantly augmented on a global scale. This escalation in flood damages has spurred researchers to prioritize the development of resilient and inclusive modelling techniques aimed at mitigating the effects of floods. The objective of this chapter is to present an overview of the concepts and techniques associated to flood hazard, vulnerability, and risk assessment in order to establish a Climate-Resilient Nation. The flood risk assessment process primarily comprises three key components: risk recognition, risk investigation, and risk assessment. Flood risk, as a dependent variable, is influenced by both flood vulnerability and flood hazard, with both factors contributing to its determination. There is a prosperity of freely available Remote sensing data, geospatial products, and various analytical methods and models that can be used for flood risk assessment and monitoring. Numerous tools and techniques exist for conducting flood risk assessments, such as the statistical method based on historical flood hazards, the index-based multi-criteria decision analysis method, the satellite imagery based spatial analysis method, Monte Carlo simulation and Artificial Intelligence method. All of these methods provide an overview of the present status and future scenario. A hybrid approach, which combines two or more tools and techniques simultaneously, has been adopted to assess, monitor, and propose management plans for flood hazards. This integration allows for enhanced analysis while saving time and effort. The introduction of synthetic aperture radar (SAR) based microwave sensors has brought about a transformative change in flood hazard management. These sensors have empowered continuous data acquisition, unaffected by weather conditions, and have enabled round the clock monitoring capabilities. The continuous availability of free datasets from missions such as Sentinel-1, along with the advancements in processing technologies based on cloud computing like the Google Earth Engine, has made SAR data a precious resource for flood hazards monitoring. As a result, near real-time flood mapping and automated services have developed. Recent advancements, particularly in optical and microwave data, have led to more accurate and efficient monitoring, mapping, and modelling of floods.