Global near real time flood mapping using a fully automated Sentinel 1 based processing chain
Fast growing population numbers and climate change as a driving force for extreme meteorological events lead to an increasing impact of natural disasters on the environment in general and human life in particular. Concurrently, technical developments strongly enable a better spacecraft driven earth observation resulting in an increasing demand for rapid crisis mapping products (Voigt, et al. 2016) Of all globally monitored natural disasters floods occurred with a frequency of 39 in the period from 1980 to 2015 (Munich RE, 2016) This number emphasizes the need for a global time independent flood monitoring followed by information about the spatial distribution of flooded areas. This information directly serves as an input for end users, e.g. rescue forces in the field, insurance companies, planners of infrastructure, etc. In this article, we demonstrate an automated processing chain automatically deriving flood information from globally acquired Sentinel 1 data. We first describe the data used and further elaborate on the methodology in more detail. The processing chain has been designed to compute global data and currently operates on different areas of interest all over the world. However, we apply the methodology to a single use case in Kerala, India, and discuss the benefits and disadvantages of a radar based flood detection system. We conclude this article with the further use of the results in the form of a web based presentation as well as crisis mapping products.