Modeling Hotspots of Climate Change in the Sahel Using Object-Based Regionalization of Multidimensional Gridded Datasets

The population of subsaharan Africa, and particularly of the countries of the Sahel and western Africa, is one of the most vulnerable to climate change and climate-related extreme events. To provide updated information for targeted climate change adaptation measures, we modeled hotspots of climate change and related extreme events in an integrative manner. This was achieved by constructing a spatial composite indicator of cumulative climate change impact, which integrates four climate- and hazard-related subindicators: seasonal temperature trends, seasonal precipitation trends, drought occurrences, and major flood events. The analysis is based on time-series of freely available continuous, gridded geo-spatial datasets, including remote sensing data. The aggregation of the four subindicators was performed by making use of a regionalization approach, based on segmentation techniques widely used in the remote sensing community in the field of object-based image analysis. Following the approach presented in this paper, 19 hotspots with most severe climatic changes were identified, evaluated, and mapped. The method enables not only the prioritization of intervention areas, but also allows decomposing the identified hotspots into their underlying subindicators, and thus additional information for effective climate change adaptation measures can be provided.