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

Figure 1

Figure 1
Base map showing the geographical focus of the study.

Figure 2

Figure 2
IPCC SREX disaster risk framework [6].

Figure 3

Figure 3
Constructing spatial composite indicators following the geon concept: different normalized (sub-) indicators Formula$({\rm SI}_{1},\ldots,{\rm SI}_{\rm n})$ are aggregated by making use of regionalization techniques. Following this approach, the resulting units (or geons) are homogeneous in terms of the phenomenon under investigation (based on [15] and [18]).

Figure 4

Figure 4
CCCI in the Sahel and western Africa based on the aggregation of a set of four climate-/hazard-related subindicators (i.e., temperature, precipitation, drought, and flooding). Hotspots are displayed in red color.

Figure 5

Figure 5
Visualization in ArcGIS Explorer Online. This allows not only visualizing the CCCI, but also the share of the underlying subindicators per geon (unit).