Geospatial assessment of intrinsic resilience to the climate change for the central coast of Bangladesh

Abstract

Climate change resilience not only depends on the physiographic properties, but also the socio-economic status of the people. Considering climate change resilience as a socio-ecological construct, few attempts have been taken to measure resilience across the space, especially at national and community scales. There is a paucity of research that contributes to the spatial understanding of climate change resilience at local level from the system approach. This study aims to provide an assessable means through an analytical geospatial exercise of intrinsic resilience of a socio-ecological system in the context of climate change scenario. Due to the unique physiographic and geomorphological characteristics, the central coast of Bangladesh has already been termed as one of the most climate change vulnerable hotspots by the International Panel on Climate Change (IPCC). Therefore, it demands a comprehensive assessment in terms of climate change vulnerability, adaptive capacity and resilience. We investigated the intrinsic resilience of this region by adopting Climate Change Resilience of Place (C-CROP) model. This study is the first attempt to the implication of the C-CROP model in real world scenario. Remote Sensing based earth observation, census, and ancillary data were in the centre of the investigation while Principal Component Analysis (PCA) was employed to select and weigh bottom level indicators. 20 adaptive capacity indicators and 17 vulnerability indicators were selected in this regard. Using PCA, 37 indicators are reduced to 5 adaptive capacity and 3 vulnerability principal components which explain 73.81% and 79.17% variance in the data respectively. Quantification and mapping of intrinsic resilience through geospatial approach using Google Earth Engine (GEE) provide useful data that show how intrinsic resilience is spatially distributed in the most vulnerable hotspot in the climate change context. The findings of the study can contribute to climate change adaptation and disaster risk reduction programs to sustainably allocate limited resources and set priority interventions in order to build vulnerable communities resilient in changing climatic scenario.