Understanding the effects of socio-ecological shocks on land use/land cover (LULC) change is essential for developing land management strategies and for reducing adverse environmental pressures. Our study examines the impacts of the armed conflict in Syria, which began in mid-2011, and the related social and economic crisis on LULC between 2010 and 2018. We used remote sensing for change detection by applying a supervised maximum likelihood classification to Landsat images of the three target years 2010, 2014, and 2018.

Connectivity and wildlife corridors are often key components to successful conservation and management plans. Connectivity for wildlife is typically modeled in a static environment that reflects a single snapshot in time. However, it has been shown that, when compared with dynamic connectivity models, static models can underestimate connectivity and mask important population processes. Therefore, including dynamism in connectivity models is important if the goal is to predict functional connectivity.

Globally, coastal communities are impacted by hazards including storm events, rising water levels, and associated coastal erosion. These hazards destroy homes and infrastructure causing human and financial risks for communities. At the same time, the economic and governance capacity of these communities varies widely, impacting their ability to plan and adapt to hazards. In order to identify locations vulnerable to coastal hazards, knowledge of the physical coastal changes must be integrated with the socio-economic profiles of communities.