LST-R: A method for assessing land surface temperature reduction in urban, hot and semi-arid Global South.

Over the next 30 years, temperatures are expected to increase in hot semi-arid zones. Despite increasing studies on urban heat, cooling measures suitable for this climate zone remain poorly investigated. The proposed method is innovative because it focuses on significant landscape metrics for determining the land surface temperature (LST) and evaluating cooling measures.

Dataset on the expansion and consolidation of flooded settlements in the Dosso Region, Niger.

Flood risk reduction at the local scale requires knowledge of the settlements which are most exposed to floods, and those where the existing measures are insufficient to handle the threats. The knowledge on spatial dynamics of the flooded human settlements is limited, especially that of the smaller ones, such as the settlements in the sub-Saharan Africa. The dataset on 122 flooded settlements in the Dosso Region (Niger) offers information on: the built-up area and the number of buildings with corrugated iron roofs in 2004, 2012, and 2019 (average dates), the type of human settlements (city, rural town, village, or hamlet), the flood dates and the number of buildings collapsed between 2011 and 2019.

Method for pluvial flood risk assessment in rural settlements characterised by scant information availability.

In tropical regions, heavy precipitations may lead to catastrophic flooding due to the degradation of catchments and the expansion of settlements in flood prone zones. In the current situation, where information on rainfall and exposed assets is either scant, or requires significant time to be collected, pluvial flood risk assessments are conducted using participatory tools, without any scientific support. Another option is to use satellite precipitation products, digital terrain models and satellite images at high to moderate-resolution.