The role of population data in urban ecosystem service assessment: A case stdy of microclimate cooling in Prague
Abstract
Green areas, providing benefits of cooling the surrounding environment, are usually not distributed equally in urban space, which leads to some people benefiting more from ecosystems' cooling abilities and some people left exposed to higher levels of heat stress. Population data have been widely used as an indicator for estimating benefits of and needs for ecosystem services, including microclimate cooling.
However, the spatial and temporal resolution and demographic and socio-economic information of population data can largely determine the results of assessments. Few studies have used people's movement as an indicator for heat exposure throughout a day, which revealed the different levels of heat stress depending on a person's daily route.
This has not been employed in ecosystem service assessment of urban cooling and could have important implications for an equitable spatial planning in the context of climate change increasing the magnitude and frequency of extreme temperature events. We address these issues by exploring the differences in urban microclimate cooling realised benefits and unsatisfied needs, while employing residential data (static) and diurnal intra-urban population movement data (dynamic) on a census unit and a building scale on a case study of Prague, Czechia.
We used InVEST Urban cooling model to estimate the provision of cooling and coupled it with the need for cooling, represented by the levels of heat stress based on the Wet Bulb Globe Temperature, also accounting for vulnerabilities of various socio-economic groups and places. The results show areas where people benefit from ecosystem cooling and where they are exposed to extreme temperatures in static and dynamic model, census unit and building resolution, daytime and night-time.
Besides identifying the areas for microclimate improvement for a specific case study, the research enhances the understanding and use of population data in urban ecosystem service assessments and stresses the significance of how data and indicator selection alter the results that could be later picked up by decisionmakers for spatial planning.