HeatAdapt: Heat stress monitoring supporting Austrian climate change adaptation strategies

Most of the largest cities experience profound changes due to urbanization and hence, city administrations are facing challenges in order to safeguard high quality urban growth despite increasingly tight spatial resources. Modifications in the built up environment increase the temperature of cities compared to their surroundings and are more prone to excess heat. Moreover, climate change in general and the increasing temperatures in particular pose a particular risk for mountainous areas affecting alpine communities and their economy.

• Health Heat induces stress on the human body, particularly dangerous for infants and elders
• Urban planning : Urban heat island effect, Heat related health issues; energy systems strain (e.g. more air conditioning)
• Infrastructure : increased cost & environmental burden , street and pavement lifetime (cracks, softening, etc.) etc.), maintenance and repair
• Agriculture : Irrigation crop health issues ,act.

Taking action in terms of adaptation is not only the focus of larger cities but also of any growing built up or settlement area as well as mountain region. Understanding how land use and climate trends lead to changes to the local climate is essential for decision makers to find optimally cost effective, evidence based, and consistent solutions for sustainable cities but also for communities in rural or mountainous areas.

The project HeatAdapt combines Land use and Land Cover (LULC) and climate data to demonstrate the effect of urbanization or other LULC changes on ambient temperatures and supports the location of other heat related hotspot areas in rural and mountainous regions at high spatial resolution. Making use of regional clim ate model (RCM) based scenario data will further allow to assess future expected areas for which adaptation actions will be required (e.g., greening activities) allowing city administrations and municipalities to plan ahead (e.g., demonstrate effect of additional soil sealing). HeatAdapt uses artificial intelligence (AI) and multi sensor data fusion methodologies to develop a prototype algorithm for monitoring land surface temperature (LST). Further, climate scenarios are fused with the model, enabling AOI based scenario analysis factoring in LULC changes. HeadAdapt will provide statistical outputs of proposed indicators per administrative unit (province, district, municipalities, census units) and will allow for a statistical evaluation of relation between LULC composition and temperature indicators and potential demonstration of effects changing LULC composition . The project is part of the GTIF demonstrator (Green Transition Information Factory), focusing on Austria to explore Green Transition pathways. For further information, please contact sammer@geoville.com