Integration of climate change adaptation measures into spatial planning using data-based methods
Initial situation/motivation
Over the last ten years, green and blue infrastructure (GBI) in cities has evolved from a leisure and recreational function to a key lever in the fight against climate change and biodiversity loss. International, national and local strategies emphasize the need to integrate GBI more strongly into municipal planning. Despite the rapidly increasing amount of available geo-referenced data on climate risks, decision-making in administration and planning remains difficult. This is due to a lack of standardized indicators, uncertainties about the effects of GBI and the lack of clear framework plans for risk minimization. A data-supported, evidence-based approach, as envisaged in this project, could considerably facilitate and accelerate the implementation of local and regional climate protection measures.
Contents and objectives
To date, local planning practice has lacked a spatial approach that not only provides low-threshold information on climate-related hazards, but also offers concrete, scientifically sound proposals for measures in the area of green and blue infrastructure based on an up-to-date empirical data model. The aim of the project is to close this gap by developing a digital, data-based model that links locally existing climate risks with suitable, concrete GBI measure proposals. This should reduce uncertainties in planning and accelerate the implementation of local climate adaptation measures. In addition, previously unresolved questions on quantifying the effects of GBI measures will be supplemented by empirical data and broad consensus solutions among cities, municipalities and spatial planners in an innovative approach.
Methodical approach
The methodology includes the research and analysis of available georeferenced terrestrial and satellite data on climate risks and existing green and blue elements, the creation of climatope and climate function maps and the identification of local climate risk zones. Based on this data, a decision model is developed that proposes suitable GBI measures for specific risk zones. The measures are evaluated in a matrix according to effectiveness, complexity of implementation and other parameters and assigned to specific spatial planning instruments. Finally, the fields of action and measures are visualized on a WebGIS platform. In addition, stakeholder perspectives are incorporated through workshops and test runs.
Expected results
The project aims to provide proof of concept for a WebGIS-based visualization tool that supports local planning authorities and decision-makers in the selection of suitable GBI measures. This tool will provide geospatial and evidence-based suggestions to implement climate adaptation measures at the municipal level in a faster and more targeted way. In addition, the project is expected to provide valuable insights on climate risk-relevant geodata and combined decision models, which will provide the involved decision-makers with an important information leap in the field of climate change adaptation.
Project management: AEE – Institute for Sustainable Technologies
