International Journal of Research and Scientific Innovation (IJRSI)
Bridging the Urban Climate Evidence-to-Action Gap: Introducing the Geospatial Urban Climate Adaptation and Resilience Decision-Support Framework (GUCAR-DSF)
Published July 21, 2026 • Vol. 13, Issue 6, pp. 6844–6864Open Access
DOI: 10.51244/IJRSI.2026.1306000513
Abstract
Rapid urbanisation, climate change, land-use transformation, ecosystem degradation, infrastructure deficits, and social inequality are intensifying complex and spatially uneven climate risks in cities. Although advances in remote sensing, Geographic Information Systems, Earth Observation, vulnerability assessment, resilience planning, and adaptive governance have improved the capacity to understand urban climate risk, these capabilities are often applied through fragmented analytical and institutional systems. As a result, hazard mapping may remain disconnected from vulnerability assessment, adaptation planning from implementation, governance from spatial evidence, and monitoring from future decision-making. This creates a persistent evidence-to-action gap in climate-resilient urban planning. This paper introduces the Geospatial Urban Climate Adaptation and Resilience Decision-Support Framework (GUCAR-DSF) as an integrative evidence-to-action framework for supporting climate-resilient urban planning. Developed through structured interdisciplinary evidence synthesis, the framework draws on resilience thinking, social-ecological systems, adaptive governance, geospatial intelligence, and multi-hazard risk perspectives. It connects eight interdependent functions: climate and environmental observation; geospatial intelligence and indicator generation; multi-hazard diagnostics; vulnerability and adaptive-capacity assessment; adaptation appraisal and prioritisation; governance, participation and implementation; monitoring, evaluation and adaptive learning; and decision-support communication and scaling. The central innovation of GUCAR-DSF lies in its continuous evidence-to-action cycle, in which implementation generates new knowledge and monitoring informs renewed observation, analysis, prioritisation, and institutional adjustment. The framework supports spatially targeted, socially differentiated, and continuously evaluated adaptation across risks such as urban heat, flooding, compound hazards, land-use change, ecosystem degradation, informal-settlement vulnerability, critical infrastructure exposure, and Nature-Based Solutions. Its modular design makes it relevant to both data-rich and resource-constrained contexts, particularly rapidly urbanising cities in the Global South. As a conceptual framework, GUCAR-DSF requires empirical validation, comparative testing, and longitudinal assessment. It therefore provides a foundation for future empirical testing, pilot implementation, and comparative urban resilience research.
Keywords: GUCAR-DSF; urban climate adaptation; geospatial intelligence; climate resilience; multi-hazard risk; vulnerability assessment; evidence-to-action; adaptive governance
| Journal | International Journal of Research and Scientific Innovation (IJRSI) |
|---|---|
| ISSN | 2321-2705 |
| Volume / Issue | Volume 13, Issue 6 |
| Pages | 6844–6864 |
| Publication date | July 21, 2026 |
| DOI | 10.51244/IJRSI.2026.1306000513 |
| Publisher | RSIS International |
| License | Open Access |
How to cite this article
Garba T (2026). Bridging the Urban Climate Evidence-to-Action Gap: Introducing the Geospatial Urban Climate Adaptation and Resilience Decision-Support Framework (GUCAR-DSF). International Journal of Research and Scientific Innovation (IJRSI), 13(6), 6844-6864. https://doi.org/10.51244/IJRSI.2026.1306000513
BibTeX
@article{Garba2026,
title = {Bridging the Urban Climate Evidence-to-Action Gap: Introducing the Geospatial Urban Climate Adaptation and Resilience Decision-Support Framework (GUCAR-DSF)},
author = {Garba T},
journal = {International Journal of Research and Scientific Innovation (IJRSI)},
volume = {13},
number = {6},
pages = {6844--6864},
year = {2026},
doi = {10.51244/IJRSI.2026.1306000513},
publisher = {RSIS International}
}