The increasing convergence of demographic ageing and climate-induced hazards presents a complex planning challenge for Pakistan. Older populations are disproportionately vulnerable to extreme heat, floods, and glacial hazards due to limited mobility, higher prevalence of chronic illness, and reduced adaptive capacity. Therefore, the Planning Commission of Pakistan must transition from generalized vulnerability assessments to granular, spatially explicit profiling of high-risk ageing populations, embedded within national development and resilience planning frameworks.

1. Integrating Multi-Hazard Spatial Risk Mapping with Demographic Ageing Data
A critical first step involves the development of multi-layered spatial risk atlases that integrate hazard exposure (heatwaves, floods, glacial lake outburst floods) with age-disaggregated population data. Pakistan is already highly exposed to multiple hazards including extreme heat, floods, and glacial melt requiring district-level multi-hazard mapping to identify vulnerable regions .
The Planning Commission can institutionalize this through:
Overlaying National Socio-Economic Registry (NSER) or census data (age cohorts 60+) with hazard maps.
Developing “Ageing Vulnerability Hotspot Maps” at tehsil or union council level Integrating spatial datasets into planning tools such as PC-1 appraisal and PSDP prioritization. Such integration ensures that ageing populations in floodplains (e.g., Sindh, KP river basins), heat-prone cities, and glacial regions (Gilgit-Baltistan) are explicitly identified in planning processes.
2. Leveraging Geospatial Technologies and Remote Sensing
Recent advances in geospatial science offer powerful tools for high-resolution spatial profiling. Studies demonstrate that combining satellite imagery (e.g., Sentinel, Landsat) with population datasets enables precise identification of populations exposed to floods and infrastructure risks .
The Planning Commission should establish a National Geospatial Vulnerability Platform integrating remote sensing, GIS, and AI-based population disaggregation. Utilize 30m–100m resolution population grids to identify elderly populations in hazard-prone zones. Partner with institutions such as SUPARCO and universities for real-time spatial analytics. This would significantly improve the precision of targeting, moving beyond district-level averages to micro-spatial planning.
3. Urban Heat Risk Profiling for Ageing Populations
Urban centers in Pakistan are experiencing intensified Urban Heat Island (UHI) effects due to rapid urbanization. For instance, Rawalpindi has witnessed a steady rise in land surface temperature linked to expanding built-up areas and limited vegetation. Heatwaves disproportionately affect older persons, with evidence showing elevated mortality among elderly populations in dense urban environments.
Policy actions should include mapping heat exposure + elderly population density to identify thermal vulnerability clusters.
Integrating green infrastructure planning (urban forests, cooling corridors) in high-risk zones.
Developing heat-health early warning systems tailored to elderly populations.
This aligns spatial planning with public health resilience, a critical but often overlooked dimension.
4. Floodplain and Coastal Vulnerability Mapping
Flood risks, particularly in Sindh, KP, and coastal cities require spatial profiling that links hydrological exposure with demographic vulnerability. Evidence shows that integrating flood maps with population and infrastructure data allows policymakers to identify the proportion of exposed populations and critical assets .
The Planning Commission can strengthen this by identifying elderly populations in flood-prone districts (e.g., Indus basin, Karachi’s low-lying areas). Incorporating climate-induced displacement risk into spatial planning is also crucial. Aligning PSDP investments toward climate-resilient housing and evacuation infrastructure is central. Furthermore, urban areas such as Karachi face compounded risks from coastal flooding, heatwaves, and dense informal settlements, making spatially targeted interventions essential.
5. Profiling Glacial and Mountain Vulnerability
Northern Pakistan’s glacial regions face increasing risks from glacial lake outburst floods (GLOFs) and extreme temperature variability. Spatial monitoring studies highlight the importance of spatio-temporal mapping of glacial hazards for risk identification and early warning.
Planning responses should include, mapping ageing populations in high-altitude, remote communities
integrating GLOF risk layers with settlement and demographic data, and prioritizing accessibility (roads, health services) in isolated ageing communities. Recent climate events demonstrate how accelerated glacial melt and extreme heat can trigger catastrophic floods, particularly in northern regions .
6. Institutionalizing Spatial Ageing Metrics in Planning Frameworks
To ensure sustainability, spatial profiling must be embedded within institutional processes. Introduce “Age-Sensitive Spatial Planning Indicators” in PC-1 and PSDP evaluation and make mandatory age-disaggregated spatial data reporting across ministries. Aligning with National Climate Change Policy and SDG localization frameworks is also important. This would move Pakistan toward evidence-based, intersectional planning, where ageing is integrated alongside gender, poverty, and climate vulnerability.
7. Toward an Integrated Intersectional Spatial Framework
Finally, the Planning Commission should adopt a multi-dimensional vulnerability index combining age (elderly population density), climate exposure (heat, floods, glaciers), socio-economic status (poverty, housing conditions), and accessibility (healthcare, transport, early warning systems). Such an approach would enable prioritization of “compound risk zones”, where ageing populations face overlapping vulnerabilities.
Conclusion
Strengthening spatial profiling of high-risk ageing populations requires a paradigm shift from static, sectoral planning to dynamic, data-driven, and spatially integrated governance. By leveraging geospatial technologies, embedding demographic sensitivity into planning instruments, and adopting a multi-hazard framework, the Planning Commission of Pakistan can significantly enhance climate resilience, social protection targeting, and inclusive development outcomes. This transition is not merely technical but institutional, requiring coordination across planning, climate, health, and social protection systems to ensure that ageing populations are no longer invisible within Pakistan’s development landscape.