Integrating Geospatial Intelligence and Community Knowledge to Assess Climate Risks in Mountain Social Ecological Systems of Northern Pakistan

 

Northern Pakistan’s mountain regions are changing quickly under climate change. Rising temperatures, shifting rainfall, and more frequent extreme events are increasing landslides, flash floods, glacial lake outburst floods, and related hazards. At the same time, communities are expanding into more exposed locations, often without reliable data or early warning systems. In many high elevation valleys, environmental monitoring is minimal or absent, which makes safe planning and climate adaptation difficult.

In response, AI Geo Navigators developed a practical geospatial tool and tested it in Gilgit Baltistan, Swat, and Chitral. The approach combines freely available satellite imagery, digital elevation models, drone surveys, and open datasets to map multiple, overlapping risks. These include unstable slopes, flood prone areas, proximity to seismic zones, and locations affected by past disasters. The hazard information is analysed together with settlement locations, roads, agricultural land, and surrounding ecosystems to better understand who and what is exposed.

A central part of the work was direct engagement with local communities. Rather than relying only on desk based analysis, field visits, mapping sessions, and conversations with residents were used to document past flood paths, landslide zones, and land use changes that are not visible in satellite data alone. This local knowledge helped correct gaps in the remote analysis and grounded the results in lived experience.

The results show that combining low cost geospatial tools with community input produces a much clearer and more realistic picture of risk in complex mountain terrain. The approach supports safer settlement planning, climate adaptation efforts, and improved local risk communication in areas where official monitoring and warning systems remain weak. It demonstrates that meaningful climate risk assessment in mountain social ecological systems does not require large budgets, but does require integration of technology with people who know the landscape best.