Climate shocks and sustainable future development; a case of Murree tourist destination

Mountain tourism destinations face compounding threats from climatic variability, vegetation degradation, and surging visitor demand, yet integrated operational governance frameworks remain rare in the Global South. Murree, Pakistan’s premier Himalayan hill station, exemplifies this urgency: the 7–8 January 2022 snowstorm claimed 23 lives, exposing failures in early warning, capacity management, and coordination. This study addresses the gap by integrating high-frequency climate diagnostics, satellite-derived vegetation metrics, and a behavioral attention proxy into a unified analytical framework that yields empirically grounded recommendations. Using a weekly panel (April 2016–March 2022) for Murree and three regional comparators (Federal, Punjab, Sindh), we test variance shifts in temperature and relative humidity, map seasonal NDVI from cloud-masked Landsat 8/9 composites, and model Google Trends intensity via ARMA. Results show Murree is cooler (mean 20°C) and more humid (mean 70%) than lowland sites, with post-2019 widening of weekly temperature dispersion consistent with elevation-dependent warming. Forest cover declined from ~71% (1988) to 66.5% (2018) while built-up area expanded nearly eightfold (1.3%→9.5%); persistent low-NDVI anomalies concentrate along settlement and road corridors. An ARMA model explains 58% of search-intensity variance (R² = 0.58), confirming strong seasonality and event-driven spikes. A chi-square test (p = 0.04) indicates a significant association between climate anomalies and deforestation outcomes. This advances mountain-tourism scholarship by showing how multi-source high-frequency data can support real-time risk governance and offers a transferable model for similarly exposed Himalayan destinations.