Quantifying Land Use Changes and Carbon Stock Degradation in Ayubia National Park Using Application of Markov Chain Model

Land use land cover change(LULCC) plays a significant role in understanding of global change. Particularly in regions with high population growth and climate change, anthropogenic activities have drastically altered land use and land cover (LULC). This study examines land use and land cover change (LULCC) in Ayubia National Park, located in the Himalayan foothills of Khyber Pakhtunkhwa. This study utilized Landsat satellite imagery from 1992, 2002, 2012, and 2022 to analyze patterns of land use change and quantify the resulting carbon loss over time. To project future land cover transitions and assess landscape dynamics, the Markov Chain model was em-ployed. This probabilistic modeling framework enabled the quantification of transition probabil-ities between land cover classes and facilitated predictive mapping of LULCC trajectories. The park was categorized into five land cover classes: grassland, built-up areas, mixed forests, conifer forests, and bare land. The analysis revealed that 371.94 hectares of forest land were converted to other uses between 1992 and 2022, indicating increased anthropogenic pressure on forest re-sources. Carbon stock assessments showed that temperate coniferous forests (TCF) had a carbon value of 135.19 ±9.74 MgC ha⁻¹, while mixed forests (MF) had 86.43 ±8.25 MgC ha⁻¹. The decline in carbon values is attributed to deforestation and development. The study underscores the need for sustainable forest management policies to mitigate the impact of land use changes and preserve carbon stocks in the western Himalayan region of Pakistan.