Integrating remote sensing and modeling to assess land use changes and carbon dynamics in the Indian Himalayas

The Himalayan region is experiencing evident climate change and increasing human interventions, leading to rapid alterations in land use and ecosystem balance, which highlights the necessity for sustainable planning using geospatial technology. Therefore, this study utilised satellite imagery (Landsat series) and Google earth engine to analyze decadal land use dynamics (2003, 2013, 2023) using the random forest algorithm and carbon storage data from Hamirpur district of the Indian Himalayas. The findings indicated significant shifts in land use over the two decades: the vegetation cover declined from 67% in 2003 to 61% in 2023, followed by a decrease in barren land from 2.6% to 1.8%, while waterbodies remained relatively constant at around 0.5%. In contrast, built-up areas increased notably from 4.3% to 7.1%, grasslands nearly tripled from 1% to 2.7%, and agricultural land showed a slight overall increase, stabilizing around 27%. Future land use projections using the CA–Markov model indicated a gradual decline in vegetation cover (0.83%) and a steady increase in built-up areas (6.25%), while other land cover classes are expected to remain relatively stable over time. The carbon storage estimation using the InVEST model indicated carbon variation from 0 to128 Mg ha^-1, and there was a decline in areas with very high carbon levels (6%) and an increase in medium and high carbon classes. Overall, the observed changes in land use dynamics and a decline in areas with very high carbon storage in the region highlight the need for integrated land management practices, including afforestation, controlled urban expansion, and the conservation of existing green cover to ensure sustainable development and enhanced carbon sequestration.