P lanning for sustainable economic, social, environmental, and land resources are critical because of population growth and global climate change (Ashraf, 2020;Matin et al., 2019). Due to the enormous burden of agriculture and urbanization, various human activities are underway to use the earth's natural re-sources, which are decreasing rapidly. Therefore, remote sensing satellite data are shown to be very useful for the analysis and mapping of land cover (Lasko et al., 2018;Levizzani et al., 2019). Even if the resulting spatial dataset has different resolutions, this change can be monitored using a GIS approach (Giuliani et al., 2020;Munsi et al., 2010). It is essential to fill in the literature about land use and land cover changes Abstract | In the sustainable management of natural resources, land use and land cover (LULC) changes play an essential role. Pakistan is rich in biodiversity and provides ecosystem services to the country's population, especially the mountains of the northern highland. These areas have experienced extensive depletion of ecosystem services and are susceptible to fast LULC changes. Real-time monitoring and assessment based on spatio-temporal are important to know such LULC changes. This study examines LULC in the northern mountains of Pakistan from MODIS (MCD12Q1) time series from 2001 to 2018. LULC was classified into ten significant classes. Findings of the data revealed that shrublands (0.33-0.17%), grasslands (45.83-41.74), and cropland (12.71-10.47) were decreased significantly. At the same time, savannas, permanent wetlands, urban and built-up lands, natural vegetation, permanent snow and ice, and barren lands increased substantially over the entire period. Due to the lack of baseline data, the LULC map will play an essential role in the sustainable management of LULC in the Hindu Kush, Karakoram and Himalayan regions of Pakistan. For the sustainable maintenance of the mountainous ecosystem, comprehensive research is recommended about these LULC vulnerabilities locally and regionally.