###### Abstract  
Pakistan has an annual deforestation rate of 4.6% which is the second highest in Asia. It has been described by the Food and Agriculture Organization (FAO) that the deforestation rate increased from 1.8-2.2% within two decades (1980-2000 and 2000-2010). KPK (Khyber Pakhtunkhwa), Pakistan's northwestern province, holds 31% of the country's total forest resources, the majority of which are natural forests. The Malam Jabba region, known for its agro-forestry practices, has undergone significant changes in its agricultural, forestry, and urban development. Agricultural and built-up land increased by 77.6% in the last four decades, and significant changes in land cover especially loss in forest, woodland, and agricultural land were observed due to flood disasters since 1980. For assessing and interpreting land-cover dynamics, particularly for changes in natural resources such as evergreen forest cover, remote sensing images are valuable assets. This study proposes a framework to assess the changes in vegetation cover in the Malam Jabba region during the past four decades with Landsat time series data. The random forest classifier (RF) was used to analyze the forest, woodland, and other land cover changes over the past four decades. Landsat MMS, TM, ETM+, and OLI satellite images were used as inputs for the random forest (RF) classifier. The vegetation cover change for each period was calculated from the pixels using vegetation indices such as NDVI, SAVI, and VCI. The results show that Malam Jabba's total forest land area in 1980 was about 236 km\({}^{2}\) and shrank to 152 km\({}^{2}\) by 2020. The overall loss rate of evergreen forests was 35.3 percent. The mean forest cover loss rate occurred at 2.1 km\({}^{2}\)/year from 1980 to 2020. The area of woodland forest decreased by 87 km\({}^{2}\) (25.43 percent) between 1980 and 2020. Other landcover increased by 121% and covered a total area of 178 km\({}^{2}\). The overall accuracy was about 94% and the value of the kappa coefficient was 0.92 for the change in forest and woodland cover. In conclusion, this study can be beneficial to researchers and decision makers who are enthusiastic about using remote sensing for monitoring and planning the development of LULC at the regional and global scales. L 11 January 2023 15 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1858 1859 1859 1860 1870 1871 1888 1889 1889 1890 1891 1892 1893 1894 189 capturing carbon dioxide [2]. Being the second-largest source of carbon dioxide emissions (10-25 percent globally), deforestation has wide-ranging environmental and socioeconomic implications [3; 4]. Deforestation and forest exploitation can result in the release of CO\({}_{2}\) upwards into the Earth's atmosphere, affecting the global climate and influencing ecological change [5]. Dense trees occupying areas larger than 5 hectares in size, with trees larger than 5 m in height, and covering no less than 10% of the canopy is known as forest land [6]. This excludes most agricultural land and densely populated areas [7]. An area is classified as \"Other woodland\" if it contains more than 0.5 hectares and has a canopy cover of 5-10 percent or has trees taller than 5 m or a total cover of bushes, shrubs, and trees larger than 10 percent. It excludes area which is primarily used for agricultural purposes or for urban purposes. Shrubland, scattered woody trees, grassland, barren land, agricultural land, and others are defined as other land cover [8]. Deforestation is the process of converting forest land into another type of usage or reducing the tree canopy permanently below a level of 10% [7]. Disturbance, overuse, other anthropogenic activities, or shifting environmental circumstances, all contribute to deforestation when forest cover is reduced to less than 10% [9]. For this, reforestation or aforestation are highly needed.