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Forests cover almost one-third of the Earth's land surface. Tropical dry forests are the second-most-important forest type in the world covering approximately 42% of tropical and sub-tropical forest area. The main features of these forests are their deciduousness, a prolonged dry period extending 3-9 months, and little annual precipitation of 250-2,000 mm. Tropical dry forests are found in five of the eight realms in the world. More than half of the forests are distributed in the Americas, with other portions in Africa, Eurasia, Australia, and Southeast Asia. The forests are unique in nature, and provide shelter to a huge number of endemics and endangered species. Among woody plant species, about 40% are not found anywhere in the world. These forests are now the most threatened among all forest types. The conservation status of these forests is endangered. Deforestation, rapid civilization, land conversion, fire, and climate change are the major threats. Proper management with time-oriented policy could be helpful to restore these forests and protect the existing remnant areas.

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Forest cover change is an important criterion as it affects the environmental balance whereas land surface temperature is a significant parameter within the earth climate system. Spatio-temporal change of forest cover can be detected and land surface temperature can be retrieved by applying remote sensing technology. The present study aimed to capture the impact of forest cover change on land surface temperature in Dudpukuria-Dhopachari Wildlife Sanctuary (DDWS), Bangladesh, using multi-spectral and multi-temporal satellite data. To avoid the biasness in the calculation, leaf flash time was targeted for collecting Landsat images from United States Geological Survey (USGS) Earth Explorer and, based on availability, images were collected purposively which ones had closer time period:1990 (March 5, 1990), 2000 (February 5, 2000), 2010 (February 24, 2010) and 2020 (March 23, 2020). Unsupervised classification was applied over the images Landsat 4–5 Thematic Mapper (TM), 7 Enhanced Thematic Mapper Plus (ETM+), and 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data for detecting forest cover change. To retrieve the land surface temperature, Mono Window Algorithm (MWA) method was applied over similar images. Maximum forest degradation was observed in 2010 and the change found was 17% as compared to 1990. After 2010, the forest started to flourish. Land surface temperature dramatically changes over the time period. The highest land surface temperature in the forested area was observed in 2020 (32.2°C) and it was changed 7.7°C from that of the 1990 (24.5°C). In every 10 years, almost 2.3°C–3.0°C temperature change was detected. In the first three decades, a reverse relationship was observed between land surface temperature and forest cover; however, in the last decade, land surface temperature was found to increase with the increase of forest cover. Thus, the results of the study revealed that land surface temperature may not be relevant with the local forest cover change directly. It can be estimated from the results that local forest cover change may have limited impact on local temperature rather than global forest cover change, whereas global warming could play a vital role in changing land surface temperature locally as well as globally.