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Abstract Background Tropical forests have been experiencing remarkable rates of transformation over the past century as they are getting degraded or decimated to a great extent by anthropogenic activities. This study aims at investigating the long-term forest cover transformation in Palamau Tiger Reserve (PTR), Jharkhand, India, using Landsat TM, ETM+, and OLI satellite images during 1975–2015. The forest cover was delineated utilizing various keys of visual interpretation techniques. Results The forest cover was primarily decreased in the north-eastern and north-western parts in PTR. In order to identify the anthropogenic disturbance in the forest reserve, human settlement density was mapped using high-resolution Google Earth imagery. The results showed a positive correlation between human population density and settlement density. Five major affected sites with an outer buffer of 2 km were demarcated in order to deduce the anthropogenic influences in major non-forested sites in PTR. It was observed that the forest change was maximum at site 3 (Ranidah, area 61.06 km2, − 6.47% change) followed by site 2 (Saidup, area 124.38 km2, − 7.65% change), where settlement units were also high (2638 and 2621 settlement units, respectively). At site 1 (Barkheta, area 81.59 km2), − 1.99% change was observed, and at site 4 (Samadh Tola, area 9.15 km2), 1.03% change was observed having moderate settlement units (2422 and 1892 settlement units, respectively). Areas with the low level of human settlements (1038 settlement units) observed the least change, i.e., at site 5 (Netarhat, area 48.52 km2), 0.58% change was observed mainly during the years. Conclusions The forest cover exhibited an overall decrease of 14.55 km2 (− 1.34% change) with episodic variation during 1975–2015 in PTR, Eastern India. A significant forest disturbance occurred primarily in the north-eastern and north-western parts of PTR along the forest fringe due to the high population and settlement density. The study highlighted the potential use of freely available multi-temporal satellite observations in forest management. |
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