Developing a Spatially Explicit Forest Database for Planning and Carbon Stock Estimation: A GIS-based Approach in Rajgarh Forest Division of Sirmaur District, Himachal Pradesh, India

Abstract

The conventional method of forest plan preparation cannot provide real-time forest inventory data, making planning inefficient. It struggles with data synthesis, retrieval, and reliability due to scattered sources. GIS addresses these challenges by efficiently storing, retrieving, and analyzing spatial and non-spatial data, enhancing precision, objectivity, and cost-effectiveness in forest management. This study aimed to develop a comprehensive forest resource database and spatial analysis of growing stock and carbon stock for Rajgarh Forest Division in Sirmaur district, Himachal Pradesh located between 30° 38’40” to 31° 01’14” N latitude and 77°01’5” to 77°26’13”E longitude, at an elevation ranging from 500 m to 3500 ma.s.l. Maps and toposheets from the Rajgarh Forest Division were scanned, georeferenced and digitized in ArcMap. Key features such as forest boundaries, roads, rivers, compartments, and land uses were digitized, and a GIS database was created. Forest attributes, including area, vegetation types, working circles, and growing stock, biomass and carbon stock were entered into the database. Thematic maps were prepared, and growing stock and carbon stock distribution were analyzed across different forest units using GIS-based extrapolation of enumerated sampling data. The Rajgarh Forest Division consists of six working circles, four ranges, 879 compartments, and 41 beats. A small to very small variation in the area of management units, forest vegetation, and land uses was observed compared to the reported Working Plan. The total growing stock and carbon stock were estimated at 7.05×10⁶ m³ and 3.29×10⁶ t, respectively. The contribution of different forest ranges to total growing stock and carbon stock was: Habban (71.98% and 67.85%), Rajgarh (19.72% and 22.59%), Narag (4.03% and 5.06%), and Sarahan (4.27% and 4.50%). Among the working circles, Chil Shelterwood, Deodar-Kail, Rehabilitation, Plantation, Protection, and Selection contributed 8.98% & 9.15%, 31.37% & 28.44%, 6.45% & 7.73%, 2.47% & 2.57%, 15.13% & 21.66%, and 35.59% & 30.45% to the total growing stock and carbon stock, respectively. Among the forest vegetation types in Rajgarh Forest Division, the highest growing stock was recorded in Oaks (1.79×10⁶ m³), followed by Deodar (1.79×10⁶ m³), Spruce (1.43×10⁶ m³), and Chil (8.53×10⁵ m³), with the lowest in Bamboo (9.26×10² m³). Carbon stock was highest in Oaks (1.41×10⁶ t), followed by Deodar (6.32×10⁵ t) and Spruce (4.08×10⁵ t), while Bamboo had the lowest (4.14×10² t). The study highlights the utility of GIS in forest management, emphasizing its role in database development and forest inventory analysis. The results provide a critical foundation for sustainable forest planning, resource allocation, and conservation strategies in the Rajgarh Forest Division.