Carbon Stock Assessment of Law Kyntang Ryngkew Swer Sacred Grove, East Khasi Hills, Meghalaya: A GIS and NDVI-Based Approach

Abstract

Sacred groves maintained by traditional indigenous laws in Northeast India act as crucial biodiversity havens and important carbon sinks. This research assessed the biomass and carbon storage of the Law Kyntang Ryngkew Swer Sacred Grove in the East Khasi Hills of Meghalaya by integrating systematic field surveys with remote sensing and geospatial methods. Fifteen quadrats measuring 38.4 × 38.4 m were set up to document species diversity, diameter at breast height, and tree height. Aboveground biomass (AGB) was estimated through the allometric equations from Chave et al. (2014) designed for humid tropical forests, while belowground biomass (BGB) was calculated using recognized biomass relationships. The carbon stock was determined using the IPCC (2021) conversion factor of 0.47. High-resolution LISS-IV imagery was analyzed to derive the Normalized Difference Vegetation Index (NDVI), which was then linked to biomass through regression modeling to create spatial carbon maps. The findings indicated significant carbon sequestration potential, with average values for AGB and BGB suggesting considerable aboveground and belowground reserves, and total carbon storage surpassing 100 Mg ha⁻¹. NDVI displayed a negative correlation with biomass as a result of canopy saturation in dense areas; nevertheless, calibrated models facilitated effective spatial mapping. The classified carbon distribution (62–200 Mg ha⁻¹) revealed variability associated with vegetation density, slope, and aspect, with higher stocks found in less disturbed, well-oriented locations. The research highlights the ecological and climatic importance of sacred groves, advocating for their inclusion in REDD⁺ initiatives and community-led conservation efforts. It also illustrates the effectiveness of NDVI–GIS techniques for biomass mapping in smaller, culturally significant forests.