Developing a novel ecological fuzzy forest health index (FFHI) for Standardizing forest-smart mining using remote sensing techniques

The pressing concerns associated with climate change underscore the critical need for environmental conservation and sustainable resource management. As technological and industrial advancements continue to drive an ever-increasing demand for materials, the extraction of which often involves mining, the imperative to explore novel methodologies for assessing and mitigating the environmental impact of such operations, particularly in areas with forest cover, becomes evident. This study proposes a novel approach utilizing fuzzy logic to calculate the Forest Health Index (FHI), introducing both a Fuzzy Constructive FHI and a Fuzzy Destructive FHI index, each ranging from 0 to 100. The study employs the Sungun copper mine as a case study, situated within the Arasbaran environmentally protected area. To examine the impact of mining operations on forest health, remote sensing is employed to visualize deforestation trends at the Sungun copper mine from 2008 to 2023. Vegetation indices are utilized to estimate the Forest Health Index (FHI) through remote sensing methodologies, incorporating a combination of expert opinions and estimated numbers to assess variables influencing the FHI. Results indicate that the Fuzzy Forest Health Index (FFHI) for Sungun is 2.1. In the continuation of the research, for broader global case studies, maximum and minimum FFHIs were observed in Merian (37.92, interpreted as a rather average constructive fuzzy forest health index) and Nimba Range Mineral Province (NRMP) (-25.7, interpreted as a rather low/average destructive fuzzy forest health index), respectively. The outcomes emphasize the importance of implementing forest-smart mining practices to mitigate the adverse effects of mining. • A novel ecological Fuzzy Forest Health Index (FFHI) is constructed for the computation of the Forest Health. • Utilization of vegetation indices in estimating the Forest Health Index (FHI) through remote sensing methodologies. • Presentation of Fuzzy Constructive FHI and Fuzzy Destructive FHI indicators in forest health assessment. • Study outcomes, grounded in the FFHI, emphasize the importance of embracing forest-smart mining to mitigate adverse impacts.