LEVERAGING REMOTE SENSING AND PARTICIPATORY GIS FOR ENVIRONMENTAL RESILIENCE: A SYSTEMATIC REVIEW OF GLOBAL COMMUNITY FORESTS

Abstract

Though forest cover nearly one-third of world cover, intensified human activities and inadequate management practices results in encroachment, human-wildlife conflict and forest degradation. Geospatial approaches, including remote sensing and participatory GIS, play a crucial role in monitoring community forests, strengthening land rights, safeguard stability and sustainability of natural resources. This systematic review maps the global landscape of geospatial methodologies used to scale up community forest conservation, promote agriculture and strengthen environmental resilience. To serve this purpose, reputable academic database Scopus has been used 59 relevant studies were selected by employing PRISMA method. Further, VOS viewer and R studio was used to systemically map the annual scientific production, source dynamics, word cloud, treemap, thematic map were graphed for better understanding. The findings of the study revealed that 2023 was the peak stage of this research domain and Ecological Indicators was the highly published journal. Further, Remote sensing of Environment was found to be first journal to publish article on remote sensing based on the inclusion and exclusion criteria of the study. Employing geospatial approaches helps to address socio-economic disparities in forest access, biodiversity conservation, natural resource management, forest fire susceptibility and prevention, long-term monitoring vegetation changes, mapping tree species diversity, land use and land cover classification, forest degradation and restoration, environment assessment, territory identification and land phenology. Apart from forest management, geospatial approaches plays an indispensable role in improving agriculture by analysing desertification and drought variability, assessing soil moisture, mapping soil fertility, predicting yield, pest and disease identification and management, estimating groundwater potential and much more. Ultimately, blending multi-spectral remote sensing with participatory frameworks provides the scalable, data-driven architecture required to enhance crop monitoring, support decision making in agricultural planning for sustainable agriculture and ensure food security.