Forest Regeneration Status To Support Forest Health In Panti Forest Reserve Using Machine Learning Approach Ashleza Ahmad (1*), Noordyana Hassan (2)
1) Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (UTM), 81310 UTM Skudai, Johor, Malaysia
2) Geoscience and Digital Earth Centre (INSTeG), Research Institute of Sustainable Environment (RISE), Universiti Teknologi Malaysia (UTM), 81310 UTM Skudai, Johor, Malaysia
Abstract
Remote sensing has now acquired a crucial role for mapping forest changes, understanding ecosystem dynamics, and monitoring both deforestation and natural regeneration. It significantly contributes forest management, biodiversity conservation and habitat monitoring since it provides extensive information on spatial data. In the past, Panti Forest Reserve, located in Kota Tinggi, Johor, Malaysia, experienced scheduled logging, which led to habitat loss and a decline in wildlife presence, as the Sustainable Forest Management (SFM) was not employed anymore in this area to encourage forest regeneration. However, recent observations suggest that the forest is regenerating, with increasing signs of wildlife returning. This observation raises important questions about the drivers of habitat reoccupation and the spatial conditions that support wildlife return. This study aims to analyse land use and land cover (LULC) changes in Panti Forest Reserve for the years 2015, 2020, and 2025 using SPOT satellite imagery and the Random Forest classification. Key environmental variables such as elevation, slope, distance from water sources, and distance from forest edges will be analysed to explore their influence on wildlife return. Statistical analysis will be conducted to identify the impact of forest regeneration on wildlife presence in the area. The findings of this study will contribute to the Forestry Department of Peninsular Malaysia and the Department of Wildlife and National Parks (PERHILITAN) by supporting forest management and wildlife conservation planning.
Keywords: Forest regeneration, land cover change, Random Forest classification, wildlife return
