Evaluating Forest and Land Rehabilitation Using Remote Sensing: A Case Study in Maros Regency

Remote sensing technology has become crucial in vegetation monitoring, particularly for assessing vegetation density. Despite its broad application, its use in evaluating land rehabilitation efforts remains limited. The increasing extent of degraded lands has underscored the importance of effective forest and land rehabilitation activities. Traditionally, evaluating these efforts involves direct site visits to monitor plant growth annually for three years post-planting, which is time-consuming, labor-intensive, and costly. According to rehabilitation standards, a program is successful if 75% of the planted vegetation survives until the end of the third year. This study presents an efficient alternative by evaluating a rehabilitation site in Maros Regency, using remote sensing technology to monitor planting success over periods of 15 years (2007), nine years (2013), and three years (2019). The evaluation utilizes multispectral drone imagery and Normalized Difference Vegetation Index (NDVI) analysis to assess vegetation density through multi-temporal analysis across wide areas. The findings reveal that the percentage of forested areas after three, nine, and fifteen years of rehabilitation activities was 24.6%, 3.1%, and 23.5%, respectively. This research demonstrates the potential for further application of Unmanned Aerial Vehicle imagery in monitoring the success of land rehabilitation projects.