Vegetation information is an important index utilized in numerous fields including landscaping, ecological restoration, urban planning, and the environment. We investigated the temporal changes and ecological restoration techniques for damaged quarries using orthophoto images supplied by the National Geographic Information Institute and drone multispectral sensor technology. We examined the area changes of deforestation in quarries and the supervised categorization of photos to produce qualitative and quantitative results based on a temporal background of roughly 24 years from 2000 to 2024. Additionally, different vegetation indices (normalized difference vegetation index, soil-adjusted vegetation index, and modified soil-adjusted vegetation index) and their variation trends were also investigated by analyzing the multispectral images from 2011, 2017, and 2024. The kappa coefficient for orthophoto images through supervised classification was approximately 0.781 on average, indicating satisfactory classification results. The accuracies in 2023 and 2024 were low, which was considered to be due to ambiguous boundary distinctions in the beginning stage of the restoration of damaged areas. The vegetation indices were analyzed for changes over three years in zones A, B, and C. Consequently, the vegetation index for 2017 was lower than those for 2011 and 2024, and it was observed that quarry development in 2017 progressed significantly across all areas. Discussions on the restoration plan for the damaged quarry are presented by comparing the area and vegetation index presented in the time series analysis of this study, therefore rendering information on future vegetation management. This study shows how sensor technology can be usefully applied to ecological restoration, making it meaningful for both environmental and sensor-related research.