Satellite Image Segmentation for Forest Fire Risk Detection using Gaussian Mixture Models

Forest fires are a major threat to the environment, causing destruction to both wildlife and human habitats. Despite preventative measures, they still contribute significantly to global forest destruction. Previous scientific studies aimed at detecting potential areas and predicting the extent of fires that were already in progress using sophisticated techniques like aerial surveillance and artificial intelligence. However, proposed research introduces a new method that utilizes Gaussian mixture-based image segmentation techniques applied to satellite imagery for forest fire detection. This innovative approach can identify areas at risk of forest fire, enabling early detection and intervention, which can reduce the spread and intensity of fires. With this technique, forest fires can be detected before they become catastrophic, thus minimizing the damage caused by forest fires. By identifying potential areas, forest managers and firefighters can take preventative measures in advance to mitigate the impact of fires.