Technological Approach to Invasive Species: The Role of Remote Sensing and Predictive Modeling

The dataset provides a global compilation of case studies on invasive species monitoring using remote sensing between 2016 to 2024. It documents species across continents, their study areas, techniques applied, datasets and sensors used, research objectives, ecological impacts, and accuracy assessments. The data reflects diverse methodologies, including UAV imagery, multispectral, hyperspectral, LiDAR, and time-series satellite analysis. It highlights both the potential of advanced machine learning and deep learning methods for scalable detection and the ecological risks posed by invasive plants. References to peer-reviewed studies ensure reliability, making this dataset a valuable resource for ecological monitoring and management strategies.