Three-Dimensional Mapping of Habitats Using Remote-Sensing Data and Machine-Learning Algorithms

Progress toward habitat protection goals can effectively be performed using satellite imagery and machine-learning (ML) models at various spatial and temporal scales. In this regard, habitat types and landscape structures can be discriminated against using remote-sensing (RS) datasets. However, most existing research in three-dimensional (3D)...

Flood susceptibility mapping using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression

Flood has long been known as one of the most catastrophic natural hazards worldwide. Mapping flood-prone areas is an important part of flood disaster management. In this study, a flood susceptibility mapping framework was developed based on a novel integration of nature-inspired algorithms into support vector regression (SVR). To this end,...