Predicting species using machine learning at CCAI / May 2024
Species distribution models are crucial tools that predict species locations by interpolating observed field data with environmental information. We develop an improved, scalable method for species distribution modelling by proposing a dataset pipeline that incorporates global remote sensing imagery, land use classification data, environmental variables, and observation data, and utilising this with CNN models to predict species presence at higher spatial and temporal resolutions than well-established species distribution modelling methods.