A research team led by the University of Aberdeen has developed a pioneering AI model to improve accuracy and reduce computational time in land cover mapping, particularly for vegetation.

First, a specific conceptual land cover classification scheme is presented based on the definition of delimitation and characterization variables. The regional conceptual classification scheme ...

A supervised classification by the maximum likelihood algorithm composed of five classes—Bare land, Settlements, Water bodies, Vegetation and Mine activities, was designed for this study, in order to ...

Impact Observatory, contracted by Esri, developed a deep learning AI land classification model using a massive training dataset of billions of human-labeled image pixels, and applied this model to ...

A Kansas State University geography professor is using satellite imagery to research how land use and land cover changes affect human health and food security.