A Review of Geospatial Data Analysis and Visualization Using Machine Learning
A Review of Geospatial Data Analysis and Visualization Using Machine Learning
Author(s): Floarea-Maria Brebu, Cosmin-Constantin Mușat, Clara-Beatrice Vîlceanu, Sorin-Ioan Herban, Carmen GreceaSubject(s): Geography, Regional studies, Applied Geography, Geomatics, Maps / Cartography
Published by: Editura Aeternitas
Keywords: geospatial data; satellite images; machine learning; prediction models; analysis; visualization;
Summary/Abstract: Currently, machine learning, including artificial neural networks of different architectures and support vector machines, provides extremely important tools for analyzing, processing and visualizing geo and intelligent environmental data. Machine learning represents an important complement to traditional techniques, such as geostatistics.In this article, we present a review of several applications from the last period of using machine learning for geospatial data: regional classification of environmental data, continuous mapping, environmental data, and pollution, including the use of automated algorithms, optimization (design / redesign) of monitoring networks.
Journal: RevCAD Journal of Geodesy and Cadastre
- Issue Year: 2024
- Issue No: 36
- Page Range: 13-22
- Page Count: 10
- Language: English