The role of web cloud-based platforms for land cover classification

Mapping of land use and lad cover can be performed using image classification. Machine learning algorithms are a promising alternative for remote sensing images classification. They differ in their ability to manipulate large dimensionalities data and mapping of classes with complex characteristics. On the other hand, there are web cloud-based platforms for remote sensing analysis. These kind of web platforms can be used for scientific analyses and visualization of geospatial datasets. They store, organize and provide access to a wide variety of satellite imageries and geospatial datasets, and offers global-scale environmental data analysis capabilities. These kind of platforms enables fast processing of several spectra-temporal image analysis. It also possible to edit codes adding different classifiers contained in this platform, such as machine learning techniques. The aim of the special session is to promote deep discussions and insights on the role of web cloud-based platforms, using machine-learning techniques and remote sensing products for land cover classification.