With AutoMap, the handling of satellite images has never been easier! We simplify the production of maps based on earth observation data and handle the application of machine learning algorithms for land surface classifications by providing a solid data processing pipeline in a fully managed cloud infrastructure. Bring your own samples or use our default solution, while we take care of the thousands of images that fit your request, all the clouds in your area of interest and every aspect of process optimization and secure data storage. Don't worry about machine learning concepts, intelligent training data collection, hyperparameter optimization or informative feature spaces - That's our job as well! Seeing the world from above is now as demanding as ordering a pizza!

An informational service on the SDG indicators 2.4.1 “Proportion of agricultural area under productive and sustainable agriculture” and 15.3.1 “Proportion of land that is degraded over total land area” based on the 10 m. agricultural land productivity and crop type mapping on Sentinel-2 data as well as Sen-4-CAP.

By joining forces with the agricultural machine builder AVR, VITO Remote Sensing can provide a data integration between the new AVR Connect platform and the information platform WatchITgrow.

NEO signals changes to agriculture parcels. Monitoring, based on satellite imagery in combination with artificial intelligence, aims to detect changes in the boundaries of the parcels. The service saves time and money because, based on the mutation signalling, parcels can be looked at more specifically to determine the new parcel boundaries. This supports the process of keeping the national LPIS (Land Parcel Identification System) registry up to date. The service that NEO provides is unique: it is the first time that mutation signalling based on earth observation is performed automatically on this scale. In this way the 500.000 parcels in the Netherlands are monitored. Open data from the national satellite data portal in the Netherlands is used.