Map production from remotely sensed data
National Mapping Authorities (NMAs) require collection, compilation, and validation of data from diverse information sources and sensors. Remotely sensed data—aerial imagery and data from satellites and other sensors—is critically important to identifying and collecting new and changed features and updating them on the base data. This is done with analytical tools and, increasingly, artificial intelligence (AI) and deep learning. Data and services from all levels of government and other organizations are easily incorporated. The compiled data can then be verified and corrected by field staff.
Collect and capture
The Public Authority for Civil Information (PACI) used machine learning and deep learning to modernize GIS data and support the Kuwait Vision 2035.