Scalable explorative change detection for big Sentinel-2 data
The aim of SEVA was to develop a scalable exploration tool that supports users to conduct change detection based on optical Sentinel-2 satellite observations. The scalable exploration tool supports the following essential steps of change detection: a) exploration and selection of optical satellite images to recognize proper data for the current application scenario, b) automated extraction of changes from the optical satellite images, c) analysis of errors and d) assessment and interpretation of the extracted changes.
Funded by: Federal Ministry of Economic Affairs and Energy (BMWi)
Funding period: 01.11.2017 - 30.04.2020