Sentinel-2, which is a part of 20 European Space Agency's (ESA) satellite constelation that will be developed and fully functional by 2020, complements the needs of Copernicus - European Earth Observation Programme by collecting information about the Earth's surface structure and processes to provide data for variety of environmental and security applications.
The Institute for Environmental Solutions (IES), supported by ESA PECS programme is implementing the SENTISIMULAT project. IES will use its airborne remote sensing system ARSENAL to simulate the performance of ESA's Sentinel-2 satellite to continue the development of Land Use - Land Cover (LC-LU) classification algorithms and perform feasibility study on the fusion of Sentinel-2 images and Landsat-8 thermal infrared images with airborne hyperspectral data.The algorithm will help to use satellite data for analysis of LC-LU, spread of invasive species, dynamics of forest resources and vitality, identification of damaged areas, wetlands, flood risk areas and degraded ecosystems and evaluate various aspects of biodiversity loss.
The results will serve as stepping stones for further development of operational Earth observation products and services in various sectors in Latvia, such as Rural Support Service, the Latvian Rural Advisory and Training Centre, Ministry of Agriculture, Ministry of Environment and Regional Development, Latvian Environment, Geology and Meteorology Centre and other institutions.
The view expressed herein can in no way be taken to reflect the official opinion of ESA.
IES is the main contractor. The airborne remote sensing data will be collected with IES’s Airborne Environmental Surveillance and Monitoring System ARSENAL. For verification of LC-LU classes an image of high spatial resolution (0.2-4m), covering the same swath, will be acquired simultaneously with the hyperspectral data.
The observation will be fulfilled by two hyperspectral airborne imaging sensors (infrared light) and a high resolution RGB camera (visible light) which are embedded in the ARSENAL. The spectral band of the two hyperspectral sensors will be applied to simulate the Sentinel-2 bands and the maximum swath and required spatial resolution both for hyperspectral and RGB sensors will be reached by careful data collection planning.
As a result of the project, IES will develop a LC-LU classification algorithm for the Sentinel-2 data.