The Remote Sensing Lab operates within the Regional Analysis Division of the Institute of Applied Mathematics of FORTH (Foundation for Research and Technology Hellas). The Lab is activated in the field of Earth Observation and its area of application is the study of environmental phenomena and problems. Understanding Earth system processes, as well as their interaction effects of the manmade activities has been recognized by the global scientific community as an urgent and important research direction requiring further investigation. Observing the Earth by the technology of Remote Sensing is a non-invasive, non-destructive method of obtaining information. Remote Sensing can help monitor changes in the Earth’s climate and environment, because it offers a unique perspective of the Earth, its resources and human impact upon it. It is a fast-growing area of research with technological advantages leading to smaller satellites with improved instrumentation, as well as to advanced airborne hyper-spectral sensors, unmanned aerial vehicles and ground systems.
The activities of the Lab focus on both urban and natural environment. Concerning urban environment, the estimation of energy, water and carbon exchanges between the surface and the atmosphere is an area where Remote Sensing data and methods are of greatest relevance. Several city typologies and climatically meaningful urban zoning systems can be derived based on satellite observations. Furthermore, consideration of issues related to sustainability into urban plans provides an opportunity for Remote Sensing to be used extensively in the planning processes since it can generate vast amounts of information at different levels of resolution that can be used as input to planning models and also detecting changes through time. Concerning natural environment, the Lab activities deal with environmental monitoring and development of methods for exploiting Earth Observation in improving future ecosystem benefits and ecosystems services.
The Lab exploits the advances in applied and computational mathematics (i.e. inversion methods for extracting geophysical parameters or geometric features from satellite images; geometric models used in photogrammetry, advanced classification algorithms etc.) and has the potential to support GIS-based spatial analysis and modeling by providing distributions of bio-geo-physical parameters. The Lab is involved and coordinates European projects funded by H2020, FP7 and ERA.Net, as well as in National funded projects. Beyond research activities, the Lab also exploits the research results towards the development of EO-based services.