HYEP 2017 summer school: “Methods and applications of hyperspectral image processing” was a good opportunity for experts in hyperspectral imagery with focus on environment and urban planning to meet and discuss the status and future development perspectives of this boosting remote sensing technique. More than 20 researchers met in Aspet, Southern France to discuss and exchange the experience on methodological aspects of signal processing, corrections, spectral databases and more advanced methods, like spectral unmixing, fusion, deep learning, supervised or non-supervised classification etc., what builds the principles of hyperspectral remote sensing. Various applications of hyperspectral imagery in urban studies, agriculture, forestry, etc. were presented by the participants.
Two researchers from Institute of Forest Management and Wood Science of Faculty of Forestry and Ecology (Donatas Jonikavičius and Gintautas Mozgeris) and Lithuanian Association of Impartial Timber Scalers (Giedrius Bosas) introduced a “low-cost” solution for hyperspectral imaging using drone, which was designed and implemented in Aleksandras Stulginskis University and the Association. After introducing the solutions developed and used in Lithuania along with the results of relevant research projects, the participants were actively involved in imaging mission planning. The flights were immediately implemented using originally developed drone system and Rikola hyperspectral frame camera. Well, these had been the first attempts of our system to fly in mountainous area and under the temperature above 35°… Acquired hyperspectral images of the area around the venue of summer school were rapidly processed and the participants had an opportunity to exercise with hyperspectral image mosaics aiming for extraction of features they had surveyed directly in the field. Following the demonstrations, valuable feed-back on the issues in solutions used were provided and potential future collaboration projects were discussed.
The summer school beneficiated from the developments of the ANR HYEP (Hyperspectral Imagery for Environmental Urban Planning) project.