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A state of the art UAV system for hyperspectral, thermal and LIDAR mapping

English title A state of the art UAV system for hyperspectral, thermal and LIDAR mapping
Applicant Brunner Philip
Number 170753
Funding scheme R'EQUIP
Research institution Centre d'hydrogéologie et de géothermie Université de Neuchâtel
Institution of higher education University of Neuchatel - NE
Main discipline Other disciplines of Earth Sciences
Start/End 01.04.2017 - 30.06.2019
Approved amount 100'000.00
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All Disciplines (6)

Other disciplines of Earth Sciences
Environmental Research
Other disciplines of Engineering Sciences
Hydrology, Limnology, Glaciology

Keywords (8)

Hyperspectral imaging; UAV; Archeology; LIDAR; Thermal imaging; Remote Sensing; Hydrogeology; Ecology

Lay Summary (German)

Ein high-tec Drohnen System für die Geowissenschafften
Lay summary

Fernerkundung durch Satelliten oder Flugzeuge hat erheblich zu den Fortschritten in der Hydrologie und Hydrogeologie beigetragen. Die technologischen Entwicklungen von Sensoren und Drohnen (oder Unmanned Aerial Vehicles- UAVs) ermöglichen eine neue Dimension von Fernerkundung. Durch dieses SNF-Projekt wird ein High-Tech UAV System mit drei verschiedenen Sensoren finanziert. Ein LIDAR -System ermöglicht die Erstellung von hochaufgelösten Geländemodellen. Eine Hyperspektralkamera kann in 270 verschiedenen Wellenlängen die spektralen Eigenschaften der Geländeoberfläche messen. Eine thermische Kamera ermöglicht das Erstellen von hochaufgelösten Temperaturkarten. Die Drohne selbst kann bis zu 25 Minuten fliegen und somit pro Flug eine Fläche von ca. 1 km2 kartieren. Das System ermöglicht unter anderem folgende Anwendungen: Die thermische Kartierung von untiefen Flüssen gibt Aufschluss bezüglich der Fluss-Grundwasser-Interaktionen. Diese Daten ermöglichen die Eichung von komplexen hydrologischen Modellen. Durch den LIDAR Sensor und der Hyperspektralkamera können auch morphologische Veränderungen in Flüssen in einer hohen zeitlichen Auflösung erstellt werden. Diese Daten sind wichtig um die Zusammenhänge zwischen Sedimentations-und Fliessprozessen zu verstehen. Die Kombination von thermischen und hyperspektralen Daten erlaubt das Erstellen von räumlich und zeitlich hochaufgelösten Verdunstungskarten. Solche Daten tragen zum Verständnis der Interaktionen zwischen biologischen und hydrologischen Prozessen bei, zum Beispiel in Feuchtgebieten, aber auch für landwirtschaftlich genutzte Flächen. Das LIDAR System kann auch in der Glaziologie eingesetzt werden. Durch das widerholte Überfliegen ausgewählter Flächen können Änderungen der Eismasse berechnet werden. Weitere geplante Anwendungen in den Bereichen der Geologie, Morphologie und Vegetationsdynamik werden ebenfalls durch diese Drohnen System ermöglicht. 

Direct link to Lay Summary Last update: 03.05.2017

Responsible applicant and co-applicants


Group / person Country
Types of collaboration
UniL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel
WSL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel
UniNe CHYN Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel
EAWAG Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure

Associated projects

Number Title Start Funding scheme
184875 JuraHydroSlide: identifying the principal hydrogeologic ingredients for predicting landslide activity in Jura Mountains 01.04.2019 Project funding
162754 Integrating spatial predictions of vegetation, soils, geomorphology and hydrology for improved assessment of ecosystem services under climate change 01.01.2016 Interdisciplinary projects


Remote sensing has proven to be one of the most useful and extensive data sources for environmental sciences. The recent developments in high performance sensor technology and unmanned aerial vehicles (UAV or drone systems) open an entirely new dimension of remote sensing at extremely high resolution and precision, low cost and high temporal coverage. In this project, we propose to acquire a state of the art UAV platform including a thermal camera, a hyperspectral camera and a LiDAR system. The flight time (in minutes) is up to 25 for LiDAR data acquisition, 20 for hyperspectral and over 25 for thermal. The flight speed of the UAV is 55 km/h max, with a range of 4 km. Compared to traditional airplane/helicopter or satellite-based remote sensing data acquisitions platforms, the advantages of the proposed system will be to acquire data on-demand at extremely high spatial, spectral and temporal resolutions, at a fraction of the cost. The requested system is unique in its configuration of sensors and capabilities and will benefit 5 ongoing SNF projects as well as 5 projects funded by other sources. Examples are: •Surface water groundwater interactions: Temperature is a natural tracer for groundwater exfiltration into rivers. With the thermal camera we can complement existing ground based Distributed Temperature Sensing systems (DTS) to test new approaches for quantifying groundwater exfiltration to rivers. •Mapping vegetation using the hyperspectral camera: Hyperspectral imaging allows identifying different types of vegetation based on their spectral properties. This allows for innovative projects in different environments such as for monitoring vegetation dynamics in an alluvial plain, peatlands, alpine areas and restored rivers. •The proposed system allows establishing surface energy balances, therefore high resolution maps of evapotranspiration (ET) can be calculated. High resolution ET maps allow establishing water balances of wetlands, and well as identifying topographical and ecological controls on ET fluxes. The system can be used without any engineering from our side. All aspects of sensor integration are carried out by our proposed supplier (SPECIM). Payload requirements are fulfilled. Sensors and LiDAR fulfill the required spatial and spectral resolution as well as elevation accuracy to carry out all the proposed projects. The provided software solution integrates IMU/ GNSS and sensor data, therefore georeferenced points clouds, hyperspectral data cubes and thermal images can be used without any software development from our side.The consortium consists of 4 applicants: Prof. P. Brunner (UniNe); Dr. T. Jonas (WSL); Prof. G. Mariethoz (UniL) and Prof. J. Kirchner (ETHZ). All applicants have a proven and highly complementary track record in acquiring and processing remote sensing data, as well as in integrating remote sensing data in their specific disciplines. The majority of proposed research projects are in collaboration across the different institutions and therefore all the required skills to obtaining and processing the different types of data are guaranteed. Through the close collaboration, the state of the art sensor platform can be operated at a very high technical and scientific level.The total costs are 221’964 CHF, half of which is requested from the SNF. The remaining cost will be split up evenly between the four institutions. We are convinced that through this project, highly innovative and productive research collaborations can be established between all involved institutions.