To support environmental management there is increasing need for timely, accurate and detailed information on our land. Unmanned Aerial Systems (UAS) are increasingly used to monitor agricultural crop development, habitat quality or urban heat efficiency. An important reason is that UAS technology is maturing quickly while the flexible capabilities of UAS fill a gap between satellite based and ground based geo-sensing systems.
In 2012, different groups within Wageningen University and Research Centre have established a Unmanned Airborne Remote Sensing Facility. The objective of this facility is threefold:
- To develop innovation in the field of remote sensing science by providing a platform for dedicated and high-quality experiments;
- To support high quality UAS services by providing calibration facilities and disseminating processing procedures to the UAS user community;
- To promote and test the use of UAS in a broad range of application fields like habitat monitoring, precision agriculture and land degradation assessment.
The facility is hosted by the Laboratory of Geo-Information Science and Remote Sensing (GRS) and the Department of Soil Physics and Land Management (SLM) of Wageningen University together with the team Earth Informatics of Alterra.
Description of facility
The added value of the Unmanned Aerial Remote Sensing Facility is that compared to for example satellite based remote sensing more dedicated science experiments can be prepared. This includes for example higher frequent observations in time (e.g., diurnal observations), observations of an object under different observation angels for characterization of BRDF and flexibility in use of camera’s and sensors types. In this way, laboratory type of set ups can be tested in a field situation and effects of up-scaling can be tested.
The following platforms are available:
- Altura PRO AT8 multicopter system with a fully autonomous flying functionality. The platform allows different sensor types to be attached up to a weight of 1.8 kg.
- Fixed wing system Mavinci with a orthophoto system for automated analysis of digital terrain model.
The following camera types are available:
- High-resolution orthophoto camera system;
- Four-band multi spectral system (G, R, NIR): MUMSY system;
- Hyperspectral camera system in range 400-1000 nm with 10 nm spectral resolution: HYMSY system.
Next to the camera systems, processing facilities are developed for automated processing of the acquired image datasets. From this high-quality products like Digital Surface Models, RGB Orthomosaics and Hyperspectral data Cubes can be derived which will be adopted for research in different application fields.
Currently the following projects are using the UARS Facility:
- Smart Inspectors: The project is aiming at the development of a remote sensing infrastructure using state-of-the-art sensors on Unmanned Aerial Systems (UAS) for environmental applications and is funded by the INTERREG IVA program Deutschland-Nederland. Within the project, research organizations (Hochschule Kleve, Wageningen University, Landwirtschaftszentrum Haus Riswick) and companies (BLGG Research, Sceme.de, IMST) are cooperating to bring fundamental research to operational applications. The Wageningen University groups will be responsible for processing of the acquired images to products like nitrogen status of crops and soil organic matter relevant for farmers and nature managers.
- BIOSOS: this project aims to develop tools and models for consistent multi-annual monitoring of NATURA 2000 sites and their surroundings. The emphasis of the project is on NATURA 2000 sites in the Mediterranean part of Europe, but also sites in the Netherlands, Wales and even the tropical rainforest of Brazil are included. For this project, the opportunities of UAS are investigated for the nature reserve Wekeromse Zand in the Netherlands.
- NatureCoast: The STW-funded research program NatureCoast (nature-driven nourishment of coastal systems) investigates the dynamical nature of the Sand Motor. The aim of this unprecedented large nourishment of sand is to supply the adjacent coast with a surplus of sand for years to come, making the coast broader and safer against storms. Unmanned Aerial Systems (UAS) are intensively used to study the impact of the Sand Motor on the adjacent dunes. It allows for mapping dune development at a very high spatial-temporal resolution, offering an invaluable platform for coastal research. Two PhDs of the UAV Facility are working within this project: Corjan Nolet and Marinka van Puijenbroek.
Bartholomeus, H., Suomalainen, J., Franke, J., Kooistra, L., 2015. Design of an UAV-based Hyperspectral Scanning System and Application in Agricultural and Environmental Research. Presentation Geospatial World Forum, Lisabon, Portugal, from 25-29 May, 2015.
Kooistra, L., 2015. Unmanned Aerial Systems: Smart Inspectors for Environmental Monitoring Applications. Presentation European Drone Convention, 21 April 2015, Genk, Belgium.
Roosjen, P., Bartholomeus, H., Suomalainen, J., Clevers, J.P.G.W., 2015. BRDF Effects Based on Optical Multi-Angular Laboratory and Hyperspectral UAV Measurements. In: 9th EARSeL Imaging Spectrometry Workshop, 14 – 16 April 2015, Luxembourg.
Gevaert, C.M., Tang, J., Suomalainen, J., Kooistra, L., 2015. Spectral-Temporal Response Surfaces for Precision Agriculture Applications. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
Brede, B., 2015. Influence of Solar Geometry on the Enhanced Vegetation Index in Observations of an Unmanned Aerial Vehicle and the Ross-Li model. Thesis Report GIRS-2015-05, Laboratory for Geo-information Science and Remote Sensing, Wageningen University, The Netherlands.
Kramer, H., Mücher, S., Franke, J., Kooistra, L., Suomalainen, J., Bartholomeus, H., 2015. Meer detail met UAV’s: gedetailleerde luchtfoto’s uit onbemande luchtvaartuigen, Geo-Info 2: 34-36.
Suomalainen, J., Anders, N., Iqbal, S., Roerink, G., Franke, J., Wenting, P., Hünninger, D., Bartholomeus, H., Becker, R., and Kooistra, L., 2014c. A Lightweight Hyperspectral Mapping System and Photogrammetric Processing Chain for Unmanned Aerial Vehicles. Remote Sensing 2014, 6(11), 11013-11030.
Gevaert, C.M., Tang, J., García-Haro, F.J., Suomalainen, J., Kooistra, L., 2014. Combining hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications. In: WHISPERS 5th Workshop on Hyperspectral Image and Signal Processing, 24-27 June 2014, Lausanne, Switzerland.
Suomalainen, J., Mucher, S., Kooistra, L., and Meesters, E., 2014b. Mapping Health of Bonaire Coral Reefs Using a Lightweight Hyperspectral Mapping System - First Results. In: Proceedings of the EGU General Assembly 2014, 27 April – 02 May, 2014 in Vienna, Austria. - Geophysical Research Abstracts 16: EGU2014-15619-1
Kooistra, L., Suomalainen, J., Franke, J., Bartholomeus, H., Mücher, S., and Becker, R., 2014a. Monitoring agricultural crops using a light-weight hyperspectral mapping system for unmanned aerial vehicles. In: Proceedings of the EGU General Assembly 2014, 27 April – 02 May, 2014 in Vienna, Austria. - Geophysical Research Abstracts 16: EGU2014-2790.
Bartholomeus, H., Suomalainen, J., Kooistra, L., 2014. Estimation of within field variation of SOM using UAV based RGB and elevation data. In: Proceedings of the EGU General Assembly 2014, 27 April – 02 May, 2014 in Vienna, Austria. - Geophysical Research Abstracts 16: EGU2014-5660.
Suomalainen, J., Franke, J., Anders, N., Iqbal, S., Wenting, P., Becker, R., and Kooistra, L., 2014a. Lightweight Hyperspectral Mapping System and a Novel Photogrammetric Processing Chain for UAV-based Sensing. In: Proceedings of the EGU General Assembly 2014, 27 April – 02 May, 2014 in Vienna, Austria. - Geophysical Research Abstracts 16: EGU2014-14473.
Mücher, S., Roerink, G., Franke, J., Suomalainen, J., and Kooistra, L., 2014. Monitoring agricultural crop growth: comparison of high spatial-temporal satellite imagery versus UAV-based imaging spectrometer time series measurements. In: Proceedings of the EGU General Assembly 2014, 27 April – 02 May, 2014 in Vienna, Austria. - Geophysical Research Abstracts 16: EGU2014-15788.
Van Duijvenbode, J., 2013. Incident light monitoring for UAV-acquired image correction. Thesis Report GIRS-2014-01, Laboratory for Geo-information Science and Remote Sensing, Wageningen University, The Netherlands.
Kooistra, L., Suomalainen, J., Iqbal, S., Franke, J., Wenting, P., Bartholomeus, H., Mücher, S., Becker, R., 2014b. Crop monitoring using a light-weight hyperspectral mapping system for unmanned aerial vehicles: firs results for the 2013 season. In: Bendig, J., Bareth, G. (Eds.): Proceedings of the Workshop on UAV-based Remote Sensing Methods for Monitoring Vegetation. Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten, Cologne, Germany, 51 - 58.
Jonkheer, E.; Kooistra, L., 2014. Luchtsteun voor de akkerbouwer. Landbouw mechanisatie 17-20.
Anders, N.; Keesstra, S.D.; Suomalainen, J.M.; Bartholomeus, H.; Kooistra, L., 2013. Monitoring geomorphological change with unmanned aerial vehicles. In: Proceedings of the 8th IAG International Conference on Geomorphology, Paris, France, 27 - 31 August, 2013.
Suomalainen, J., Anders, N., Iqbal, S., Wenting, P., Franke, J., Becker, R., Kooistra, L., 2013a. Development of a Lightweight Hyperspectral Mapping System for Unmanned Aerial Vehicles. In: 8th EARSeL Imaging Spectrometry Workshop, 8 – 10 April 2013, Nantes, France.
Suomalainen, J., Anders, N., Iqbal, S., Wenting, P., Franke, J., Becker, R., Kooistra, L., 2013b. A light-weight hyperspectral mapping system for unmanned aerial vehicles – the first results. In: WHISPERS 5th Workshop on Hyperspectral Image and Signal Processing, 25-28 June 2013, Gainesville, Florida, USA.
Postma, S.; Kooistra, L., 2013. Duizenden drones boven je hoofd. Nederlands Dagblad 16 maart 2013
Kooistra, L., Beza, E., Verbesselt, J., Van den Borne, J., & Van der Velde, W., 2012. Integrating remote-, close range- and in-situ sensing for high-frequency observation of crop status to support precision agriculture. In Proceedings Sensing a Changing World, Wageningen, The Netherlands, 9-11 May, 2012 (pp. 15-20). Wageningen, The Netherlands.
Kooistra, L.; Bartholomeus, H.M.; Becker, R.; Borne, J.; Valkengoed, E. van; Serruys, P.; Voet, P. van der, 2012. Supporting nitrogen management in arable farming using unmanned aerial vehicles. In: Proceedings i-SUP 2012, 3rd Conference “Innovation for Sustainable Production”, 06-09 May 2012, Bruges, Belgium.
Kuilder, E., 2012. Kuilder, E., 2012. Mapping floodplain structure for hydraulic roughness parameterization. Msc thesis Master Geo-information Science and Remote Sensing, Wageningen University, The Netherlands.