Spectral imaging from UAVs under varying illumination conditions
Hakala, T., Honkavaara, E., Saari, H., Mäkynen, J., Kaivosoja, J., Pesonen, L., & Pölönen, I. (2013). Spectral imaging from UAVs under varying illumination conditions. In G. Grenzdörffer, & R. Bill (Eds.), UAV-g2013, 4–6 September 2013, Rostock, Germany (pp. 189-194). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (XL-1/W2). International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprsarchives-XL-1-W2-189-2013 Retrieved from http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W2...
Published inInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
© Author(s) 2013. This work is distributed under the Creative Commons Attribution 3.0 License.
Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes with stereoscopic overlaps. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14–0.18. In the corrected data, the homogeneity was 0.10–0.12 with a correction based on broadband irradiance measured in UAV, 0.07–0.09 with a correction based on spectral irradiance measurement on ground, and 0.05–0.08 with a radiometric block adjustment based on image data. Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications. ...
PublisherInternational Society for Photogrammetry and Remote Sensing (ISPRS)
ConferenceISPRS Workshops. UAV-g2013, 4–6 September 2013, Rostock, Germany
Is part of publicationUAV-g2013, 4–6 September 2013, Rostock, Germany. Edited by G. Grenzdörffer, & R. Bill. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (XL-1/W2). International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprsarchives-XL-1-W2-189-2013
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Except where otherwise noted, this item's license is described as © Author(s) 2013. This work is distributed under the Creative Commons Attribution 3.0 License.
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