Universität zu Köln

Aasen, Helge ORCID: 0000-0003-4343-0476, Burkart, Andreas, Bolten, Andreas ORCID: 0000-0003-1287-9705 and Bareth, Georg (2015). Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance. ISPRS-J. Photogramm. Remote Sens., 108. S. 245 - 260. AMSTERDAM: ELSEVIER SCIENCE BV. ISSN 1872-8235

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Abstract

This paper describes a novel method to derive 3D hyperspectral information from lightweight snapshot cameras for unmanned aerial vehicles for vegetation monitoring. Snapshot cameras record an image cube with one spectral and two spatial dimensions with every exposure. First, we describe and apply methods to radiometrically characterize and calibrate these cameras. Then, we introduce our processing chain to derive 3D hyperspectral information from the calibrated image cubes based on structure from motion. The approach includes a novel way for quality assurance of the data which is used to assess the quality of the hyperspectral data for every single pixel in the final data product. The result is a hyperspectral digital surface model as a representation of the surface in 3D space linked with the hyperspectral information emitted and reflected by the objects covered by the surface. In this study we use the hyperspectral camera Cubert UHD 185-Firefly, which collects 125 bands from 450 to 950 nm. The obtained data product has a spatial resolution of approximately 1 cm for the spatial and 21 cm for the hyperspectral information. The radiometric calibration yields good results with less than 1% offset in reflectance compared to an ASD FieldSpec 3 for most of the spectral range. The quality assurance information shows that the radiometric precision is better than 0.13% for the derived data product. We apply the approach to data from a flight campaign in a barley experiment with different varieties during the growth stage heading (BBCH 52 - 59) to demonstrate the feasibility for vegetation monitoring in the context of precision agriculture. The plant parameters retrieved from the data product correspond to in-field measurements of a single date field campaign for plant height (R-2 = 0.7), chlorophyll (BGI2, R-2 = 0.52), LAI (RDVI, R-2 = 032) and biomass (RDVI, R-2 = 0.29). Our approach can also be applied for other image-frame cameras as long as the individual bands of the image cube are spatially co-registered beforehand. (C) 2015 International Society for Photogrammety and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Aasen, Helge UNSPECIFIED orcid.org/0000-0003-4343-0476 UNSPECIFIED Burkart, Andreas UNSPECIFIED UNSPECIFIED UNSPECIFIED Bolten, Andreas UNSPECIFIED orcid.org/0000-0003-1287-9705 UNSPECIFIED Bareth, Georg UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-392061
DOI:	10.1016/j.isprsjprs.2015.08.002
Journal or Publication Title:	ISPRS-J. Photogramm. Remote Sens.
Volume:	108
Page Range:	S. 245 - 260
Date:	2015
Publisher:	ELSEVIER SCIENCE BV
Place of Publication:	AMSTERDAM
ISSN:	1872-8235
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Geosciences > Geographisches Institut
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language UNMANNED AERIAL VEHICLE; CROP SURFACE MODELS; PRECISION AGRICULTURE; ABOVEGROUND BIOMASS; STRESS DETECTION; AIRCRAFT SYSTEM; NITROGEN STATUS; MAPPING SYSTEM; WATER-STRESS; DATA FUSION Multiple languages Geography, Physical; Geosciences, Multidisciplinary; Remote Sensing; Imaging Science & Photographic Technology Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/39206