Paper
14 May 2012 Collection and quality control of spectral signatures in the field
Brian Curtiss, Alexander F. H. Goetz
Author Affiliations +
Abstract
Field spectral signatures are commonly collected in conjunction with remote sensing campaigns. Unfortunately, the lack of sufficient metadata associated with campaign-specific spectral signatures often makes it difficult for others to utilize them for their own applications. The first step in improving the utility of field collected spectral signatures is achieved by establishing fully documented procedures that minimize controllable error sources. A major source of error when collecting field spectral signatures is the variability of solar illumination. By periodically monitoring a static reference panel it is possible to both characterize the variance in solar illumination during collection as well as to correct collected spectra. In addition, recent advances in instrument sensitivity greatly reduce the time required to collect high quality spectra that in turn reduces the magnitude of potential errors associated with changes in solar illumination. Since libraries of field spectral signatures are commonly used to analyze remotely sensed imagery, it is important that field collection is performed at a relevant spatial scale and with illumination and view geometry that is similar to that for the image collection. This is particularly true of vegetation since the observed spectral signature is the result of the complex interaction of multiple illumination sources (i.e. direct sunlight, sky illumination and light scattered off other elements in the scene), canopy architecture and the reflectance properties of the individual elements within the canopy. Suggested field collection approaches that minimize these sources of error are presented.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Brian Curtiss and Alexander F. H. Goetz "Collection and quality control of spectral signatures in the field", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839011 (14 May 2012); https://doi.org/10.1117/12.919484
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Cited by 2 scholarly publications.
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KEYWORDS
Reflectivity

Light scattering

Remote sensing

Absorption

Clouds

Light

Carbon monoxide

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