Paper
4 May 2006 Analysis of a multitemporal hyperspectral dataset over a common target scene
David W. Messinger, Michael Richardson, Jason Casey
Author Affiliations +
Abstract
As hyperspectral sensors become more available, an understanding of the impact of "natural change" on exploitation of that imagery is required. During the summer of 2005, the RIT Digital Imaging and Remote Sensing Laboratory, in conjunction with the Laboratory for Imaging Algorithms and Systems, undertook a collection campaign of a common target scene with a Vis / NIR hyperspectral sensor. The Modular Imaging Spectrometer Instrument (MISI) has 70 channels from 0.4μm to 1.0μm and was flown over the RIT campus on six different dates between May and September along a common flightline. Flights were spaced by as little as 3 days and as long as a month. Twice, multiple flightlines were collected on a single day, separated by minutes and hours. Several experiments were run during individual flights, but the goal here is to describe and understand the temporal aspects of the data. Results from classifying each image are presented to show how local weather history, slightly different collection geometries, and real scene change affect the results. Similarly, common regions of interest in the imagery are defined and comparisons are made of the statistical variations in the regions across the season. Additionally, signature prediction forward in time using the method of Covariance Equalization is examined as to its applicability to this dataset.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David W. Messinger, Michael Richardson, and Jason Casey "Analysis of a multitemporal hyperspectral dataset over a common target scene", Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62331I (4 May 2006); https://doi.org/10.1117/12.665521
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Buildings

Near infrared

Reflectivity

Statistical analysis

Target detection

Imaging systems

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