31 December 1997 Airborne VIRS for monitoring of the environment
Author Affiliations +
Proceedings Volume 3221, Sensors, Systems, and Next-Generation Satellites; (1997); doi: 10.1117/12.298111
Event: Aerospace Remote Sensing '97, 1997, London, United Kingdom
A great effort is actually devoted to design and to develop new remote sensing instruments with increased spectral and spatial resolution. This effort is aimed to obtain a direct and sure target recognition relying on identification of narrow features in the reflectivity spectrum of the observed targets. VIRS is a promising instrument for airborne hyperspectral remote sensing. The sensor is one of the first imaging spectrometers operating in push-broom mode, and provides 20 independent channels selected among 240 possible bands distributed between 400 and 1000 nm. Each channel has a spectral resolution of 2.5 nm and a digitalization accuracy of 10 bit. The main problem for application of hyperspectral remote sensing to environmental studies is that most of the available theoretical models were derived for low resolution spectral measurements. These models do not take advantage of the huge information gathered by such a sensor as the VIRS. In this paper the problem of modeling and interpreting hyperspectral remotely sensed data acquired by the VIRS is examined. The paper shows the main technical characteristics of the sensor, and investigates its use for environmental monitoring. Our work shows the lack of reliable models for theoretical interpretation of data as well as the need for higher spectral resolution data in some specialized applications.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alessandro Barducci, Ivan Pippi, "Airborne VIRS for monitoring of the environment", Proc. SPIE 3221, Sensors, Systems, and Next-Generation Satellites, (31 December 1997); doi: 10.1117/12.298111; https://doi.org/10.1117/12.298111

Data modeling

Environmental monitoring

Remote sensing


Spectral resolution

Target recognition

Environmental sensing


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