Airborne imaging spectrometer: A new tool for remote sensing

Vane, Gregg; Goetz, Alexander; Wellman, John B.

doi:10.1109/tgrs.1984.6499168

Cited by 120 publications

(61 citation statements)

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“…Imaging spectroscopy (IS), or hyperspectral remote sensing (HRS), is an advanced tool that provides high spectral resolution data in an image, with the aim of providing nearlaboratory-quality reflectance or emittance for each individual picture element (pixel) from a far or close distances (Vane et al, 1984). This information enables the identification of objects based on the spectral absorption features of chromophores and has found many uses in terrestrial and marine applications (Clark and Roush, 1984, Vane et al, 1984, Dekker et al, 2001.…”

Section: Imaging Spectroscopymentioning

confidence: 99%

“…This information enables the identification of objects based on the spectral absorption features of chromophores and has found many uses in terrestrial and marine applications (Clark and Roush, 1984, Vane et al, 1984, Dekker et al, 2001. Figure 1 illustrates the concept, in which the spectral information of a given pixel shows a new dimension that cannot be obtained by traditional point spectroscopy, air photography or other multi-band images.…”

Section: Imaging Spectroscopymentioning

confidence: 99%

“…Since the spatial-spectral-based view may provide better information than viewing either the spatial or spectral view separately, IS serves as a powerful and promising tool in the modern remote-sensing arena. Since 1983, when the first airborne IS sensor (AIS, Vane and Goetz 1984) ushered in the IS era (Vane et al, 1984), this technique has been used mostly for geology, water, and vegetation applications. It appears that its application did not extend to soils because these present a complex matrix: it is only recently, with the advent of better signal-to-noise sensors, the manufacture of less expensive IS sensors and the development many soil (point) spectroscopy applications, that soil-IS activity has progressed somewhat.…”

Section: Imaging Spectroscopymentioning

confidence: 99%

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Soil Spectral Imaging: Moving From Proximal Sensing to Spatial Quantitative Domain

Dor

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Imaging spectroscopy (IS) is a relatively new technique that has attracted the attention of workers in many fields. In the soil sciences, this technology is not well developed and additional research is required – despite the fact that a large number of soil properties in the soil environment have already been studied from a reflectance perspective with much success (e.g. organic matter, cation exchange capacity, carbonate content and specific surface area). Going from proximal sensing to image spectrometry is not only a journey from the micro to macro scales; it is a lengthy one that is fraught with problems, such as dealing with data having a low signal-to-noise level, contamination of the atmosphere, large data sets, the Bidirectional Reflectance Distribution Function (BRDF) effect and more. In this paper, provide a brief history of both near infrared spectroscopy (NIRS) and IS approaches and attempt to understand why, despite its promise, IS has not yet been well developed for the soil sciences. We assume that research, education, exposure of the technology to end-users and governmental involvement are the major factors that require attention in this venue. Also provide some personal thoughts on the future of IS in soil and conclude that in 5 to 10 years, this application will have matured into one that is ready to use and well-known among soil scientists, end-users and decision-makers.

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Section: Imaging Spectroscopymentioning

confidence: 99%

Section: Imaging Spectroscopymentioning

confidence: 99%

Section: Imaging Spectroscopymentioning

confidence: 99%

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Soil Spectral Imaging: Moving From Proximal Sensing to Spatial Quantitative Domain

Dor

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Earth observation (EO) with imaging spectrometers started in 1982 with the first flights of the Airborne Imaging Spectrometer (AIS) followed by the Advanced Visible/Infrared Imaging Spectrometer (AVIRIS) in 1987 [36,37]. The high information content of the contiguous narrow spectral bands, which cover the visible (VIS), near infrared (NIR), and short-ware infrared (SWIR), provided valuable insights on surface characteristics and opened up new pathways of image analysis.…”

Section: Introductionmentioning

confidence: 99%

The EnMAP-Box—A Toolbox and Application Programming Interface for EnMAP Data Processing

et al. 2015

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Abstract:The EnMAP-Box is a toolbox that is developed for the processing and analysis of data acquired by the German spaceborne imaging spectrometer EnMAP (Environmental Mapping and Analysis Program). It is developed with two aims in mind in order to guarantee full usage of future EnMAP data, i.e., (1) extending the EnMAP user community and (2) providing access to recent approaches for imaging spectroscopy data processing. The software is freely available and offers a range of tools and applications for the processing of spectral imagery, including classical processing tools for imaging spectroscopy data as well as powerful machine learning approaches or interfaces for the integration of methods available in scripting languages. A special developer version includes the full open source code, an application programming interface and an application wizard for easy integration and documentation of new developments. This paper gives an overview of the EnMAP-Box for users and developers, explains typical workflows along an application example and exemplifies the concept for making it a frequently used and constantly extended platform for imaging spectroscopy applications. OPEN ACCESSRemote Sens. 2015, 7 11250

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“…With these multispectral AVHRR data, research has been pursued to assess the effect of the atmosphere on derived surface parameters [Tanre et al, 1992]. Based on the advance of detector and optical technology, the first Earth-looking airborne imaging spectrometers were conceived in the late 1970s and were developed in the 1980s to measure spectral images [Vane et al, 1984[Vane et al, , 1987. From the earliest imaging spectrometer data acquisitions, the effects of water vapor on the measured spectra were observed and studied [Conel et al, 1988].…”

Section: Introductionmentioning

confidence: 99%

Atmospheric water vapor sensitivity and compensation requirement for Earth‐looking imaging spectrometers in the solar‐reflected spectrum

Green¹

2001

J. Geophys. Res.

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Abstract. An increasing number of Earth-looking imaging spectrometers are being developed to derive properties of the surface from measured upwelling spectral radiance that has passed through the atmosphere. However, the measurements are influenced by the amount of atmospheric water vapor. Water vapor is present in every spectrum and is highly variable through space and time. This research assesses the sensitivity to the accurate knowledge of atmospheric water vapor of imaging spectrometers with surface measurement objectives. This sensitivity is explored for a range of imaging spectrometer spectral resolutions from 5 to 20 nm as well as for a range of atmospheric water vapor from normal to dry conditions. The effect of atmospheric water vapor errors of 50, 25, 10, 5, and 1% is analyzed. In all cases the derived surface reflectance is shown to be strongly sensitive to the accurate knowledge of water vapor in the imaging spectrometer measurement. This result leads to a general requirement of 1% or better knowledge of atmospheric water vapor in order to derive surface reflectance that is largely free of water-vapor-induced errors, distortions, and spectral artifacts.

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Airborne imaging spectrometer: A new tool for remote sensing

Cited by 120 publications

References 0 publications

Soil Spectral Imaging: Moving From Proximal Sensing to Spatial Quantitative Domain

Soil Spectral Imaging: Moving From Proximal Sensing to Spatial Quantitative Domain

The EnMAP-Box—A Toolbox and Application Programming Interface for EnMAP Data Processing

Atmospheric water vapor sensitivity and compensation requirement for Earth‐looking imaging spectrometers in the solar‐reflected spectrum

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