Effect of Reduced Spatial Resolution on Mineral Mapping Using Imaging Spectrometry—Examples Using Hyperspectral Infrared Imager (HyspIRI)-Simulated Data

Abstract

Abstract:The Hyperspectral Infrared Imager (HyspIRI) is a proposed NASA satellite remote sensing system combining a visible to shortwave infrared (VSWIR) imaging spectrometer with over 200 spectral bands between 0.38 and 2.5 μm and an 8-band thermal infrared (TIR) multispectral imager, both at 60 m spatial resolution. Short Wave Infrared (SWIR) (2.0-2.5 μm) simulation results are described here using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data in preparation for the future launch. The simulated data were used to assess the effect of the HyspIRI 60 m spatial resolution on the ability to identify and map minerals at hydrothermally altered and geothermal areas. Mineral maps produced using these data successfully detected and mapped a wide variety of characteristic minerals, including jarosite, alunite, kaolinite, dickite, muscovite-illite, montmorillonite, pyrophyllite, calcite, buddingtonite, and hydrothermal silica. Confusion matrix analysis of the datasets showed overall classification accuracy ranging from 70 to 92% for the 60 m HyspIRI simulated data relative to 15 m spatial resolution data. Classification accuracy was lower for similar minerals and smaller areas, which were not OPEN ACCESSRemote Sens. 2011, 3 1585 mapped well by the simulated 60 m HyspIRI data due to blending of similar signatures and spectral mixing with adjacent pixels. The simulations demonstrate that HyspIRI SWIR data, while somewhat limited by their relatively coarse spatial resolution, should still be useful for mapping hydrothermal/geothermal systems, and for many other geologic applications requiring mineral mapping.

Temporal and Seasonal Variations of the Hot Spring Basin Hydrothermal System, Yellowstone National Park, USA

“…Because each pixel is ~one meter in area, the total radiative heat output for an area is the sum of the corrected and calibrated ground temperature for each pixel in the region of interest taken to the fourth power and multiplied by the Stefan Boltzman constant. Zero degrees Celsius (273.15 Kelvin) is an approximation for the air temperature at time of acquisition (2007)(2008)(2009)(2010)(2011)(2012) Yellowstone National Park, Kruse and others [5] assessment of spatial resolution regarding detail and adequacy for mapping does apply to our study of temporal and seasonal variations in the Hot Spring Basin hydrothermal system. Night-time, airborne thermal infrared imagery with its high-spatial resolution (~1 m) is an important component for defining the area over which heat output is calculated and change in this hydrothermal system can be measured.…”

“…Yellowstone National Park has been a test bed for various sensors, platforms and imaging techniques for various geologic applications [1][2][3][4][5][6][7][8][9][10][11][12]. The focus of these efforts involved geologic mapping [4,[7][8][9]11,13,14], hydrothermal mixing of waters [1], mineral mapping [3,5] and estimating Yellowstone's radiative heat for the entire park or specific areas [2,6,10,12,15]. The thermal infrared sensors covered two thermal infrared regions: 3-5 microns (µm) and 8-12 microns (µm).…”

A New Approach for the Analysis of Hyperspectral Data: Theory and Sensitivity Analysis of the Moment Distance Method

“…For instance, the recently-launched Landsat 8 Operational Land Imager (OLI) has only nine relatively broad bands [81], which may be insufficient to detect curve changes. However, with the existence of Hyperion, a spaceborne imaging spectrometer launched in 2001 [49,67], the upcoming HyspIRI mission [50,51], airborne imaging spectrometers (e.g., AISA Eagle [82], MASTER [83], and AVIRIS [84,85]), and the advent of robust, affordable field spectrometers, fine spectral resolution datasets are increasingly available for MDI utilization.…”

“…Whereas current indices incorporate two-band or three-band relations, no metric has dealt with the raw shape of the curve by featuring multiple bands that could carry additional spectral information useful for vegetation monitoring. In this era of spaceborne sensors such as the EO-1 Hyperion [49] and NASA's Hyperspectral InfraRed Imager (HyspIRI) [50][51][52] that may be launched in the future, VIs can be designed for optimal use of the spectrum by creating new indices that incorporate wavelengths not sampled by any broadband system [53]. Unlike broadband sensors such as the Landsat TM, ETM, and OLI that have few bands, both spaceborne sensors have many spectral channels that span from the visible to NIR-regions considered as essential for vegetation studies.…”

Application of Neural Networks to Matlab Analyzed Hyperspectral Images for Characterization of Composite Structures

“…Common problems in the area of hyperspectral analysis involving data relevancy include optimal selections of wavelength, number of bands, and spatial and spectral resolution. Despite the fact that hyperspectral image analysis is used to perform index analysis in hyperspectral and multispectral satellite imagery, it is assumed that it can be used for image comparison of similar or processed images, of completely different origin [11][12][13][14][15].…”