Mineral Mapping Using Simulated Worldview-3 Short-Wave-Infrared Imagery

Abstract

WorldView commercial imaging satellites comprise a constellation developed by DigitalGlobe Inc. (Longmont, CO, USA). Worldview-3 (WV-3), currently planned for launch in 2014, will have 8 spectral bands in the Visible and Near-Infrared (VNIR), and an additional 8 bands in the Short-Wave-Infrared (SWIR); the approximately 1.0-2.5 μm spectral range. WV-3 will be the first commercial system with both high spatial resolution and multispectral SWIR capability. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data collected at 3 m spatial resolution with 86 SWIR bands having 10 nm spectral resolution were used to simulate the new WV-3 SWIR data. AVIRIS data were converted to reflectance, geographically registered, and resized to the proposed 3.7 and 7.5 m spatial resolutions. WV-3 SWIR band pass functions were used to spectrally resample the data to the proposed 8 SWIR bands. Characteristic reflectance signatures extracted from the data for known mineral locations (endmembers) were used to map spatial locations of specific minerals. The WV-3 results, when compared to spectral mapping using the full AVIRIS SWIR dataset, illustrate that the WV-3 spectral bands should permit identification and mapping of some key minerals, however, minerals with similar spectral features may be confused and will not be mapped with the same detail as using hyperspectral systems. The high spatial resolution should provide detailed mapping of complex alteration mineral patterns not achievable by current multispectral systems. The WV-3 simulation results are promising and indicate that this sensor will be a significant tool for geologic remote sensing.

Sentinel-2 for Mapping Iron Absorption Feature Parameters

“…The recently launched Worldview-3 sensor has 8 SWIR bands, of which four were taken from the ASTER design [25]. Sentinel-2 lacks such narrow bands in the SWIR bands (Figure 1), and van der Meer et al [4] then also concluded that proxies obtained with Sentinel-2 were the same as what could be obtained with Landsat, albeit on a slightly higher spatial resolution.…”

“…First, the field-of-view of the Sentinel-2 bands can be expected to differ from what we obtained with a spatial degradation by pixel aggregation. The actual point spread function of the Sentinel-2 sensor will sample a slightly larger field-of-view than what we used by the exact given pixel size in following [25]. Secondly, the lossy compression of data used on-board Sentinel-2 was not taken into account.…”

“…The wavelength range, nominal band width and sampling interval of the 4 detectors are: After spectral resampling, the data were spatially resampled from the approximately 5 m resolution of the Hymap data to the 10 m, 20 m and 60 m spatial resolutions of Sentinel-2. In the absence of a point spread function that describes the response of the Sentinel-2 sensor to the sampled area, we used pixel aggregation (neighbourhood averaging), following Kruse and Perry [25] in their simulation of Worldview-3 data.…”

Sentinel-2A MSI and Landsat 8 OLI Provide Data Continuity for Geological Remote Sensing

“…After the spectral resampling, the data were spatially resampled from the original 4 m pixel resolution to the 20 m resolution of Sentinel-2A MSI bands. This was done following Kruse and Perry [48] using pixel aggregation (neighbourhood averaging). The subset of the study area was eventually covered by 402 × 201 pixels of 20 × 20 m.…”

Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping

“…Multispectral and superspectral imagery have been effectively used for mapping geology/minerals [7][8][9][10][11] as well as for monitoring mining impacts [12][13][14][15][16][17][18][19]. However, with a low number of rather broad spectral bands, these systems provide only discrete spectral information (e.g., the state-of-the-art Sentinel-2 sensor has 13 spectral bands [20].…”