A comparison of airborne and simulated EnMap Hyperspectral Imagery for mapping bedrock classes in the Canadian Arctic

• Main Author: MacLeod, Roger
• Other Authors: Niemann, K. O. (Kurt Olaf)
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: EnMap; Hyperspectral; Remote sensing; Hope Bay; Satellite; Arctic; Northwest Territories
• Online Access: https://dspace.library.uvic.ca//handle/1828/8699

The upcoming launch of the German hyperspectral satellite: Environmental Mapping and Analysis Program (EnMAP) will provide potential for producing improved remotely sensed maps in areas of exposed bedrock in advance of Arctic geology programs. This study investigates the usefulness of this moderate resolution (30m) sensor for predictive lithological mapping using simulated imagery to classify a map area dominated by mafic and felsic volcanics and minor sedimentary and volcaniclastic rocks in the Hope Bay Greenstone Belt of the Northwest Territories. The assessment also included the classification of high resolution and fidelity airborne (ProSpecTIR–SPECIM Dual sensor) hyperspectral imagery for comparison to understand the impact of combined lower signal-to-noise ratio (SNR), and spectral and spatial resolutions associated with EnMap. The performance of both sensors was assessed through statistical analysis of the classification results based on partial unmixing of the data as well as common geological band indices. The results obtained from these analyses were compared to a detailed published geological map of the study area. Both sensors, the airborne ProSpecTIR–SPECIM and spaceborne EnMap, provided good results however despite the simulated EnMap data’s lower resolution and SNR, the results showed it to have greater statistical accuracy and to be visually representative of the mapped geology. The results demonstrated that EnMap satellite hyperspectral technology is an effective tool for mapping lithology in the Canadian North. The discrimination of rock compositions was successful when their occurrences were spatially large and abundant; however, it was identified that spectral similarity between unit classes and spectral variability within classes are critical factors in mapping lithology. Graduate