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Hyperspectral Sensing – Imaging Spectroscopy
Spectral, – 200+ bands Spatial
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What is Hyperspectral Sensing?
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Data Cube – a way to visualize the data
Z = Spectral Bands X Y
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Multispectral Hyperspectral
Each pixel Discrete bands Continuous spectrum Reflectance Reflectance Wavelength Wavelength
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Multispectral vs. Hyperspectral Data
Multispectral, e.g., Landsat TM Hyperspectral, e.g., AVIRIS Reflectance Wavelength
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Diagnostic / identifying characteristics are lost in wide bands
Spectra of two materials with (very) different reflectance and absorption properties. If sensed with a wide band, Reflectance they will have the same response and cannot be discriminated or identified. Wavelength Diagnostic / identifying characteristics are lost in wide bands
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Imaging Spectrometry Concept
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Analysis of Hyperspectral Data -- Approaches
Wavelength Reflectance Direct identification using diagnostic absorption and reflection features Comparison to laboratory and field measured spectra
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Crop Identification and Inventory based solely on the spectra
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Reflectance Spectra of Minerals
Relative Reflectance Wavelength, μm
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Mineral Detection and Mapping
Reflectance Wavelength, μm Mineral Detection and Mapping
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Mineral Maps from Hyperspectral Data
True Color Image
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University of Minnesota, Remote Sensing Lab and Water Resources Center
River Airborne Hyperspectral Remote Sensing 1.5 2 2.5 3 3.5 4 4.5 5 5.5 400 500 600 700 800 900 Wavelength (nm) Reflectance % Confluence of Minnesota and Mississippi Rivers University of Minnesota, Remote Sensing Lab and Water Resources Center
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Satellite Hyperspectral Sensors
Hyperion On E0-1 (NASA) satellite 220 bands, 0.4 – 2.5 μm 12-bit radiometric resolution 30 m spatial resolution 7.5 km swath (= narrow)
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Summary Hyperspectral sensing and analysis provides increased information compared to multispectral data A fast growing technology - New sensors, new classification algorithms, and new image processing algorithms are being developed Applications are being developed as the technology develops Wavelength, μm Reflectance
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