470 likes | 1k Views
Hyperspectral Remote Sensing. Hyperspectral Sensing. Multiple channels (50+) at fine spectral resolution (e.g., 5 nm in width) across the full spectrum from VIS-NIR-MIR to capture full reflectance spectrum and distinguish narrow absorption features. Reflectance from green plant leaves.
E N D
Hyperspectral Sensing • Multiple channels (50+) at fine spectral resolution (e.g., 5 nm in width) across the full spectrum from VIS-NIR-MIR to capture full reflectance spectrum and distinguish narrow absorption features
Reflectance from green plant leaves • Chlorophyll absorbs in 430-450 and 650-680nm region. The blue region overlaps with carotenoid absorption, so focus is on red region. • Peak reflectance in leaves in near infrared (.7-1.2um) up to 60% of infrared energy per leaf is scattered up or down due to cell wall size, shape, leaf condition (age, stress, disease), etc. • Reflectance in Mid IR (2-4um) influenced by water content-water absorbs IR energy, so live leaves reduce mid IR return
Hand-held Spectroradiometer • Calibrated vs “dark” vs. “bright” reference standard provided (spectralon white panel - #6 in image) • Can use “passive” sensor to record reflected sunlight or “active” illuminated sensor clip (#4)
Compact Airborne Spectrographic Imager (CASI) • Hyperspectral: 288 channels between 0.4-0.9 mm; each channel 0.018mm wide • Spatial resolution depends on flying height of aircraft and number of channels acquired CASI 550 For more info: www.itres.com
EO-1: Hyperion • The Hyperion collects 220 unique spectral channels ranging from 0.357 to 2.576 micrometers with a 10-nm bandwidth. • The instrument operates in a pushbroom fashion, with a spatial resolution of 30 meters for all bands. • The standard scene width is 7.7 kilometers. Standard scene length is 42 kilometers, with an optional increased scene length of 185 kilometers • More info: https://eo1.usgs.gov/sensors/hyperion
EO-1 • ALI & Hyperion designed to work in tandem
Hyperion Image EO1H0140312004120110PY 2004/04/29 R 800- G 650- B 550 Fallow field Active crop
Hyperion Image EO1H0140312004184110PX 2004/07/02 R 800- G 650- B 550 Conifer forest Deciduous forest
Hyperspectral Sensing: Analytical Techniques • Data Dimensionality and Noise Reduction: MNF • Ratio Indices • Derivative Spectroscopy • Spectral Angle or Spectroscopic Library Matching • Subpixel (linear spectral unmixing) analysis
http://www.ajol.info/index.php/wsa/article/viewFile/49049/35397http://www.ajol.info/index.php/wsa/article/viewFile/49049/35397 • http://www.csr.utexas.edu/projects/rs/hrs/hyper.html • Open Penn State RS class: https://open.ems.psu.edu/node/1354 • 258 pages, if you need help sleeping: http://www.umbc.edu/rssipl/people/aplaza/Papers/BookChapters/2012.EUFAR.Hyperspectral.pdf • http://www.mdpi.com/2072-4292/9/11/1110
31 pages. Looks good. http://www.umbc.edu/rssipl/people/aplaza/Papers/Journals/2013.GRSM.Hyperspectral.pdf