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 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)

AVIRIS:Airborne Visible InfraRed Imaging Spectrometer

Hyperspectral sensing: AVIRIS

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: http://eo1.usgs.gov/hyperion.php

EO-1 ALI & Hyperion designed to work in tandem

Hyperion over New Jersey EO1H0140312004120110PY_PF1_01 2004/04/29, 0 to 9% Cloud Cover EO1H0140312004120110PY_PF1_01 2004/04/29, 0 to 9% Cloud Cover EO1H0140312004120110PY_PF1_01 2004/04/29, 0 to 9% Cloud Cover EO1H0140312004184110PX_SGS_01 2004/07/02, 10% to 19% Cloud Cover EO1H0140312004184110PX_SGS_01 2004/07/02, 10% to 19% Cloud Cover

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/viewFi le/49049/35397 http://www.csr.utexas.edu/projects/rs/hrs/hyper.h tml A decent 3-page summary: http://citeseerx.ist.psu.edu/viewdoc/download?d oi=10.1.1.485.4789&rep=rep1&type=pdf 258 pages, if you need help sleeping: http://www.umbc.edu/rssipl/people/aplaza/Pap ers/BookChapters/2012.EUFAR.Hyperspectral.pdf

31 pages. Looks good. http://www. umbc 31 pages. Looks good. http://www.umbc.edu/rssipl/people/aplaza/Pap ers/Journals/2013.GRSM.Hyperspectral.pdf