Speaker Dr Alex Goetz Reporter Susan Buckingham Title Hyperspectral Imaging Hyperspectral Remote Sensing What is hyperspectral remote sensing Contiguous spectrometry which can critically sample absorption features especially in the 2 2 5 region where fundamental vibrations and overtones create unique spectral signatures for minerals Critical contiguous sampling often 10 nm creates characteristic spectra that can be identified using libraries of spectral signals In addition such hyper sampling provides enough data so that data can be unmixed Mixing of signals occurs when two or more materials reflect energy back towards the sensor The ability to unmix reflectance data implies that hyperspectral analysis essentially allows for a trade off of spatial resolution for spectral resolution Early Development Hyperspectral theory was tested using SMIR flown on Shuttle in the 80 s Tests successfully identified minerals in Egypt proving that there was critical information beyond 1 2 um Flow on tests were provided by AIS Airborne Imaging Spectrometer flown on theC130 over Cuprite Flight over Cuprite sold idea that spectral reflectance data could successfully identify geologic units During a second flight a spectral unknown was discovered buddingtonite only known to exist in 5 other locations and considered at the time to be an indicator mineral for gold deposits later this proved to be untrue The excitement over the results lead to the development of AVIRIS Airborne Visible and Infrared Imaging Spectrometer AVIRIS is considered to be the best calibrated hyperspectral imager today Atmospheric Corrections Hyperspectral imagery requires some level of atmospheric correction There are two critical water absorption bands 1 38 1 88 that are almost always saturated In addition there are absorption features created by 03 CO2 as well The plank curve shows us that the signal past 1 2 um is very weak thus the atmosphere plays a greater role disrupting the spectral signal The effect of the atmosphere must be removed in order to actually determine the characteristic spectra of materials There are a variety of methods used to atmospherically correct data Most widely used is atmospheric modeling models are developed to estimate the influence of various gases in the atmosphere on the radiance ATREM is 1 model that has been used successfully It uses develops a ratio based on water measured within 3 bands and recreates a water vapor image HATCH is another program developed at the University of Colorado Boulder which has also proved successful in correcting reflectance data At one point it was assumed that at in arid environments the effect of water vapor would be minimal Even in arid environments ie Rogers dry lake there are cirrus clouds that alter radiance requiring each pixel be evaluated separately Cirrus clouds provide additional problems by increasing path radience They have made NDVI measurements extremely difficult Hyperspectral Imagers AVIRIS HYMAP commercial SacTIR push broom ex government personnel Hydice military CASI Canadian Hyperion EO1 Hyperion Earth Observing 1 Tested technology for a Landsat follow on The sensor was not meant to be a long term sensor Resolution 30m pixels 7 7 km swath 10 nm spectral resolution The detectors are not stable due to fluctuations with temperature This flaw results in stripped imagery Never the less the usefulness of this test sensor has been extensive Hyperspectral Applications Wild fire temperature observations Carbon Sequestration Vegetation species distinction HERO mission Geology Mapping