High Performance Computing in Remote Sensing - Chapter 14

Chapter 14 AVIRIS and Related 21st Century Imaging Spectrometers for Earth and Space Science Robert O. Green, Jet Propulsion Laboratory, California Institute of Technology Contents 14.1 Introduction ........................................................... 336 14.2 AVIRIS and the Imaging Spectroscopy Measurement ................... 338 14.2.1 The AVIRIS Imaging Spectrometer Characteristics .............. 339 14.2.2 The AVIRIS Measured Signal ................................... 342 14.2.3 Range of Investigations Pursued with AVIRIS Measurements .... 345 14.2.4 The AVIRIS Data Archive and Selected Imaging Spectroscopy Analysis Algorithms ............................................ 346 14.3 Objectives and Characteristics of a Spaceborne Imaging Spectrometer for the Moon ............................................. 348 14.3.1 Objectives of the Moon Mineralogy Mapper ..................... 348 14.3.2 Characteristics of the M3 Imaging Spectrometer ................. 348 14.3.3 Prospects for the M3 Imaging Spectrometer Data Set ............. 351 14.4 Objectives and Characteristics of a Future Spaceborne Imaging Spectrometer for the Earth ............................................. 352 14.4.1 Objectives of an Earth Imaging Spectrometer for Measuring the State of Terrestrial and Aquatic Ecosystems .................. 352 14.4.2 Characteristics of an Ecosystem Focused Earth Imaging Spectrometer .......................................... 353 14.4.3 Roles for High-Performance Computing ......................... 354 14.5 Acknowledgments ..................................................... 356 References .................................................................. 356 Imagingspectroscopy(alsoknownashyperspectralimaging)isafieldofscientificin-vestigation based upon the measurement and analysis of spectra measured as images. Thehumaneyequalitativelymeasuresthreecolors(blue,green,andred)inthevisible portion of the electromagnetic spectrum when viewing the environment. The human eye-brain combination is a powerful observing system, however, it generally pro-vides a non-quantitative perspective of the local environment. Imaging spectrometer 335 © 2008 by Taylor & Francis Group, LLC 336 High-Performance Computing in Remote Sensing instruments typically measure hundreds of colors (spectral channels) across a much wider spectral range. These hundreds of spectral channels are recorded quantitatively as spectra for every spatial element in an image. The measured spectra provide the basisforanewapproachtounderstandingtheenvironmentfromaremoteperspective based in the physics, chemistry, and biology revealed by imaging spectroscopy. The measurement of hundreds of spectral channels for each spatial element of an image consisting of millions of spatial elements creates an important requirement for the use of high-performance computing. First, high-performance computing is required to acquire, store, and manipulate the large data sets collected. Second, to extract the physical, chemical, and biological information recorded in the remotely measured spectra requires the development and use of high-performance computing algorithms and analysis approaches. This chapter uses the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) to review the critical characteristics of an imaging spectrometer instrument and the corresponding characteristics of the measured spectra. The wide range of scientific research as well as application objectives pursued with AVIRIS is briefly presented. Rolesfortheapplicationofhigh-performancecomputingmethodstoAVIRISdatasets are discussed. Next in the chapter a review is given of the characteristics and mea-surement objectives of the Moon Mineralogy Mapper (M3) imaging spectrometer planned for launch in 2008. This is the first imaging spectrometer designed to acquire highprecisionandhighuniformityspectralmeasurementsofanentireplanetary-sized rocky body in our solar system. The size of the expected data set and roles for high performance computing are discussed. Finally, a review is given of one design for an Earthimagingspectrometerfocusedoninvestigationofterrestrialandaquaticecosys-tem status and composition. This imaging spectrometer has the potential to deliver calibrated spectra for the entire land and coastal regions of the Earth every 19 days. The size of the data sets generated and the sophistication of the algorithms needed for full analysis provide a clear demand for high-performance computing. Imaging spectroscopyandthedatasetscollectedprovideanimportantbasisfortheuseofhigh-performance computing from data collection to data storage through to data analysis. 14.1 Introduction Imaging spectroscopy is based in the field of spectroscopy. Sir Isaac Newton first separated the color of white light into the rainbow in the late 1600s. In the 1800s, Joseph von Fraunhofer and others discovered absorption lines in the solar spectrum and light emitted by flames. Through investigation of these absorption lines, the linkage between composition and signatures in a spectrum of light was established. The field of spectroscopy has been pursued by astronomers for more than 100 years to understand the properties of stars as well as planets in our solar system. On Earth, spectroscopy has been used by physicists, chemists, and biologist to investigate the properties of materials relevant to their respective disciplines. In the later half of the © 2008 by Taylor & Francis Group, LLC AVIRIS and Related 21st Century Imaging Spectrometers 337 Conifer Grass Kaolinite Gypsum 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Broad Leaf Jarosite Sage_Brush Dolomite NPV Hematite 0.0 400 700 1000 1300 1600 1900 2200 2500 Wavelength (nm) Figure14.1 Alimitedsetofrockformingmineralsandvegetationreflectancespec-tra measured from 400 to 2500 nm in the solar reflected light spectrum. NPV cor-responds to non-photosynthetic vegetation. A wide diversity of composition related absorption and scattering signatures in nature are illustrated by these materials. 20th centuryEarthscientistsdevelopedspaceborneinstrumentsthatviewtheearthina fewspectralbandscapturingaportionofthespectralinformationinreflectedlight.The AVHRR,LandSat,andSPOTareimportantexamplesofthismultispectralapproachto remotesensingoftheEarth.However,thefewspectralbandsofmultispectralsatellites fail to capture the complete diversity of the compositional information present in the reflected energy spectrum of the Earth. Figure 14.1 shows a set of measured reflectancespectrafromalimitedsetofrockformingmineralsandvegetationspectra. Awidediversityofcomposition-relatedabsorptionandscatteringsignaturesexistfor such materials. Figure 14.2 shows these selected reflectance spectra convolved to the band passes of the LandSat Thematic Mapper. When mixtures and illumination factors are included, the 6 multispectral measurements of the multispectral Thematic Mapper are insufficient to unambiguously identify the 10 materials present. In the 1970s,realizationofthelimitationsofthemultispectralapproachwhenfacedwiththe diversityandcomplexityofspectralsignaturesfoundonthesurfaceoftheEarthleadto theconceptofanimagingspectrometer.Theuseofanimagingspectrometerwasalso understood to be valid for scientific missions to other planets and objects in our solar system.Onlyinthelate1970sdidthedetectorarray,electronics,computer,andoptical technology reach significant maturity to allow design of an imaging spectrometer. With the arrival of these technologies and scientific impetus, the Airborne Imaging Spectrometer (AIS) was proposed and built at the Jet Propulsion Laboratory [1]. The © 2008 by Taylor & Francis Group, LLC 338 High-Performance Computing in Remote Sensing Conifer Grass Kaolinite Gypsum 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Broad Leaf Jarosite Sage_Brush Dolomite NPV Hematite 0.0 400 700 1000 1300 1600 1900 2200 2500 Wavelength (nm) Figure 14.2 The spectral signatures of a limited set of mineral and vegetation spec-traconvolvedtothesixsolarreflectedrangebandpassesofthemultispectralLandSat Thematic Mapper. When mixtures and illumination factors are included, the six mul-tispectral measurements are insufficient to unambiguously identify the wide range of possible materials present on the surface of the Earth. AISfirstflewin1982aswellasinseveralsubsequentyearsasatechnologyandscience demonstration experiment. Concurrently with the development of the AIS a role for high-performancecomputingwasidentifiedandpursued[2].TheAISinstrumenthad limitedspectralcoverageaswellaslimitedspatialcoverage.Evenasademonstration experiment, the success of the AIS led to the formulation of the proposal for the Airborne Visible/Infrared Imaging Spectrometer. This next generation instrument was specified to measure the complete solar reflected spectrum from 400 to 2500 nm and to capture a significant spatial image domain. The broader spectral and spatial domain of this full range instrument continued to grow the role for high-performance computing in the field of imaging spectroscopy. 14.2 AVIRIS and the Imaging Spectroscopy Measurement The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) [3, 4] measures the total upwelling spectral radiance in the spectral range from 380 to 2510 nm at ap-proximately 10 nm sampling intervals and spectral response function. Figure 14.3 shows a plot of the AVIRIS spectral range in conjunction with an atmospheric trans-mittance spectrum. Also shown for comparison are the spectral response functions © 2008 by Taylor & Francis Group, LLC AVIRIS and Related 21st Century Imaging Spectrometers 339 AVIRIS 224 Contiguous Spectral Channels 1 0.9 0.8 0.7 0.6 0.5 0.4 Atmosphere Transmittance 0.3 0.2 Landsat TM 6 Multispectral 0.1 Bands 0400 700 1000 1300 1600 1900 2200 2500 Wavelength (nm) Figure 14.3 AVIRIS spectral range and sampling with a transmittance spectrum of the atmosphere and the six LandSat TM multi-spectral bands in the solar reflected spectrum. of the multispectral LandSat Thematic Mapper. With AVIRIS a complete spectrum is measured with contiguous spectral channels. Across this spectral range the atmo-sphere transmits energy reflected from the surface, except in the spectral regions of strong water vapor absorption centered near 1400 and 1900 nm. These strong water vapor absorption regions are used for cirrus cloud detection and compensation. Mea-surement of this complete spectral range allows AVIRIS to be used for investigations beyond those possible with a multispectral measurement. In addition, measurement of the full spectrum allows use of new, more accurate, computationally intensive algorithms that require high-performance computing. In the spatial domain, AVIRIS measures spectra as images with a 20 m spatial resolution and an 11 km swath with up to 1000 km image length from NASA’s ER-2 aircraft flying at 20 km altitude. On the Twin Otter aircraft flying at 4 km altitude, the spatialresolutionis4mwitha2kmswathandupto200kmimagelength.Figure14.4 shows an AVIRIS data set collected over the southern San Francisco Bay, California, from the ER-2 platform in image cube representation. The spectrum measured for each spatial element in the data set may be used to pursue specific scientific research questions via the recorded interaction of light with matter. 14.2.1 The AVIRIS Imaging Spectrometer Characteristics ThefullsetofAVIRISspectral,radiometric,spatial,temporal,anduniformitycharac-teristicsaregiveninTable14.1.Thesecharacteristicshavebeenrefinedandimproved since the initial development of AVIRIS based upon the requirements from scientists © 2008 by Taylor & Francis Group, LLC ... - tailieumienphi.vn