Digital Imaging and Remote Sensing Laboratory Sensor Characteristics.

Slides:



Advertisements
Similar presentations
1 ATST Imager and Slit Viewer Optics Ming Liang. 2 Optical layout of the telescope, relay optics, beam reducer and imager. Optical Layouts.
Advertisements

A Graphical Operator Framework for Signature Detection in Hyperspectral Imagery David Messinger, Ph.D. Digital Imaging and Remote Sensing Laboratory Chester.
Aerial Photography Aerial platforms are primarily stable wing aircraft. Aircraft are often used to collect very detailed images and facilitate the collection.
 PART Absorption Spectrometer Dr. S. M. Condren SourceWavelength SelectorDetector Signal Processor Readout Sample.
Resolution Resolving power Measuring of the ability of a sensor to distinguish between signals that are spatially near or spectrally similar.
Some Basic Concepts of Remote Sensing
Resolution.
Pre-launch Characterization of the CERES Flight Model 5 (FM5) Instrument on NPP S. Thomas a, K. J. Priestley b, M. Shankar a, N. P. Smith a, M. G. Timcoe.
1 PHYSICS Demonstration of a Dualband IR imaging Spectrometer Brian P. Beecken Physics Dept., Bethel University Paul D. LeVan Air Force Research Lab, Kirtland.
Orbits and Sensors Multispectral Sensors
Line scanners Chapter 6. Frame capture systems collect an image of a scene of one instant in time The scanner records a narrow swath perpendicular to.
Satellite orbits.
Lecture 6 Multispectral Remote Sensing Systems. Overview Overview.
Remote sensing in meteorology
1 PHYSICS Progress on characterization of a dualband IR imaging spectrometer Brian Beecken, Cory Lindh, and Randall Johnson Physics Department, Bethel.
Hyperspectral Imagery
Interference and Diffraction
Lecture 2 Photographs and digital mages Friday, 7 January 2011 Reading assignment: Ch 1.5 data acquisition & interpretation Ch 2.1, 2.5 digital imaging.
Spectroscopy of Stratospheric Molecular O3
Meteorological satellites – National Oceanographic and Atmospheric Administration (NOAA)-Polar Orbiting Environmental Satellite (POES) Orbital characteristics.
Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute.
Astronomical Spectroscopy
Satellites and Sensors
Remote Sensing Hyperspectral Remote Sensing. 1. Hyperspectral Remote Sensing ► Collects image data in many narrow contiguous spectral bands through the.
The Mid-Infrared Instrument (MIRI) Medium Resolution Spectrometer for JWST Martyn Wells MIRI EC & UKATC.
1 Remote Sensing and Image Processing: 7 Dr. Mathias (Mat) Disney UCL Geography Office: 301, 3rd Floor, Chandler House Tel: (x24290)
Dr. Garver GEO 420 Sensors. So far we have discussed the nature and properties of electromagnetic radiation Sensors - gather and process information detect.
Hyperspectral remote sensing (Imaging Spectroscopy)
Resolution A sensor's various resolutions are very important characteristics. These resolution categories include: spatial spectral temporal radiometric.
Resolution Resolution. Landsat ETM+ image Learning Objectives Be able to name and define the four types of data resolution. Be able to calculate the.
14 October Observational Astronomy SPECTROSCOPY and spectrometers Kitchin, pp
18 October Observational Astronomy SPECTROSCOPY and spectrometers Kitchin, pp
Remote Sensing and Image Processing: 7 Dr. Hassan J. Eghbali.
DECam Daily Flatfield Calibration DECam calibration workshop, TAMU April 20 th, 2009 Jean-Philippe Rheault, Texas A&M University.
Remote Sensing Data Acquisition. 1. Major Remote Sensing Systems.
Headwall Instrument Overview Laboratory Characterizations Geo-Location Field Characterization Data Product Description References.
Mirza Muhammad Waqar HYPERSPECTRAL REMOTE SENSING - SENSORS 1 Contact:
Optical & Radiometric Conceptual Design of EMAS Thermal Port Upgrade Kickoff Meeting June 29, 2010 Roy W. Esplin.
14 ARM Science Team Meeting, Albuquerque, NM, March 21-26, 2004 Canada Centre for Remote Sensing - Centre canadien de télédétection Geomatics Canada Natural.
1 Reflected Solar Calibration Demonstration System - SOLARIS K. Thome, D. Jennings, B. McAndrew, J. McCorkel, P. Thompson NASA/GSFC.
CHARACTERISTICS OF OPTICAL SENSORS Course: Introduction to RS & DIP Mirza Muhammad Waqar Contact: EXT:2257 RG610.
Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Sensor Modeling in DIRSIG June 10, 2004 Cindy Scigaj Dr. John Schott.
OL 750 Measurement Systems OL 750 Measurement Systems Optronic Laboratories, Inc.
Low Polarization Optical System Design Anna-Britt Mahler Polarization Laboratory Group College of Optical Sciences.
Hyperspectral remote sensing
State of Engineering in Precision Agriculture, Boundaries and Limits for Agronomy.
Data Models, Pixels, and Satellite Bands. Understand the differences between raster and vector data. What are digital numbers (DNs) and what do they.
Geosynchronous Orbit A satellite in geosynchronous orbit circles the earth once each day. The time it takes for a satellite to orbit the earth is called.
GSFC/Spinhirne 03/13/2002 Multispectral and Stereo Infrared Cloud Observations by COVIR (Compact Visible and Infrared Imaging Radiometer) J. Spinhirne,
Interactions of EMR with the Earth’s Surface
Electro-optical systems Sensor Resolution
# x pixels Geometry # Detector elements Detector Element Sizes Array Size Detector Element Sizes # Detector elements Pictorial diagram showing detector.
UNIT 2 – MODULE 5: Multispectral, Thermal & Hyperspectral Sensing
Orbits and Sensors Multispectral Sensors. Satellite Orbits Orbital parameters can be tuned to produce particular, useful orbits Geostationary Sun synchronous.
2015 GSICS Annual Meeting, Deli India March 16~20, 2015 Xiuqing Hu National Satellite Meteorological Center, CMA Yupeng Wang, Wei Fang Changchun Institute.
Pre-launch Characteristics and Calibration
Hyperspectral Sensing – Imaging Spectroscopy
Basic Concepts of Remote Sensing
Hyperspectral Remote Sensing
Lunar Observation with
AIRS (Atmospheric Infrared Sounder) Instrument Characteristics
Hyperspectral Image preprocessing
What Is Spectral Imaging? An Introduction
Instrument Considerations
Early calibration results of FY-4A/GIIRS during in-orbit testing
OL 750 Measurement Systems
Remote sensing in meteorology
Hyperspectral Terminology
Hyperspectral Remote Sensing
Presentation transcript:

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 2 MODIS The MODerate resolution Imaging Spectrometer instrument (MODIS) the first operational space- based spectrometer. Its requirements for wide spectral coverage (VIS to LWIR) wide field of view, and a range of spectral resolutions resulted in a conventional line scanner design with multiple lines per rotation.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 3 MODIS (cont’d) Small linear arrays are located perpendicular to the scan direction with individual filters for each band. Multiple focal planes are used for the various detector materials. 8, 16, or 32 lines will be scanned per mirror sweep at 1000, 500, or 250 m nominal GIFOV.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 4 Sensors: Bandpass Filter Spectrometers – Line Scan/Whiskbroom MODIS: Moderate Resolution Imaging Spectroradiometer Solar diffuser Blackbody reference Double-sided scan mirror Aperture cover Spectroradiometric calibrator Main electronics module Space view & lunar calibration port Radiative cooler door & earth shield Thermal blanket

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 5 MODIS 39 channels (36 bands 3 with 2 gains) 1500 km swath repeat coverage of the globe every 2 days cloud, sea, and land monitoring

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 6 MODIS (partial scene 3/6/00)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 7 Types of multispectral imaging systems Spectral Line Scanners (cont’d) The basic spectrometer designs are extensions of the whisk broom or line scanners and the push broom scanners

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 8 Airborne Imaging Spectrometer Airborne Imaging Spectrometer Spectral Line Scanners (cont’d) One of the earliest experimental systems was NASA’s Airborne Imaging Spectrometer (AIS) flown in the mid 1980’s. It used the 2-d array design originally with a 32 x 32 element detector and later with a 64 x 64 element array (HgCdTe) operated from and respectively.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 9 Benefits of spectrometer data and the limitation of AIS as an imager Benefits of spectrometer data and the limitation of AIS as an imager Spectral Line Scanners (con’t)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 10 Comparison of AIS-1 and AIS-2 performance parameters (cont’d) Comparison of AIS-1 and AIS-2 performance parameters Spectral Line Scanners (cont’d) IFOV, mrad Ground IFOV, m at 6-km altitude FOV, deg Swath width, m at 6-km altitude Spectral sampling interval, nm Data rate, kbps Spectral sampling Short-wavelength mode,  m Long-wavelength mode,  m

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 11 AVIRIS AVIRIS Spectral Line Scanners (cont’d) At that time, limitations in detector technology precluded a large array and still limit 2-D array approaches. NASA chooses a whisk broom array spectrometer for its follow-on research activity. The airborne visible infrared imaging spectrometer (AVIRIS) schematic design and conceptual approach are shown in the following figures

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 12 Spectral Line Scanners Linear array Diffraction grating Aperture Telescope Oscillating scan mirror Scan Track Ground track

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 13 Spectral Line Scanners AVIRIS ( airborne visible infrared imaging spectrometer) MISI (Modular Imaging Spectrometer Instrument) CASI

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 14 Conceptual layout of the AVIRIS optical system (cont’d) Conceptual layout of the AVIRIS optical system Spectral Line Scanners (cont’d)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 15 AVIRIS Performance characteristics (cont’d) AVIRIS Performance characteristics Spectral Line Scanners (cont’d) Spectral coverage Spectral sampling interval, nm Number of spectral bands 224 IFOV, mrad0.95 Ground IFOV, m at 20-km altitude20 FOV, deg30 Swath width, km at 20-km altitude10.5 Number of cross-track pixels614 Data encoding, bits10 Data rate, Mbps17 Radiometric calibration accuracy, % Absolute6 Spectral band-to-band0.5 Spectral calibration accuracy, nm1-2 Parameter Performance

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 16 AVIRIS image cube of Moffet Field, CA (cont’d) AVIRIS image cube of Moffet Field, CA Spectral Line Scanners (cont’d) 224 channels.4  m to 2.5  m spectral bandwidth ~10 nm (Image courtesy of NASA JPL.)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 17 AVIRIS signal-to-noise

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 18 AVIRIS Scene Lake Ontario Shoreline Rochester Embayment May 20, 1999

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 19 MISI (Modular Imaging Spectrometer Instrument) (cont’d) MISI (Modular Imaging Spectrometer Instrument) Spectral Line Scanners (cont’d)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 20 Modular Imaging Spectrometer Instrument (MISI) Airborne line scanner 70 VNIR channels 5 thermal channels Nominal 2 milliradian FOV (20ft GSD at 10000ft) Sharpening bands in VIS and LWIR spectrometers thermal focal plane scan mirror On-board blackbody

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 21 thermal MISI image of nuclear power plant discharge into Lake Ontario September 3, 1999 Three of MISI’s 70 VNIR channels

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 22 MISI Examples Irodequoit Bay Charlotte Pier Ginna Power Plant

Digital Imaging and Remote Sensing Laboratory Push Broom Dispersion Systems Pushbroom axis Spectral axis Area arrays Diffraction grating Collimator Slit Optics Ground Track AIS (diffraction grating) HYDICE (prism) SEBASS (prism) Hyperion (EO-1)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 24 HYDICE Sensor HYDICE Sensor Push Broom Dispersion Systems (con’t) The Hyperspectral Digital Imagery Collection Experiment (HYDICE) uses a 2-d array push broom approach with a prism monochromator. The optical layout is on the following slide. The system is a technology demonstration airborne test bed for future satellite systems. The optics are designed to fit in a mapping camera mount.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 25 HYDICE Sensor HYDICE Sensor Push Broom Dispersion Systems (con’t) The system IFOV is 0.5 m rad and flies in a C141 at 2 to 14 km (nominal 6) with a GIFOV of 1 to 7 meters. The FOV is 8.94 degrees yielding coverage of 0.3 to 2.2 km.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 26 HYDICE Sensor HYDICE Sensor Push Broom Dispersion Systems (con’t) The prism design yields variable spectral bandwidth as shown in Figure 2. The bandwidth in the blue channels will be increased by averaging in the spectral direction at the extreme end of the blue to maintain a nominal bandwidth of approximately 10 nm.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 27 HYDICE Sensor HYDICE Sensor Push Broom Dispersion Systems (con’t) Fig 2. Spectral bandwidth (FWHM) as a function of wavelength

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 28 HYDICE Sensor HYDICE Sensor Push Broom Dispersion Systems (con’t) The wide spectral range from µm is achieved with a single cooled InSb detector (65K) array as shown in Figure 3. Special passivation and anti reflection coating were developed to maintain acceptable sensitivity and SNR over the entire range.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 29 HYDICE Sensor HYDICE Sensor Push Broom Dispersion Systems (con’t) Fig 3. Focal plane array architecture

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 30 HYDICE Sensor HYDICE Sensor Push Broom Dispersion Systems (con’t) The expected HYDICE SNR is shown in Figure 4 for its spec point of a 5% reflector (N.B. this system was designed for water sensors.)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 31 SEBASS Sensor Highlights SEBASS Sensor Highlights Push Broom Dispersion Systems (con’t) Spatially Enhanced Broadband Array Spectrograph System Developed by the Aerospace Corporation Prototype Hyperspectral Infrared Sensor Material Identification using 3-5 and 8-14 µm signatures

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 32 SEBASS Sensor Geometry SEBASS Sensor Geometry Push Broom Dispersion Systems (con’t) Pushbroom Scanner Disperses line image into its spectral components Detectors are 128x128 pixel “Blocked Impurity Band” – manufactured by Rockwell International – Built as part of NASA SIRTF effort Spatial Resolution of 0.5 and 3 meters and feet respectively 1 milliradian per pixel IFOV (~7 degrees FOV)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 33

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 34 Spectral purity issues: spatial/temporal/sensor artifacts (smile) The SEBASS Sensor is a Pushbroom Scanner

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 35 Pushbroom axis Spectral axis Area arrays Diffraction grating Collimator Slit Optics Ground Track Spectral purity issues: spatial/temporal/sensor artifacts (smile) Push Broom Dispersion Systems

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 36 Spectral purity issues: spatial/temporal/sensor artifacts (smile)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 37 Linear Wedge Filter Spectrometer Atmospheric Corrector on EO-1 wedge filter 2D array wedge interference filter side view of filter

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 38 Fourier transform instruments At longer wavelengths, the spectral features become very narrow. This is particularly important in the 8-14 µm region where many gaseous absorption features are manifest. It can be difficult to achieve sufficient spectral resolution at these wavelengths. In the laboratory Fourier, transform spectrometers are often used for detailed characterization of the spectra at these wavelengths.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 39 Fourier transform instruments Fig 1. IFTS raw data cube

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 40 Fourier transform instruments Figure 1 shows the concept behind an FTIR imaging spectrometer where a 2-d array is located at the image plane (interference plane). Each spatial 2-d sample represents a different time sample corresponding to a different location of the moving mirror in the interferometer and, therefore, a different interference pattern. For any pixel, the Fourier transform of the interference samples (interferogram) is the spectrum for that pixel. Thus, from the interferogram image cube, a conventional spectral image cube can be created by a 1- dimensional Fourier transform of each pixel.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 41 Fourier transform instruments Fig 2. A sketch of the optics of an Imaging Fourier Transform Spectrometer

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 42 Fourier transform instruments Figure 2 shows a conceptual diagram of an FTIR imaging instrument. The object plane would typically be the focal plane of the conventional collection optics. The 2-d array is located at the image plane. The primary advantage of the imaging FT instrument is that spectral resolution is primarily a function of the number of samples taken. Therefore, high spectral resolution can be achieved without great cost in detector technology.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 43 Fourier transform instruments Note a major drawback of this approach is the assumption of constant FOV during motion of the mirror.

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 44 Many variations in design of IFTS available Michelson – Collects spectral information over time – Spatial information collected like an image Sagnac – Spectral information collected spatially (over one FPA dimension) – Spatial info collected over other FPA dimension + pushbroom scanning Fourier transform instruments

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 45 Michelson Interferometer Frame camera – Must stare at one point during the collection time Interferogram collection method – Collect interference image – Move mirror (change OPD) – Change view angle – Repeat Object Plane Image Plane Fixed Mirror Moving Mirror y f f’ y’

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 46 Michelson Interferometer Input spectrum changes with view angle and pointing accuracy Collects one slice of image cube at every time interval

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 47 Sagnac Interferometer Pushbroom Scanner Collect entire interferogram over one axis of the FPA Each interferogram is collected instantaneously Examples – FTHSI on MightySat II.1 – MTU sensor for water quality of GL Mirrors Spherical lens Cylindrical lens Beam splitter Aperture Telescope focus detector

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 48 Spectral databases – mixed pixels Lab & Field Spectra – (diffuse hemispheric- BDRF ASD) USGS EOS ASTER Spectral Library

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 49 from: ASTER Spectral Library

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 50 Grass asphalt roofing Brick 1.0 ASD FieldSpec

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 51 BRDF While BRDF effects overall reflectance levels: to first order spectral contrast in materials with similar texture is not significantly impacted by normal variations in viewing conditions. (In many cases, this may not be a valid assumption: beach sand vs. plowed field.)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 52 BRDF (cont’d)

Digital Imaging and Remote Sensing Laboratory Sensor Characteristics 53 Sensor Light trap specular ray sample Incident flux Integrating Sphere Schematic concept for measuring total and diffuse reflectance