Multispectral Remote Sensing

Student Learning Outcomes Describe how multispectral remote sensing data are typically stored (matrix of pixels, rows, columns, brightness values, spectral bands, …). Differentiate between the following: Multi-, hyper-, and ultraspectral remote sensing systems Scanning and non-scanning systems Optical-mechanical and optical-electronic systems Cross-track and along-track scanners Pushbroom and whiskbroom scanners Geostationary and sun-synchronous satellite orbits Categorize the following sensors according to the above criteria: GOES, AVHRR, SeaWiFS, MODIS, Landsat, ASTER, SPOT, IRS, QuickBird, IKONOS, GeoEye-1, AVIRIS, Hyperion

Data Collection Detection of EM energy from AOI at sensor Recording of energy as analog electrical signal Onboard conversion of analog electric signal into digital value through analog-to-digital (A-to-D) conversion Return of data to earth Aircraft platform: data “flown” back to Earth Satellite platform: data “telemetered” to Earth receiving stations directly or indirectly via tracking and data relay satellites (TDRS) Ground: Data preprocessing, analysis, interpretation Distribution and use

Data Collection Most RS instruments (sensors) measure photons Photoelectric effect at the detector Electrons are emitted when a negatively charged, light-sensitive plate (detector) is subjected to a beam of photons Emitted electrons (numbers, intensity) can be collected and counted as a signal Magnitude of electric current (number of photoelectrons per unit time) is proportional to light intensity Kinetic energy of released photoelectrons varies with wavelength of the impinging radiation Detector material determines the EM wavelengths over which the detector will operate (e.g., silicon for visible light) Sensor detectors convert light into electrons that can be measured and converted into radiometric intensity value Light photons cause electrical charge that is directly related to the amount of incident radiant energy This analog signal is sampled electronically and converted into digital brightness values (8-bit: 0-255; 12-bit: 0-4,096) BVs obtained from A-to-D conversion may be stored and read by computer systems

Digital Image Terminology Digital RS data are stored as a matrix (array) of digital numbers, whereby each pixel has a location value (row i and column j) in the matrix and a brightness value (BV) for each of the individual spectral bands (k)  BVi, j, k Columns (j) 82 30 m 3 40 53 80 5 2 35 50 82 15 17 25 13 18 14 Rows (i)

Digital Image Terminology n spectral bands are registered to one another i and j for a pixel are the same in all bands a pixel’s BV may vary from band to band 10 15 17 18 16 20 22 21 24 23 25 Columns / Samples (j) Rows / Lines (i) Bands (k) (co-registered) 1 2 3 4 x-axis (j columns) y-axis (i rows)

Digital Image Terminology The BV (hence tone) of a pixel depends on the radiance recorded by the sensor and quantization level (i.e., radiometric resolution) BV (8-bit) 7-bit (0 – 127) 255 - white 127 - grey 0 - black 8-bit (0 –255) Grayscale 9-bit (0 –511) 12-bit (0 –1,023)

Multi-, Hyper-, Ultra- Multi-, Hyper-, and Ultra-Spectral RS Systems Collect reflected or emitted energy from features or areas of interest, typically in digital format Multispectral: Multiple (a few; > 2) wide, separated bands Hyperspectral: Hundreds of fairly narrow, contiguous bands Ultraspectral: Thousands of very narrow, contiguous bands

Sensor Types non-imaging non-scanning imaging Passive Active Image plane scanning Object plane scanning

Passive vs. Active Passive sensors Active sensors Detect electromagnetic radiation that is naturally reflected (visible, near-infrared, shortwave infrared) or emitted (thermal infrared) by objects Energy source = sun Active sensors Detect electromagnetic radiation that is backscattered from objects that are irradiated from artificially generated energy sources Energy sources = Radio, Sound, or Light Detection and Ranging systems

Scanning vs. Non-Scanning Scanning System System that senses a scene point by point (e.g., small areas within the scene) along successive lines over a finite time Involves movement of either the entire sensor or of one or more of its components Non-Scanning System (~ Framing system) Sensors that either don’t sweep (e.g., laser) or that produce an image instantaneously (e.g., camera, eye, TV)

Imaging vs. Non-Imaging System that measures the intensity of radiation as a function of position on the Earth’s surface so that a 2D-image of radiation intensity can be generated (e.g., cameras, scanners) Non-Imaging Either does not measure the intensity of radiation or does not do so as a function of position on the Earth’s surface (average of signal strength, etc.; 1D)

Object Plane Scanning Object plane scanner / Optical-mechanical: Contain essential mechanical component (e.g., moving mirror) that aids in scene scanning Images one target pixel at-a-time, and all pixels in a sequential fashion, from the object plane to the image plane Scanning mechanism (e.g., mirror) “points” the scanner to different target pixels in a sequential fashion

Image Plane Scanning Image plane scanner / Optical-electronic: Sensed radiation moves directly through the optics onto the linear or array detectors Images an entire scan line or frame at-a-time on the image plane Scanning takes place on the image plane Has larger array of detectors in the image plane than an object plane scanner

Cross-vs. Along-Track Scanners Cross-Track Scanners Use a rotating (spinning) or oscillating mirror to sweep along a line (long and narrow) or a series of adjacent lines traversing the ground Optical-mechanical Whiskbroom

Cross-vs. Along-Track Scanners Use a linear array of detectors: as platform advances along the track, radiation is received simultaneously at all detectors Optical-electronic Pushbroom

Passive Sensor Types Passive, non-scanning, non-imaging Microwave radiometer, magnetic sensor, gravimeter, Fourier spectrometer, etc. Passive, non-scanning, imaging Camera: monochrome, natural color, infrared, color infrared, etc. Passive, scanning, imaging, image plane scanning Optical-electronic scanner, TV camera, etc. Passive, scanning, imaging, object plane scanning Optical-mechanical scanner, microwave radiometer

Active Sensor Types Active, non-scanning, non-imaging Microwave radiometer, microwave altimeter, laser water depth meter, laser distance meter Active, scanning, imaging, image plane scanning Passive phase array radar Active, scanning, imaging, object plane scanning Real aperture radar, synthetic aperture radar

Detectors Discrete detectors Linear arrays Area arrays Have a single active area Linear arrays Have a few to several thousand detectors lined up in a row Area arrays Have two-dimensional area arrays

Sensor Type I Analog Frame Cameras Acquire traditional aerial photography Film with silver halide crystals (emulsion) instead of detectors

Sensor Type II Digital Frame Cameras based on Area Arrays Each spectral band has a filter and a separate area array Number of detectors = # of rows × # of columns × # of bands Leica Geosystems Emerge Digital Sensor System Vexcel UltraCam Large Format Camera Z/1 Digital Modular Camera

Sensor movement direction Sensor Type III Linear Array (“Pushbroom”) Similar to area array, but has only 1 row (line) of detectors Array is moved in a single direction, and a radiance reading is taken at regular intervals 1 linear array per spectral band; number of pixels contained in one row of an image equals the number of detectors Filters are used to restrict the wavelengths IFOV (1 detector) Linear array Objective lens Angular field of view Sensor movement direction Pixel width = easily calculated Pixel length = function of IFOV, sensor speed and detector sampling.

Sensor Type III Multispectral Imaging using Linear Arrays SPOT 1, 2, 3 HRV and SPOT 4, 5 HRVIR and Vegetation IRS LISS-III and -IV NASA Terra ASTER NASA Terra MISR DigitalGlobe QuickBird Space Imaging IKONOS ImageSat International EROS A1 ORBIMAGE OrbView-3 and -5 GeoEye-1 … HRV – High Resolution Visible HRVIR – High Resolution Visible Infrared IRS LISS – Indian Remote Sensing System Linear Imaging Self-scanning Sensor ASTER – Advanced Spaceborne Thermal Emission and Reflection Radiometer MISR – Multiangle Imaging Spectroradiometer ADS – Airborne Digital Sensor System

Direction of sensor movement Sensor Type IV Scanning Mirror and Single Discrete Detectors and Filters (“Whiskbroom”) 1 detector per spectral band Rotating mirror changes the angle of the incident light source (hence what portion of the ground is being detected) Filters restrict the wavelengths for each band Rotating mirror Swath width Filters restrict the wavelengths for each band Detector Angular field of view Pixel width = function of mirror rotation rate and IFOV Pixel length = function of IFOV, sensor speed and detector sampling rate Direction of sensor movement

Sensor Type V Scanning Mirror and Multiple Discrete Detectors and Filters (“Whiskbroom”) Linear array of detectors for each spectral band Mirror angles the light across multiple detectors instead of one Filters restrict the wavelengths for each band Pushbroom sensors: may have thousands of detectors per spectral band Scanning mirror sensors: usually only have a few detectors per spectral band (e.g., if there are 6 detectors per array, every 6th pixel in the image is from a given detector) Filters restrict the wavelengths for each band MSS scanning arrangement

Sensor Type VI Scanning Mirror and Multiple Discrete Detectors and Dispersing Element (“Whiskbroom”) Instead of wide band filters, this type has a dispersing element (prism) that breaks the incoming radiation into discrete wavelengths and disperses it across a linear array of detectors Rotating mirror and forward sensor movement create the spatial arrangement of pixels Advantage of dispersing element (vs. a set of filters): much smaller bands can be detected without a massive amount of additional hardware (there is not 1 filter per band as in the previous sensors)

Sensor Types IV, V, VI Multispectral Imaging using Scanning Mirrors and Discrete Detectors Landsat MSS Landsat TM Landsat ETM+ NOAA GOES NOAA AVHRR NASA and ORBIMAGE SeaWiFS Daedalus AMS NASA ATLAS … MSS – Multispectral Scanner TM – Thematic Mapper ETM+ - Enhanced Thematic Mapper Plus GOES – Geostationary Operational Environmental Satellite AVHRR – Advanced Very High Resolution Radiometer SeaWiFS – Sea-viewing Wide Field-of-view Sensor AMS – Aircraft Multispectral Scanner ATLAS – Airborne Terrestrial Applications Sensor

Sensor Type VII Hyperspectral Area Array Combines pushbroom linear array with a dispersing element (“imaging spectrometry using linear and area arrays”) NASA JPL AVIRIS CASI NASA Terra MODIS NASA EO-1 ALI, Hyperion, and LAC … AVIRIS – Airborne Visible / Infrared Imaging Spectrometer CASI – Compact Airborne Spectrographic Imager 1500 MODIS – Moderate Resolution Imaging Spectrometer EO – Earth Observer ALI – Advanced Land Imager LAC – LEISA Atmospheric Corrector

Many Types of RS Systems

Many Types of RS Systems

Comparison of Sensor Types Advantages Disadvantages Digital frame camera area array Well defined geometry; long integration time Many detectors required Linear array Uniform detector response in along-track direction; no mechanical scanner; somewhat long integration time Many detectors per line required; complex optics Scanning mirror and single discrete detector and filters Uniformity of detector response over the scene; simple optics Short dwell time per pixel; high band width and time response of detector Scanning mirror and multiple discrete detectors and filters Uniformity of detector response over swath; simple optics High band width and time response of detector Scanning mirror and discrete detectors and dispersing element Uniformity of detector response over the scene or swath; simple optics; more and narrower bands possible Many detectors per line required; complex optics; high time response of detector Hyperspectral area array Uniform detector response in along-track direction; no mechanical scanner; somewhat long integration time; more and narrower bands possible

Examples for Sensor Types Digital Frame Camera Area Array ADAR (Positive Systems, Inc.), Leica Geosystems Emerge Digital Sensor System, Vexcel UltraCam Large Format Camera, Z/1 Digital Modular Camera Whiskbroom Landsat MSS, TM, and ETM+ NOAA GOES NOAA AVHRR NASA and ORBIMAGE, Incl. SeaWiFS Daedalus, Inc. AMS NASA ATLAS Pushbroom SPOT HRV, HRVIR, Vegetation, and HRS Indian Remote Sensing System (IRS) LISS III and LISS IV NASA EOS Terra ASTER and MISR DigitalGlobe, Inc. QuickBird Space Imaging, Inc. IKONOS ImageSat International, Inc. EROS A 1 ORBIMAGE, Inc. OrbView-3 and OrbView-5 GeoEye-1 Linear and Area Arrays NASA JPL AVIRIS ITRES Research, Ltd. CASI NASA EO-1, ALI, Hyperion, and LAC NASA EOS Terra MODIS

Two Key Types of Satellite Orbits Geostationary Sun-synchronous

Geostationary Satellites Equatorial orbit Orbit circular with zero degrees inclination Orbital height: 36,000 km Orbital period: 24 hours (Earth’s rotation time) Continuously observe one side of the Earth Viewed from Earth, satellite appears stationary (i.e., hovering over the same position) Common uses: communications and weather forecasting Examples: NOAA’s geo-stationary operational environmental satellites (GOES), METEOSAT, INSAT, GMS Geostationary orbit = special case of geosynchronous orbit

Geostationary Satellites

Geostationary Satellites 180 °E 2 0°E Useful GOES coverage Communication range GOES West East 140 °W 100 6 0°W

Sun-Synchronous Satellites Near-polar-orbit Orbit slightly tilted with a steep inclination angle of about 98º Orbital height: about 600 to 800 km Orbital period: about 100 min Pass over a point on earth’s surface at the same time each day Viewed from satellite, Earth appears to be struck by Sun’s radiation at the same angle Common uses: environmental monitoring and assessment Examples: NOAA's polar-orbiting environmental satellites (POES), Landsat, SeaWiFS, IKONOS Polar orbit: passes over north and south poles during each orbit Satellites can scan the entire Earth’s surface (like pealing an orange around and around, one strip at a time) Must move quickly to avoid being pulled in by Earth’s gravitational field

Sun-Synchronous Satellites Example: Landsat 99 ° Landsat at 12:30 p.m. local time Equatorial plane and direction of Earth rotation 9:42 a.m. S N Left: Inclination of the Landsat orbit to maintain a sun-synchronous orbit Right: From one orbit to the next, the position directly below the satellite moved 2,875 km at the equator as Earth rotated beneath it; the next day, 14 orbits later, it was approximately back to its original location, with orbit 15 displaced westward from orbit 1 by 159 km

Sun-Synchronous Satellites Example: Landsat

Sun-Synchronous Satellites Example: Landsat 1-3 Sun-synchronous, circular orbit Nominal altitude: 919 km Orbital inclination: 99º (nearly polar; crosses equator at 9º) 1 orbit/103 min. → 14 orbits/day Position below spacecraft moves: → 2,875 km/orbit → 40,250 km/day Orbit 15 is displaced from orbit 1 at equator by 159 km → 18 days later, orbit 252 falls directly over orbit 1 → ~ 26 km of overlap between successive orbits Path & Row World Reference System (WRS) → 57,784 scenes each 185 km wide and 170km long