1. Multispectral
Remote Sensing

2. 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

3. 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

4. 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

5. 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)

6. 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)

7. 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)

8. 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

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

10. 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

11. 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)

12. 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)

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

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

21. 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

22. 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.

23. 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

24. 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

25. 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

26. 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)

27. 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

28. 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

29. Many Types of RS Systems

30. Many Types of RS Systems

31. 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

32. 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

33. Two Key Types of Satellite Orbits
Geostationary
Sun-synchronous

34. 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

35. Geostationary Satellites

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

37. 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

38. 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

39. Sun-Synchronous Satellites
Example: Landsat

40. 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