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Orbits and Sensors Multispectral Sensors

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Presentation on theme: "Orbits and Sensors Multispectral Sensors"— Presentation transcript:

1 Orbits and Sensors Multispectral Sensors

2 Outline for 15 October 2007 Orbits: geostationary, polar
Cross-track scanners (whiskbroom sensor) Pushbroom sensors Field of View (“swath width”) Pixel size Multispectral sensors: Landsat

3 Satellite Orbits Orbital parameters can be tuned to produce particular, useful orbits Geostationary Sun synchronous (Polar, Low Earth Orbit) Geosynchronous Altimetric

4 Geostationary Orbits Geo orbit is stationary with respect to a location on the earth Circular orbit around the equator (orbital inclination = zero) Placed in high orbit (35,800 km) to match the angular velocity of Earth

5 Uses of Geostationary Orbits
Weather satellites (GOES, METEOSAT) Constant monitoring Communication satellites Constant contact w/ground stations Limited spatial coverage each satellite can only cover about 25-30% of the earth’s surface coverage extends only to the mid-latitudes, no more than about 55o

6 Sun-synchronous (Polar) Orbit
“Low Earth Orbit” (LEO) are typically about 700 km altitude Precession of the satellite orbit is the same as the angular speed of rotation of the sun Satellite crosses the equator at the same time each day “Polar orbit” is very common Orbital inclination is “retrograde” (typically ~98o) Near circular orbits have period of about minutes

7 Animation of GEO and LEO orbits


9 Polar Orbiting Satellite Tracks

10 Uses of Sun-Synchronous Orbits
Equatorial crossing time depends on nature of application (low sun angle vs. high sun angle needs) Earth monitoring -- global coverage Good spatial resolution

11 Terra satellite overpasses for today over North America

12 Getting the Data to the Ground
On-board recording and pre-processing Direct telemetry to ground stations receive data transmissions from satellites transmit commands to satellites (pointing, turning maneuvers, software updating Indirect transmission through Tracking and Data Relay Satellites (TDRS)

13 Imaging Systems Cross-track scanning systems
“whiskbroom” Along-track (non-scanning) system “pushbroom”

14 Cross-track Scanner Single detector or a linear array of detectors
“Back and forth” motion of the scanner creates the orbital “swath” Image is built up by movement of satellite along its orbital track Produces a wide field-of-view Pixel resolution varies with scan angle

15 Field of View (FOV) FOV is the swath width of the instrument
It is the width of an orbital swath Depends on the across track scan angle of the sensor (for whiskbroom) or the width of the linear detector array (for a pushbroom sensor)

16 Along-track scanner (Pushbroom)
Linear array of detectors (aligned cross-track) radiance passes through a lens and onto a line of detectors Image is built up by movement of the satellite along its orbital track (no scanning mirror) Multiple linear arrays are used for multi-spectral remote sensing dispersion element splits light into different wavelengths and onto individual detectors

17 Dwell Time The amount of time a scanner has to collect photons from a ground resolution cell Depends on: satellite speed width of scan line time per scan line time per pixel Whiskbroom scanners have much shorter dwell time than do pushbroom scanners

18 Whiskbroom vs. Pushbroom
Wide swath width Complex mechanical system Simple optical system Shorter dwell time Pixel distortion Narrow swath width Simple mechanical system Complex optical system Longer dwell time No pixel distortion

19 Signal Strength Need enough photons incident on the detector to record a strong signal Signal strength depends on Energy flux from the surface Altitude of the sensor Location of the spectral bands (e.g. visible, NIR, thermal, etc.) Spectral bandwidth of the detector IFOV Dwell time

20 Calculating the Field of View (FOV)
FOV = 2 H tan(scan angle) H = satellite altitude Example: SeaWIFS satellite altitude = 705 km Scan angle = 58.3o FOV = 1410 x tan(58.3o) = 2282 km q H FOV

21 Cross-track pixel size
x = H tan(q + b/2) x2 = H tan(q - b/2) x1 = x - x2 Pc = H tan(q + b/2) - H tan(q - b/2) q H H/cosq = Hsecq x1 x2 x

22 History of the Landsat series
Currently, Landsat 5 and Landsat 7 (ETM+) are in orbit

23 Landsat MSS 1972-present


25 Landsat orbits


27 Landsat MSS Bands and their Uses
Band 4 (Green: mm) water features (large penetration depths) sensitivity to turbidity (suspended sediments) sensitivity to atmospheric haze (lack of tonal contrast) Band 5 (Red: mm) chlorophyll absorption region good contrast between vegetated and non-veg. areas haze penetration better than Band 4 Band 6 (NIR1: mm) and Band 7 (NIR2: mm) similar for most surface features good contrast between land and water (water is strong absorber in near IR) both bands excellent haze penetration Band 7 good for discrimination of snow and ice

28 Landsat MSS Images of Mount St. Helens
September 15, 1973 May 22, 1983 August 31, 1988

29 Landsat Thematic TM present

30 Landsat Thematic Mapper Bands and their Uses
Band 1 (Blue: mm) good water penetration differentiating soil and rock surfaces from vegsmoke plumes most sensitive to atmospheric haze Band 2 (Green: mm) water turbidity differences sediment and pollution plumes discrimination of broad classes of vegetation Band 3 (Red: mm) strong chlorophyll absorption (veg. vs. soil) urban vs. rural areas

31 Landsat Thematic Mapper Bands and their Uses
Band 4 (NIR1: mm) different vegetation varieties and conditions dry vs. moist soil coastal wetland, swamps, flooded areas Band 5 (NIR2: mm) leaf-tissue water content soil moisture snow vs cloud discrimination Band 6 (Thermal: mm) heat mapping applications (coarse resolution) radiant surface temperature range: -100oC to +150oC Band 7 (NIR3: mm) absorption band by hydrous minerals (clay, mica) lithologic mapping (clay zones)

32 Landsat 7 Enhanced Thematic Mapper (ETM+) 1999-present
15m panchromatic band on-board calibration


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