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Remote Sensing

Remote Sensing. Readings: 27-20 and lecture notes Figures to Examine: 27-20 to 27-23. Examine the Image from IKONOS, 27-23 and compare it with the others. Introduction.

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Remote Sensing

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  1. Remote Sensing

  2. Readings: 27-20 and lecture notes • Figures to Examine: 27-20 to 27-23. • Examine the Image from IKONOS, 27-23 and compare it with the others.

  3. Introduction • Definition: Remote Sensing is the science of obtaining information about an area, object, or phenomenon through the analysis of data acquired by a device which is not in contact with the object, area, or phenomenon under investigation. • Energy, mainly from the sun, propagates through the atmosphere, reflected or re-emitted from the objects, and recorded by “sensors”.

  4. The Electromagnetic Spectrum • Visible wave lengths are very limited , 0.4 to 0.7 mm, Near IR 0.7 to 1.3 mm, mid IR 1.3 to 3 mm. They both could be recorded on films. • Thermal IR is mainly emitted from an object, needs thermal scanning. • Microwaves are very long waves 1mm to 1m • Most common sensing systems operate in one or several of the visible, IR, or microwave portions of the spectrum. • Energy emitted by the sun is within the visible portion, earth’s emitted energy is within the thermal IR portion.

  5. Spectral Reflectance • The ratio between the reflected energy and the incident energy at a certain wave length. • A certain object will have different spectral reflectance at different wave lengths • Different objects will have different spectral Reflectance at the same wave length • Examples: Deciduous and coniferous trees, vegetation, soil and water. • Why do we see “green”. • What is spectral signature?

  6. Dry soil gray brown Vegetation green Water clear Reflectance % Wavelength µm

  7. Normal Color photo Notice the difference in color between natural vegetation and artificial turf Infrared color photo

  8. Normal B/W photo 0.4 to 0.7 µm Deciduous (needle) and coiffeurs trees (broad leaves) reflect the same Deciduous (needle) trees reflect more, brighter B/W Infrared photo 0.7 to 0.9 µm

  9. Thermal and Multispectral scanners • Thermal scanners will detect the emitted energy in the thermal IR band. • Multispectral scanners will detect the reflected energy in the visible, IR and microwave bands, includes a number of detectors corresponding to the number of bands detected. • Thermal IR multispectral scanners. • Imaging Spectrometry: acquisition in many, very narrow, contiguous spectral bands from visible to mid IR

  10. Earth Resource Satellites • There are several types of satellites above you: communications, remote sensing, GPS, radio and TV, .. • US “LnadSat”: • Ground coverage 185 km x 185 km. Equals to 1600 photos at 1: 20,000 with no overlap. • Sensors: MSS, TM, best resolution: 30 m in black and white, LandSat 7: 15 m • French “Spot”: • Ground coverage is 60 x 60 km • Sensors: High Resolution Visible (HRV). Operates within a limited band width: 0.51 to 0.89. Resolution of 10 m in B/W, spot 5: 2.5m

  11. Spot has a better spatial resolution and less spectral resolution than LandSat • Spot imaging system could be oriented to survey a certain area at a certain time and to produce stereo pairs. • Other available systems, some with higher accuracy Such as IKONOS, figure 27-23, 1 m resolution, and Spin-2 2m resolution. • Quick Bird: Resolution up to 60 cm is commercially available today.

  12. Spot twin system

  13. SPOT 10m resolution B/W Image LA, California

  14. DEM generated from Spot imagery

  15. Quick Bird 60 cm Image of Buckingham Palace- England

  16. Quick Bird 60cm image

  17. 1m Ikonos Image in Jamaica

  18. Santiago 1m Ikonos Image

  19. Washington D.C 5M IRS Image

  20. 2 m resolution satellite image of Giza-Egypt, courtesy of Spin-2

  21. 60 cm image of a runway in Egypt

  22. Daytime thermal image Quantico, VA

  23. Nighttime thermal IMAGE HEAT LOSS

  24. Site of the ancient city of Spina, Italy

  25. Recently plowed fields that reveals the foundation of a 320-m long Roman village in northern France.

  26. Digital Image Processing • What is a digital Image • Basic Operations: • Image rectification and restoration • Image enhancement • Image classification • Data merging

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