Remote sensing a a

1. Remote sensinga a Geology 175

2. What is remote sensing? DDefinition:  -         Remote sensing is a wooly term: broadly it describes the collection and interpretation of information about a target without being in physical contact with it. It is usually implicit that the detecting and measuring medium is electromagnetic energy. This definition excludes endeavors such as seismography, magnetic, gravity, and electric surveying, which tend to come under the label of geophysical surveying. Remote sensing is not a scientific discipline but rather a tool whose range in applications is limited only by our imagination (Oppenheimer, 1996).

3. - Definition Remote sensing is the practice of deriving information about the earth’s land and water surfaces using images acquired from an overhead perspective, using electromagnetic radiation in one or more regions of the electromagnetic spectrum, reflected or emitted from the earth’s surface (Campbell, 1996).

4. Key attributes • Remotely sensed data are acquired from a great distance. • Satellite data allow many kinds of ongoing studies. • Remote sensing is safe. • Remote sensing offers very significant cost benefit analysis • Sensors can be tuned to many different wavelengths of the electromagnetic spectrum.

5. Some examples of the applications of using remote sensing: Mapping the rocks in a region (usually applicable in arid areas without much vegetative cover) • This satellite thematic mapper (TM) image of the Orocopia Mountains was created by Bob Crippen and Ron Blom at JPL. It serves as a fantastic tool for investigating rock relationships and serves as the regional base map. In the portion of this image that is outlined, note the distinct difference in colors (rock types) across the box.

6. Some examples of the applications of using remote sensing • Mapping structural lineaments

7. Some examples of the applications of using remote sensing • Bathymetry • Multispectral imagery can be used to map water depths in certain circumstances. Visible wavebands TM1 (blue), TM2 (green) and TM3 (red) penetrate water to different amounts, the shorter the wavelength the greater the penetration. Red light can penetrate up to 10m and blue light as much as 30m.

8. Some examples of the applications of using remote sensing: • Imaging buried structures The Landsat simulated true color mosaic (left) shows the Selima Sand Sheet covering all but rocky areas of the Sahara Desert in Sudan. On the right, a 50-kilometer-wide strip of Shuttle Imaging Radar, SIR-A, is placed over the Landsat mosaic to reveal old stream channels and geologic structures like these. Structures that are otherwise invisible under the surface sands are potential sources of water, placer minerals, ancient artifacts, and information on changes of climate in arid areas (courtesy of USGS Image Processing Facility, Flagstaff).

9. Some examples of the applications of using remote sensing: • Earthquake prediction The surface displacement associated with the June 1992magnitude 7.3 earthquake

10. Some examples of the applications of using remote sensing: • Determination of the surface composition of terrestrial planets The surface of Europa is broken up into large plates and covered with extensive fractures. The plates in many regions appear to have shifted and rotated, and can be fit back together like pieces in a puzzle. The false-color image to the left shows Minos Linea. The long red bands are 10 to 20 km wide and have lighter lines running through the centers.

11. Some examples of the applications of using remote sensing: • Volcanism in terrestrial planets • 1. Volcanic plume (March 4, 1999)taken by Voyager spacecraft • 2. Volcanic plume (July 3, 1999)taken by Galileo spacecraft

12. Some examples of the applications of using remote sensing: • MOUNT ETNA, a volcanic peak in Sicily, subsided as magma drained away below it. An interferogram produced by two radar scans made 13 months apart by the ERS-1 satellite displays four cycles of interference fringes, indicating that the top of the mountain settled by about 11 centimeters during this interval.

13. Electromagnetic spectrum • Electromagnetic energy refers to all energy that moves with the velocity of light in harmonic motion

14. Electromagnetic spectrum • An EM wave has two components, oscillating as sine waves mutually at right angles, one consisting of the electric field, the other the magnetic field.

15. Elecrtromagnetic spectrum

16. Electromagnetic energy Sources of electromagnetic radiation: 1. Sun (stars) 2. Matter with a temperature above absolute zero 3. Artificial transmitters (radio, radar)

17. Electromagnetic energy • The higher the frequency, the higher the energy!

18. Electromagnetic energy Interaction with materials

19. Electromagnetic energy Interaction with materials Atmospheric windows

20. Broad classification of sensors • Passive - senses the radiation that naturally upwell from the target, whether reflected or backscattered sunlight or thermal radiation • Active systems - illuminate the target with an artificial source of radiation

21. Passive system • Sunlight or thermal radiation • Inappropriate at wavelengths at which insignificant amounts of radiation occur naturally

22. Active system system • Radar • May not be practical at wavelengths where the active source requires considerable power in order to get enough signal returned to the sensor (e.g. camera flash)

23. fig 3.2

24. Raster image data • Consists of discrete picture elements called pixels • Each has an associated position within the image and a brightness value or digital number, DN.

25. Sensor Performance and Resolution • Researchers at the Spectroscopy Lab have measured the spectral reflectance of hundreds of materials in the lab, and have compiled a spectral library. The library is used as a reference for material identification in remote sensing images.

28. For images with more than one spectral band, the various bands are co-registered -therefore information from each spectral channel is available

29. Landsat band 4 Landsat band 5 Landsat band 7 False color image

32. Satellite sensors/missions SEAWIFS: http://seawifs.gsfc.nasa.gov/SEAWIFS.html Landsat 7: http://landsat.gsfc.nasa.gov/ Terra (EOS AM-1): http://terra.nasa.gov/ ASTER: http://asterweb.jpl.nasa.gov/ MODIS: http://modis.gsfc.nasa.gov/ GOES: http://www.goes.noaa.gov/ SPOT: http://www.spot.com Very High Resolution technology Commercial satellites offering up to 1 m spatial resolution are available. See the following sites for information: http://www.digitalglobe.com http://www.orbimage.com http://spaceimage.com

33. Satellite Orbits Polar Inclined geostationary

34. Active sensors (Radar) • Components • Antenna array - devices that control the propagation of an EM wave (wave guide) • Recorder – Records and or displays the signal as an image

36. Side-looking airborne radar • SLAR – an antenna array aimed to the side of sensor platforms so that it forms an image strip of land. • All weather capability • Missions can be scheduled at night • Provides clear, crisp representations of topography with good positional accuracy.

38. Geometry of the radar image • Depression angle • Nadir • Far range • Near range • Mid-range

39. Geometry of the radar image • Slant range – direct distance from the antenna to an object on the ground • Ground range – the map representation of ground distances

40. Geometry of the radar image • Geometric artifacts (Radar layover) • at near range, the top of tall objects are closer to the antenna than its base • Result is the signal from the tall objects are sometimes received ahead of near-range signals

41. Geometry of the radar image • Geometric artifacts (Radar foreshortening) • Incorrect depiction of slope • Occurs in terrain of moderate to high relief

42. Wavelength Table 7.1

43. Radar sensors • JERS • ERS • SIR-C • ENVISAT • AIRSAR

44. Optical remote sensing from satellites • Multispectral vs. hyperspectral remote sensing • Multispectral remote sensing (MRS) can be defined as an imaging system with 2 or more bands but about 12 to 15 bands is the practical maximum. • A "band" is defined as a portion of the spectrum with a given spectral width, such as 10 or 50 nm. • Multispectral systems are non-contiguous in their coverage of the spectrum.

45. Optical remote sensing from satellites • Multispectral vs. hyperspectral remote sensing • Multispectral remote sensing (MRS) can be defined as an imaging system with 2 or more bands but about 12 to 15 bands is the practical maximum. • A "band" is defined as a portion of the spectrum with a given spectral width, such as 10 or 50 nm. • Multispectral systems are non-contiguous in their coverage of the spectrum.

46. Optical remote sensing from satellites • Multispectral vs hyperspectral remote sensing • The bands can be spectrally narrow or wide. • Many satellite systems have traditionally had wide (50 - 200 nm) bands while some aircraft systems have discrete narrow bands (around 10 nm).

47. Optical remote sensing from satellites • Hyperspectral remote sensing • Hyperspectral systems are known for having dozens to hundreds of narrow contiguous bands. • Most are able to collect images starting at about 400 nm which is the edge of the blue visible part of the spectrum

49. Optical remote sensing from satellites • Hyperspectral remote sensing • these systems can measure energy up to 1100 or even 2500 nm. • Why important? Ans: for detecting fine spectral features that can identify specific materials