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Remote Sensing Theory & Background II

Remote Sensing Theory & Background II . GEOG370 Instructor: Yang Shao. What is remote sensing Satellite remote sensing Spatial: Area visible to the sensor Spectral: Ability of a sensor to define fine wavelength intervals

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Remote Sensing Theory & Background II

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  1. Remote Sensing Theory & Background II GEOG370 Instructor: Yang Shao

  2. What is remote sensing • Satellite remote sensing • Spatial: Area visible to the sensor • Spectral: Ability of a sensor to define fine wavelength intervals • Radiometric: Ability to discriminate very slight differences in energy • Temporal: Amount of time before site revisited

  3. Digital Images 10 10 25 10 30 30 sensor 30 30 5 • Space is covered continuously • with cells. • Each cell has one number • indicating the amount of • energy received from the cell • The cell is called pixel • (picture element) • The size of the pixel is the • spatial resolution

  4. Temporal Resolution Temporal Resolution: The shortest time needed to repeat the ground track

  5. Temporal resolution • National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) revisits the same geographic point two times daily at a 1.1-kilometer resolution. • Landsat Thematic Mapper: 16 days • SPOT: 14 days • Space Imaging's IKONOS revisits the same point every 11 days

  6. Across-track scanning • Scan the Earth in a series of lines • Lines perpendicular to sensor motion • Each line is scanned from one side of the sensor to the other, using a rotating mirror (A). • Internal detectors (B) detect & measure energy for each spectral band, convert to digital data • IFOV or Instantaneous Field of View (C) of the sensor and the altitude of the platform determine the ground resolution cell viewed (D), and thus the spatial resolution. • The angular field of view (E) is the sweep of the mirror, measured in degrees, used to record a scan line, and determines the width of the imaged swath (F). http://ccrs.nrcan.gc.ca/resource/tutor/fundam/chapter2/08_e.php

  7. Along-track scanning • Uses forward motion to record successive scan lines perpendicular to the flight direction • Linear array of detectors (A) used; located at the focal plane of the image (B) formed by lens systems (C) • Separate array for each spectral band • Each individual detector measures the energy for a single ground resolution cell (D) • May be several thousand detectors • Each is a CCD • Energy detected and converted to digital data • “Pushed" along in the flight track direction (i.e. along track). • “Pushbroom scanners” http://ccrs.nrcan.gc.ca/resource/tutor/fundam/chapter2/08_e.php

  8. Civil Remote Sensing Earth Resources Technology Satellite (ERTS-1; renamed Landsat 1) 1st satellite launched for peaceful purposes (1972) Satellite Launched Decom MSS TM Orbit Landsat-1 23 Jul 1972 6 Jan 1978 Yes none 18d/900km Landsat-2 22 Jan 1975 25 Feb 1982 Yes none 18d/900km Landsat-3 5 Mar 1978 31 Mar 1983 Yes none 18d/900km Landsat-4 16 Jul 1982 -- Yes Yes 16d/705km Landsat-5 2 Mar 1984 -- Yes Yes 16d/705km Landsat-6 5 Oct 1993 Launch Failure none ETM 16d/705km Landsat-7 15 Apr 1999 -- none ETM+ 16d/705km MSS: Multispectral Scanner TM: Thematic Mapper Decom: decommissioned

  9. Landsat Swath Width & Field of View Landsat swath 705km Satellite ground track scene Spatial Resolution 175km 185 km Pixel size= (30x30m)

  10. Landsat 7 ETM+ Spectral Bands Spectral resolution: The number of bands and the width of spectrum that each sensor covers

  11. Ikonos Owner: Space Imaging Temporal resolution: 11 days Radiometric resolution: 11-bit Spectral bands spatial resolution Blue (0.45-0.52) 4m Green (0.51-0.60) 4m Red (0.63-0.70) 4m NIR (0.76-0.85) 4m Panchromatic (0.45-0.90) 1m Swath width: 11km Orbit: Sun-synchronous; equatorial crossing time of 10:30am

  12. Analyses of Remotely Sensed Data • Photo-interpretation: extracting information by visual inspection of an image

  13. 3. Visual interpretation of remotely collected photographs is the only way to obtain information. • requires years of experience for accurate interpretation • can not be done so for large areas within short period of time Not many people can tell that missiles were deployed in this U-2 photograph. This was identified by then US top photo interpreter A. C. Lundahl.

  14. Color images • We put the digital numbers into the color guns of computer • so that the level of intensity for the color corresponds • to the size of the number. • If we put the same digital numbers into all three color • guns on a computer, we will get a black and white picture. • We call it an image in remote sensing terminology. • If we put the digital number for red light in red gun, • and the digital numbers for blue light in blue gun, • and the digital numbers for green light in green gun, • we will have a true color image. Otherwise, we call it • a false color image.

  15. True Color Image This is the image from MODIS showing the wide sediment plume of Yangtze River as it runs into the East China Sea. Yangtze River, originating from the Himalayans, is the longest river in China (6380km), the third longest in the world after the Amazon, and the Nile. The world largest dam, the Three Gorges Dam, is now being built in Sichuan province. Due to deforestation in the upper reaches of the river, many fear that the river will become the second Yellow River in China. Color, size, and tone are all helpful to identify the severity and extension of soil erosion

  16. False Color Image Landsat 7 ETM false color image RGB=ETM+ 453 Landsat 7 ETM true color image RGB=ETM+ 321

  17. Vegetation Information Normalized Difference Vegetation Index NDVI: [-1.0, 1.0] Often, the more the leaves of vegetation present, the bigger the Contrast in reflectance in the red and near-infrared spectra.

  18. NDVI from AVHRR Apr 24-May 7 Feb 27-Mar 12 Jul 17-Jul 30 Jun 19-Jul 2 Aug 14-Aug 27 Nov 6- Nov19

  19. Monitoring forest fire Pre-forest fire Post-forest fire Burned area identified from space

  20. Remote Sensing of Snow In the visible spectrum clouds and snow look very similar. Thus, it is difficult to separate them with human eyes. But they are very different in the mid- infrared.

  21. Mineral Distribution Map derived from AVIRIS a mineral distribution map a mineral distribution map AVIRIS

  22. NDVI and Precipitation Relationships A: 12 Apr-2 May 1982 B: 5 to 25 Jul 1982 C: 22 Sep to 17 Oct 1982 D: 10 Dec 1982-9Jan 1983 Expansion and contraction of the Sahara

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