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Remote Sensing Scanners PowerPoint Presentation
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Remote Sensing Scanners

Remote Sensing Scanners

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Remote Sensing Scanners

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    1. Remote Sensing Scanners Introduction to Remote Sensing Dr. Stuart Murchison

    2. Multispectral Scanners Advantages over multiband camera systems: Photographic systems: 0.3-0.9 ?m spectral range of sensing, wider bands Multispectral scanners: 0.3-14 ?m, more (and narrower) bands MSS use the same optical system to collect data in all spectral bands simultaneously Airborne or space platforms

    3. Across-Track Scanners Also known as WHISKBROOM Scanners Scans Right to Left one pixel at a time Using a rotating mirror

    4. Across-Track Scanners The IFOV (C) of the sensor and the altitude of the platform determine the ground resolution cell viewed (or ground Sample Distance) (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). Airborne scanners typically sweep large angles (between 90 and 120), while satellites, because of their higher altitude need only to sweep fairly small angles (10-20) to cover a broad region. Because the distance from the sensor to the target increases towards the edges of the swath, the ground resolution cells also become larger and introduce geometric distortions to the images. Also, the length of time the IFOV "sees" a ground resolution cell as the rotating mirror scans (called the dwell time), is generally quite short and influences the design of the spatial, spectral, and radiometric resolution of the sensor.

    5. Across-Track Scanners If you know how far away it is, and the angle that it subtends, you can calculate the GSD. For example, if something is 100 meters away and it fills 10 milliradians (mrad), it's 100 * 0.01 = 1 meter across. (A milliradian is 1/1000 of a radian, and a radian is about 57 degrees.) The IFOV for airborne MS scanners typically ranges from an angle of 0.5 to 5 mrad . The smaller the IFOV, the higher the spatial resolution, or the smaller the details that can be recorded.

    6. Across-Track Scanners

    7. Across-Track Scanners However, a larger IFOV provides a larger signal because energy is collected from a larger ground area Higher radiometric resolution Because the signal is much greater than the systems background electronic noise Signal-to-noise-ratio = compares the level of a desired signal (such as music) to the level of background noise. The higher the ratio, the less obtrusive the background noise is. (in our case brightness levels)

    8. Across-Track Scanners The signal-to-noise-ratio can be improved by detecting a wider range of wavelengths thereby increasing the total energy collected. Trade-offs between spatial, spectral, radiometric res Small IFOV means high spatial detail recorded, since an object can only be resolved independent of its background when the size of the object is equal to or greater than the size of the ground resolution element.

    9. Across-Track Scanners Larger IFOV also means: Signal greater than background noise Higher signal-to-noise ratio Longer dwell time If the signal-to-noise ratio is increased by broadening the wavelength band over which a detector operates, spectral resolution is sacrificed.

    10. Across-Track Scanners The incoming energy is separated into several spectral components that are independently sensed. Dichroic grating (to separate thermal and non-thermal energy forms)

    11. Along-track Scanners Also known as PUSHBROOM Scanners Sense a swath with an linear array of CCDs Because pushbroom scanners have no mechanical parts, their mechanical reliability can be very high.

    12. Along-track Scanners signal-to-noise can be greater because of less Dwell Time over the IFOV. Advantages: Smaller, lighter, no moving parts and consume less power Longer life expectancy Most widely used scanners for earth Remote Sensing

    13. Spin Scanners

    14. Conical Scanners

    15. Hyperspectral Scanners Detects tens or hundreds of narrow contiguous spectral bands simultaneously. Imaging spectroscopy has been used in the laboratory by physicists and chemists for over 100 years for identification of materials and their composition. Spectroscopy can be used to detect individual absorption features due to specific chemical bonds in a solid, liquid, or gas. With advancing technology, imaging spectroscopy has begun to focus on identifying and mapping Earth surface features. The concept of hyperspectral remote sensing began in the mid-80's and to this point has been used most widely by geologists for the mineral mapping.

    16. Hyperspectral Scanners Actual detection of materials is dependent on the spectral coverage, spectral resolution, and signal-to-noise of the spectrometer, the abundance of the material and the strength of absorption features for that material in the wavelength region measured. Hyperspectral and spectroscopy in a single system which remote sensing imaging includes large data sets and requires new processing methods.

    17. Hyperspectral Scanners Data sets are generally composed of about 100 to 200 spectral bands of relatively narrow bandwidths (5-10 nm), whereas, multispectral data sets are usually composed of about 5 to 10 bands of relatively large bandwidths (70-400 nm) Hyperspectral imagery is typically collected (and represented) as a data cube with spatial information collected in the X-Y plane, and spectral information represented in the Z direction

    18. Hyperspectral Scanners There are many applications which can take advantage of hyperspectral remote sensing: Atmosphere: water vapor, cloud properties, aerosols Ecology: chlorophyll, leaf water, cellulose, pigments, lignin Geology: mineral and soil types Coastal Waters: chlorophyll, phytoplankton, dissolved organic materials, suspended sediments Snow/Ice: snow cover fraction, grain size, melting Biomass Burning: subpixel temperatures, smoke Commercial: mineral exploration, agriculture and forest production

    19. Hyperspectral Scanners

    20. Hyperspectral Scanners

    21. Hyperspectral Scanners

    22. Hyperspectral Scanners