746A27 Remote Sensing and GIS. Multi spectral, thermal and hyper spectral sensing and usage

Transcription

1 746A27 Remote Sensing and GIS Lecture 3 Multi spectral, thermal and hyper spectral sensing and usage Chandan Roy Guest Lecturer Department of Computer and Information Science Linköping University

2 Multi spectral Remote Sensing Many electronic remote sensors acquire data using scanning systems, which employ a sensor with a narrow field of view that sweeps over the terrain to build up and produce a two-dimensional image of the surface. Scanning systems can be used on both aircraft and satellite platforms and have essentially the same operating principles. A scanning system used to collect data over a variety of different wavelength ranges is called a multispectral scanner (MSS), and is the most commonly used scanning system.

3 There are two main modes or methods of scanning employed to acquire multispectral image data across-track scanning, and along-track scanning. Across-track scanning Across-track scanners scan the Earth in a series of lines. The lines are oriented perpendicular to the direction of motion of the sensor platform (i.e. across the swath). Each line is scanned from one side of the sensor to the other, using a rotating mirror (A).

4 The incoming reflected or emitted radiation is separated into several spectral components that are detected independently. The UV, visible, near-infrared, and thermal radiation are dispersed into their constituent wavelengths. A bank of internal detectors (B), each sensitive to a specific range of wavelengths, detects and measures the energy for each spectral band and then, as an electrical signal, they are converted to digital data and recorded for subsequent computer processing.

5 The IFOV (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). Along-track scanning Along-track scanners also use the forward motion of the platform to record successive scan lines and build up a two-dimensional image, perpendicular to the flight direction. However, instead of a scanning mirror, they use a linear array of detectors (A) located at the focal plane of the image (B) formed by lens systems (C), which are "pushed" along in the flight track direction.

6 These systems are also referred to as pushbroom scanners, as the motion of the detector array is analogous to the bristles of a broom being pushed along a floor.

7 Each individual detector measures the energy for a single ground resolution cell (D) and thus the size and IFOV of the detectors determines the spatial resolution of the system. A separate linear array is required to measure each spectral band or channel. For each scan line, the energy detected by each detector of each linear array is sampled electronically and digitally recorded.

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13 Multispectral imaging using discrete detectors and scanning mirrors Landsat MSS Landsat TM NOAA AVHRR Aircraft Multispectral scanner Multispectral scanning using linear arrays SPOT High-resolution Visible (HRV) sensor Multispectral spectrometry using linear and area arrays Compact Airborne Spectrographic Imager (CASI) Multispectral Electro-optical Imaging System (MEIS)

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15 Major components of Landsat MSS

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17 Application of Landsat MSS image Channel (µm) Applications Landsat 1,2,3 Landsat 4,5 MSS 4 MSS (green) Vegetation vigor assessment, useful for the measurement of sediment concentrations in water MSS 5 MSS (red) Strongly absorbed by chlorophyll; an important band for vegetation discrimination MSS 6 MSS (near infrared) Very strong vegetation reflectance; useful for determining biomass MSS 7 MSS (near infrared) Useful for determining biomass. High land-water contrast so good for determining water bodies and coast lines

18 Application of Landsat TM image Channel (µm) Applications TM (blue) TM (green) TM (red) soil/vegetation discrimination; bathymetry/coastal mapping; cultural/urban feature identification green vegetation mapping (measures reflectance peak); cultural/urban feature identification vegetated vs. non-vegetated and plant species discrimination (plant chlorophyll absorption); cultural/urban feature identification TM (near IR) TM (short wave IR) TM (thermal IR) identification of plant/vegetation types, health, and biomass content; water body delineation; soil moisture sensitive to moisture in soil and vegetation; discriminating snow and cloud-covered areas vegetation stress and soil moisture discrimination related to thermal radiation; thermal mapping (urban, water) TM (short wave IR) discrimination of mineral and rock types; sensitive to vegetation moisture content

19 Bandwidths of Landsat MSS, TM and SPOT (HRV)

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21 Application of SPOT image Mode/Band (µm) Applications Panchromatic (PLA) (blue-green-red) Multispectral (MLA) Band (green) Water and urban studies Band (red) Water and vegetation studies Band (near infrared) Vegetation and topography

22 SPOT (HRV) satellite

23 SPOT TM

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26 Thermal Sensing Many multispectral (MSS) systems sense radiation in the thermal infrared as well as the visible and reflected infrared portions of the spectrum. However, remote sensing of energy emitted from the Earth's surface in the thermal infrared (3 mm to 15 mm) is different than the sensing of reflected energy. Thermal sensors use photo detectors sensitive to the direct contact of photons on their surface, to detect emitted thermal radiation. The detectors are cooled to temperatures close to absolute zero in order to limit their own thermal emissions. Thermal sensors essentially measure the surface temperature and thermal properties of targets.

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28 Temperature mapping with thermal scanner data Principle application of thermal images are preparation of surface temperature maps. Digital data recorded by a thermal scanner can be processed, analyzed and displayed in a variety of ways. DN recorded by a scanner, can be expressed in the following equation DN = A+ B T 4 Where, A, B = system response parameters determined by the sensor ε = emissivity at the point of measurement T = kinetic temperature at the point of measurement

29 Advanced Very High Resolution Radiometer (AVHRR) image of sea surface temperature

30 Hyperspectral Sensing Hyperspectral sensor are instruments that acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-ir and thermal IR portions of the spectrum. It is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of minerals, terrestrial vegetation, and man-made materials and backgrounds. Hyperspectral remote sensing combines imaging and spectroscopy in a single system which often includes large data sets and require new processing methods. Hyperspectral 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 ( nm).

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

33 AVIRIS hyperspectral data cube Spectral comparison between hyperspectral and broad-band data

34 MSS TM ETM

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