Chapter 5 Chapter 5 Multispectral, thermal and Multispectral, thermal and hyperspectral scanning hyperspectral scanning Introduction to Remote Sensing Instructor: Dr. Cheng -Chien Liu Department of Earth Sciences National Cheng-Kung University Last updated: 7 May 2003
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Chapter 5 Multispectral, thermal and hyperspectral scanning Introduction to Remote Sensing Instructor: Dr. Cheng-Chien LiuCheng-Chien Liu Department of.
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Chapter 5Chapter 5
Multispectral, thermal and Multispectral, thermal and hyperspectral scanninghyperspectral scanning
Introduction to Remote SensingInstructor: Dr. Cheng-Chien Liu
Department of Earth Sciences
National Cheng-Kung University
Last updated: 7 May 2003
5.15.1 Introduction Introduction
MSS (multispectral scanning) vs. MCS MSS (multispectral scanning) vs. MCS (Multiband camera system)(Multiband camera system)• Fig 2.42, 2.43 (MCS)
• AdvantagesSpectral bands: 0.3~1.4 m with narrow band widthCollection: same optical system for all bands.Calibration: electronically rather than photochemically.Storage and transmission
Across-track (whiskbroom) scanner:Across-track (whiskbroom) scanner:• Fig 5.1: operation of a five-channels sensor flight line• Using a rotating or oscillating mirror (Fig 5.1b)• Contiguous strips 2D image• Dichroic grating two forms of energy
ThermalNonthermal prism UV, Vis and near-IR
• Detectors spectral sensitivity• Signal amplified recorded A-to-D View-in-
Successful interpretationsSuccessful interpretations• Rock type, structure• Locating geologic faults• Mapping soil type & moisture• Locating irrigation canal leaks.• Volcanoes.• Evapo-transpiration from vegetation.• Locating cold water springs.• Locating hot water springs & geysers.• Thermal plumes in lakes and rivers.• Natural circulation patterns in water bodies.• Forest fires.• Locating subsurface fires in landfills or coal refuse piles
Most application Most application qualitativequalitative
Some application Some application quantitative quantitative Considerations of the time for acquiring thermal Considerations of the time for acquiring thermal
datadata• Fig 5.15: generalized diurnal radiant T variations.
5.7 Geometric characteristics of 5.7 Geometric characteristics of across-track scanner imageryacross-track scanner imagery
Along-track scanner Along-track scanner no mirror, fixed no mirror, fixed geometric relationshipgeometric relationship
Across-track scanner Across-track scanner systematic and systematic and random geometric variationsrandom geometric variations• Spatial resolution and ground coverage
Table 5.4W= 2H΄tan
5.7 Geometric characteristics of 5.7 Geometric characteristics of across-track scanner imagery (cont.)across-track scanner imagery (cont.)
• Fig 5.33: Effect of nonsynchronized image recording rate and V/H΄ ratio
• Fig 5.34: distortions induced by aircraft attitude deviations
• Fig 5.35: effect of roll compensation
5.8 Radiometric calibration of 5.8 Radiometric calibration of thermal scannersthermal scanners
Thermal scanner image Thermal scanner image lack of lack of geometric integrity geometric integrity • Take photo simultaneously
• Night time use daytime photo (even old photos will do)
5.8 Radiometric calibration of 5.8 Radiometric calibration of thermal scanners (cont.)thermal scanners (cont.)
Two methods of radiometric calibrationTwo methods of radiometric calibration• Internal blackbody source referencing
Two controlled sources: cold & hotView the sources during every scan lineFig 5.36: configurationA typical mission: height 600m 0.30C but atmospheric condition can
be 20C
• Air-to-ground correlation:Account for atmospheric effectsTheoretical approachEmpirical approach the general approach
Fig 5.37 a sample of calibration curve Fig 5.38 a thermal radiometer used for air-to-ground correlation measurements
5.9 Temperature mapping with 5.9 Temperature mapping with thermal scanner datathermal scanner data
Many applications Many applications MapMap Two proceduresTwo procedures
• Image-basedCrude form: qualitative depiction low geometric and radiometric
integritySuffice for many applicationTonal levels densitometric analysis rectilinerarized imagery.
• Numerically basedN=A+BM=A+BT4
N: DN A, B : to be determined : emissivity T: kinetic temperature
Two unknown (A, B) two equations (data)
5.10 FLIR systems5.10 FLIR systems
Forward-looking infrared (FLIR) Forward-looking infrared (FLIR) system system oblique views of the terrain oblique views of the terrain ahead of an aircraftahead of an aircraft• Fig 5.39
• Point forward sweep across the scene of interest
Fig 5.43: selected laboratory spectra of Fig 5.43: selected laboratory spectra of green leavesgreen leaves• Main components: chlorophyll and water• Shape + peak+valley species
Fig 5.44: same as Fig 5.43 but single speciesFig 5.44: same as Fig 5.43 but single species• Main components: lignin & holocellulose• Difference green or dry holocellulose