Presentation on theme: "Radiometric and Geometric Errors"— Presentation transcript:
1 Radiometric and Geometric Errors Mirza Muhammad WaqarContact:EXT:2257RG610Course: Introduction to RS & DIP
2 Outlines Digital Image Advantages of Digital Image Constraints of Remote Sensing SystemImage PreprocessingGeometric DistortionsRadiometric Distortions
3 Digital Image A metric Cell Spatial informationSpectral informationSatellite data mostly available in grid file formatUsed forSpatial Analysis (Quantitative Analysis)Spectral Analysis (Qualitative Analysis)For information extraction form satellite imagery, we normally perform both, qualitative as well as quantitative analysis.
4 Advantages of Digital Image Flexible structureAll mathematical and statistical operations can be appliedAdvance image processing packages are available to process digital imagery.
5 Constraints of Remote Sensing Systems Remote sensing systems are not yet perfect and contains four types of resolution constraints:SpatialSpectralTemporalRadiometricThese constraints (plus complexity of land and water surfaces) cause errors in data/image acquisition process.This leads to degradation of quality of remote sensing data/image.Before remote sensing data is analyzed, data/image needs to be preprocessed to restore image quality.Image restoration involves correction of distortion, degradation, and noise introduced during the imaging process.
6 Image PreprocessingDuring image processing, anomalies are removed which can create problem during information extraction.Spatial Anomalies (Geometric Distortions)Spectral Anomalies (Radiometric Distortions)
7 Geometric Distortions There are two types of geometric distortions exists in satellite dataSystematic ErrorsNon-Systematic Errors
8 Systematic ErrorsThese errors are system dependent also called platform based errors.If the quantity of error is knowThese errors can be removedMostly found in mechanical sensorsFor example, velocity of Landsat scanners’ motor varies and its variation is known.A mathematical model can be develop to remove such distortions.
10 Scan Skew DistortionDuring the time the scan mirror completes one active scan, the satellite moves along the ground track.Therefore, scanning is not at right angles to the satellite velocity vector (ground track) but is slightly skewed, which produce along track geometric distortion, if not corrected
11 Earth Rotation Effect26-28 seconds required to capture a Landsat image.In Landsat TM/ETM+, up till 16 scan line, distortion is gradual, however after 16 lines, distortion is greaterSatellites having small swath width have less earth rotation effect.
14 Platform VelocityVariation of pixel size in terms of information content.1:100 => Less information => Large pixel size1:10 => More information => Small pixel sizeWhen information is increasing, pixel size is decreasing.
15 Platform Velocity Image Scale Distortions Size of the pixel is changingFor satellite, we have equal sampling rateDue to Scale distortions, Dwell Time is changingInformation content variesInformation content is the indicator of scale
16 Mirror Scan VelocityMirror scan velocity of landsat scanner is not constantIt is slower first then it increases
17 Perspective Distortions As all remote sensing satellites exit at high altitude.Earth curvature effect become very prominent which cause perspective distortionsThis effect can be removed by rectification (we will study in next lecture).
20 Non-Systematic ErrorAll the terminologies make for non-systematic distortions was developed for aerial platforms.Two types of non-systematic distortions:Developed due to AltitudeDeveloped due to Attitude
21 Altitude Distortions Due to altitude variation, FOV and IFOV changes. Causing scale distortions.
24 Radiometric ErrorInternal cause: When individual detectors do not function properly or are improperly calibrated.External cause: Atmosphere (between the terrain and the sensor) can contribute to noise (i.e., atmospheric attenuation) such that energy recorded does not resemble that reflected/emitted by the terrain.
25 Radiometric ErrorInternal Error Correction (Correction for Sensor System Detector Error) Element(s) ij:may go bad at the beginning of the scan line (line-start problem)may go out of calibration or adjustment (line stripping or banding), ormay drop out (line drop out) completely.Detect: Take average of brightness value (BV) of surrounding pixels and compare to BVij.Correct: Assign average BV if BVij is beyond a given threshold.Or, correct from overlapped images.Improves fidelity of brightness value magnitude. Improves visual interpretability.
26 Radiometric Correction External Error Correction (Correction for Environmental Attenuation Error)Two sources of environmental attenuation:Atmospheric attenuationTopographic attenuationAtmospheric attenuation (caused by scattering and atmosphere)Not a problem for most land-cover-related studies because signals from soil, water, vegetation, and urban area may be strong and distinguishable.Problematic for biophysical information from water bodies (e.g., chlorophyll a, suspended sediment, or temperature) or vegetated surfaces (e.g., biomass, NPP, % canopy closure) because there is only subtle difference in reflectance.Error correction:data is calibrated with in situ measurements, and/or,data is corrected with a model atmosphere.Error minimized using multiple "looks" at the same object from different vantage points or using multiple bands.
27 Radiometric Correction Topographic attenuationSlope and aspect effects include shadowing of areas of interest.Goal of slope-aspect correction: To remove topographically induced illumination variation (so that two objects having same reflectance show same BV even though they may have different slope and aspect).Forest stand classification is improved when slope-aspect errors are corrected.Correction is based on illumination (proportion of direct solar radiation hitting a pixel). Digital Elevation Model (DEM) required. DEM and remote sensing data must be geometrically registered and resampled to same spatial resolution.Amount of illumination depends on relative orientation of pixels toward the sun.