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RADIOMETRIC AND GEOMETRIC ERRORS
Course: Introduction to RS & DIPUCC: 620124
Rao Zahid KhalilContact:
[email protected] +92-21-34650765-79 EXT:2257
Outlines
Digital Image
Advantages of Digital Image
Constraints of Remote Sensing System
Geometric Distortions
Radiometric Distortions
Digital Image
A Cell Spatial information Spectral information
Satellite data mostly available in grid file format
Used for Spatial Analysis Spectral Analysis
For information extraction form satellite imagery,we normally perform both, qualitative as well asquantitative analysis.
Advantages of Digital Image
1. Flexible structure
2. All mathematical and statistical operations canbe applied
3. Advance image processing packages areavailable to process digital imagery.
Remote Sensing Systems
Two major categories of remote sensingsystems Framing System Scanning System
Framing systems instantaneously acquire animage of a large area (or frame) on the terrain. Cameras are common examples of such systems
A scanning system employs detectors with anarrow field of view that is swept across theterrain in a series of parallel scan lines toproduce an image. Generally electro-optic sensors are used in
scanning systems
Electro-optical Sensors
In contrast to photographic cameras that recordradiations reflected from a ground scene directlyonto film, electro-optical sensors use non-filmdetectors.
Electro-optical detectors record the reflectedand/or emitted radiation from a ground scene aselectrical signals, which are converted into theimage DN values.
Terminologies
Flight line – the path ofthe sensor platform(satellite/ aircraft)
Scan line – the line alongwhich the sensor scans theground
Ground resolution cell –the ground segmentsensed at any instant
Pixel – (picture element)the radiometric responseof the ground resolutioncell on the image
IFOV (Instantaneous field ofview) is the cone angle withinwhich the incident energy isfocused on the detector
All energy propagating towardsthe sensor within the IFOVcontributes to the detector’sresponse at any instant
The ground resolution cell withina IFOV have homogeneous (purepixels) or heterogeneouscomposition (mixed pixels)
IFOV and ground resolution cell
D = H’
Where is in radians D is loosely referred to as the
spatial resolution of the system Smaller IFOV >> better spatial
resolution, poorer signal-to-noise ratios
Higher IFOV >> betterradiometric resolution, bettersignal-to-noise ratios, longerdwell time
IFOV and ground resolution cell
Across track (whiskbroom) scanning
The dwell time is generally quite short and
influences the radiometric resolution (in particular)
of the sensor.
Using a rotating mirror, this system scan the terrainalong lines that are perpendicular to the direction ofmotion of the sensor platform
The angular field of view (E) is the sweep of themirror used to record a scan line, and determines thewidth of the image swath (F).
Airborne scanners typically sweep large angles(between 90o and 120o), while satellites, because oftheir higher altitude need only to sweep fairly smallangles (10o to 20o) to cover a broad region
Today many scanners are still based on this principle:
NOAA/AVHRR, Landsat TM, ETM+ etc.
Along track (Pushbroom) scanning
The pushbroom motion allows each detector to see and measure the energy
from each ground resolution cell for a longer period of time (dwell time). This
allows more energy to be detected and improves the radiometric resolution.
Along-track scanners also use the forwardmotion of the platform to record successivescan lines and build up a two dimensionalimage.
They use a linear array of detectors locatedat the focal plane of the image.
Each individual detector measures theenergy for a single ground resolution celland thus the size and IFOV of the detectorsdetermines the spatial resolution of thesystem.
A separate linear array is required tomeasure each spectral band or channel.
Distortion in Imagery
Any kind of errors present in remote sensingimages are known as image distortions.
Any remote sensing images acquired fromeither spaceborne or airborne platforms aresusceptible to a variety of distortions.
These distortions occur due to data recordingprocedure, shape and rotation of the Earth andenvironmental conditions prevailing at the timeof data acquisition.
Distortion in Imagery
Distortions occurring in remote sensing imagescan be categorised into two types:
Radiometric Distortions
Geometric Distortions
Radiometric Distortion
The recorded values get distorted due to one ormore of the following factors: sensor ageing
random malfunctioning of the sensor elements
atmospheric interference at the time of imageacquisition and
topographic effects.
The above factors affect radiometry (variation inthe pixel intensities) of the images and resultantdistortions are known as radiometric distortions
Geometric Distortion
The distance, area, direction and shapeproperties vary across an image, thus theseerrors are known as geometricerrors/distortions.
This distortion is inherent in images because weattempt to represent three-dimensional Earthsurface as a two-dimensional image.
Geometric errors originate during the process ofdata collection and vary in type and magnitude.
Geometric Distortions
There are two types of geometric distortions exists in satellite data
1. Systematic Errors
2. Non-Systematic Errors
Systematic Errors
Skew caused by Earth Rotation Effect
Scanning system – induced variation in ground resolution cell size
One dimensional relief displacement.
Tangential scale distortion
Earth Rotation Effect
Around 30 seconds required to capture aLandsat image (185 x 185 km).
In Landsat TM/ETM+, up till 16 scan line,distortion is gradual, however after 16 lines,distortion is greater
Satellites having small swath width have lessearth rotation effect.
Earth Rotation
Earth Rotation Effect
This displacement results in a NE to
SW orientation of the image.
Distortion in Scale due to Scanning System
For scanners, the angular
IFOV is constant. As a
result the effective pixel
size on the ground is
larger at the extremities
of the scan than at nadir.
By placing the pixels on
a uniform display grid,
the image will suffer an
across-track
compression.
Relief displacement
Objects directly below the centre of the camera lens
(i.e. at the nadir) will have only their tops visible,
While all other objects will appear to lean away
from the centre of the photo such that their tops and
sides are visible.
If the objects are tall or are far away from the centre
of the photo, the distortion and positional error will
be larger.
Distortion in Scale due to Scanning System
Objects near the edge of the flight line be compressed and their shape distorted.
If the linear feature is parallel with or perpendicular to the line of flight, it does not experience
sigmoid distortion
Non-Systematic Error
All the terminologies make for non-systematicdistortions was developed for aerial platforms.
Two types of non-systematic distortions:
1. Developed due to Altitude
2. Developed due to Attitude
Geometric variations between scan lines are alsocaused by altitude and attitude of the platform
Altitude Distortions
Due to altitude variation, FOV and IFOV changes.
Causing scale distortions.
Attitude Distortions
Roll occurs the wings
move up or down
Pitch occurs the nose or
tail moves up or down
Yaw occurs the body is
forced by wind to be
oriented some angle
Geometric Distortions
Geometric Distortions
Geometric Distortions
Slew: Motion of the platform perpendicular to the
intended direction of motion. The problem can occur when there is a cross wind over the flight path. The aircraft is oriented parallel to the intended flight path but the actual motion is at a slight angle to the intended direction. Thus, the scan lines will be perpendicular to the intended path but consecutive scan lines will be shifted in the direction perpendicular to the path.
Radiometric Error
Internal cause: When individual detectors do notfunction properly or are improperly calibrated (alsoknown as systematic errors)
These errors can be modelled, identified and corrected.
External cause: Atmosphere (between the terrainand the sensor) can contribute to noise (i.e.,atmospheric attenuation) such that energy recordeddoes not resemble that reflected/emitted by theterrain.
Radiometric Error
Some commonly observed systematicradiometric errors:
random bad pixels
line or column drop-outs
line start problems
n-Line striping
Radiometric Error
Random Bad pixels Sometimes, an individual
detector does not recordreceived signal for apixel.
This may result inrandom bad pixels.When there arenumerous random badpixels found within thescene, it is called shotnoise.
Radiometric Error
Line striping
a detector does not fail completely but its calibrationparameters (gain and offset/bias) are disturbed.
For example, a detector might record signals over adark, deep body of water that are almost uniformly 20or 30 gray levels higher than the other detectors forsame band.
The result would be an image with systematic,noticeable lines that are brighter than adjacent lines.
Radiometric Correction
External Error Correction (Correction for Environmental AttenuationError)
Two sources of environmental attenuation: Atmospheric attenuation
Topographic attenuation
Atmospheric 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., chlorophylla, 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 amodel atmosphere.
◼ Error minimized using multiple "looks" at the same object from different vantagepoints or using multiple bands.
Radiometric Correction
Topographic attenuation Slope and aspect effects include shadowing of areas of interest.
Goal of slope-aspect correction: To remove topographically inducedillumination variation (so that two objects having same reflectanceshow same BV even though they may have different slope andaspect).
Forest stand classification is improved when slope-aspecterrors are corrected.
Correction is based on illumination (proportion of direct solarradiation hitting a pixel). Digital Elevation Model (DEM)required. DEM and remote sensing data must be geometricallyregistered and resampled to same spatial resolution.
Questions & Discussion