Notes

Sr TONG Kwan-yuen
22 Oct 2014
1
Contents
 Basic concepts
 Practical Issues
 Examples
2
Data
Products
Data
Acquisition
Interpretation
& Analysis
Source of
Energy
Propagation
through the
atmosphere
Digital
Data
Processing
Pictorial
Data
Analysis
Retransmission
through the
atmosphere
Users
Information
Products
GIS Analysis
Visual
Digital
Internet or
Intranet
Information
Dissemination
3
Data
Acquisition
 Characteristics of sensor
Source of
Energy
platform
 Characteristics of
Propagation
through the
atmosphere
imaging sensor
Retransmission
through the
atmosphere
4
EM Spectrum
5
Types of Sensor Platform
Fixed-wing aircraft
Satellite
UAV
Helicopter
Car-based MMV
Backpack MMS
6
Characteristics of Sensor Platform
 Flying height
 Speed (overlapping/image motion/productivity)
 Payload (type and weight)
 Mobility (site constraints/weather conditions/relevant
legislation)
 Temporal resolution
 GNSS navigation system
 Power supply
 Weight
 Etc.
7
Sensor Platform Specifications
Example
Operating
Height
Speed
Payload
Type /Max
Weight
Revisit
cycle
Satellite
Landsat 8
705 km
27,360 km/h
Optical
sensor
16 days
Fixed-wing
aircraft
Jetstream 41
2000 – 20000 ft
160 kt
(300 km/h)
LFDAC, M/H
DC, LiDAR
Dep on
weather &
air traffic
Helicopter
EC 155 B1
300 – 2000 ft
60 – 70 kt
(100 – 120
km/h)
LiDAR, M/H
DC
Dep on
weather &
air traffic
UAV
DJI Phantom
2
180 – 300 ft
above ground
54 km/h
DC (< 7 kg)
Dep on
weather &
pwr supply
Car-based MMV
(along roads)
Survey Van
Ground level
30 – 40 km/h
M/H DC and
LS
Dep on
weather &
road traffic
Backpack MMS
(hiking trails,
village areas)
Human
Ground level
5 km/h
M/H DC
Dep on
weather &
pedestrian
flow
8
Sensor Characteristics
 Active/passive sensor
 Metric/non-metric sensor
 Film/digital and image/laser/radar sensor
 Spectral resolution (channels and bandwidth)
 Radiometric resolution
 Spatial resolution (pixel size/resolving
power/scanning resolution)
 Measuring range and accuracy
 Focal length and FOV (wide-angle/normal angle)
 Frame size/ Coverage/Swath width
9
Sensor Characteristics
 Frame rate
 Data storage devices
 Forward motion compensator
 Gyro-stabilized mount
 GNSS/IMU devices
 Power consumption
 Weight and size
 Lifespan (satellite)
 Etc.
10
Examples of Passive Sensor
Digital aerial camera
Analogue aerial
camera
Thermal sensor
Space-borne
optical sensor
Multi-head
oblique cameras
Handheld camera
360 degree
panoramic
camera
11
Examples of Active Sensor
Canadian RADARSAT-2
LiDAR Survey
Handheld
laser scanner
12
Sensors vs GSD
2 cm at 300 ft with 20 mm lens
7.5 cm at 6,000 ft with 300mm lens
 RMK-TOP
 UltraCam Eagle
4.5 cm at 6,000 ft with 210mm lens
 LiDAR
10 cm (H) and 7 cm (V) at 4,000 ft
 WorldView-2
0.46 m PAN and 1.85 m MS
 Gaofeng-2
0.8 m PAN and 3.2 m MS
 Spot 6/7
1.5 m PAN and 6 m MS
 Resources Satellite 3 5.8 m MS
 Landsat 7/8
15 m PAN and 30 m MS
 UAV
13
Sensors vs Coverage
70m at 300 ft / 20 mm lens
1,380 m at 6,000 ft / 300mm lens
 RMK-TOP
630*400 m at 6,000 ft / 210mm lens
 UltraCam Eagle
 LiDAR
500 m at 4,000 ft
 WorldView-2
16.4 km
 Gaofeng-2
Unknown
 Spot 6/7
60 km
 Resources Satellite 3 51 km
 Landsat 7/8
185 km
 UAV
14
Zeiss RMK TOP
 Focal length: 153mm and 305mm
 Film format: 230 mm x 230 mm (9” x 9”)
 Film type: Panchromatic/colour/NIR
 Lens aperture:







TOP15 : f/4.0 to f/22
TOP30 : f/5.6 to f/22
(typical f/5.6 at 6,000ft)
Shutter speed:
1/50 to 1/500 (typical 1/250s at 6,000 ft)
Frame rate per second : max 1.5s typical 2.3 to 4 s
depends on overlapping % and flying speed)
Resolving power : > 200 lp/mm
Forward motion compensator: available
Gyro-stabilized mount: available
GPS navigation: available
Weight: ~ 100 kg
• Photo intentionally removed
15
Microsoft UltraCam Eagle
 Focal length: 80 mm and 210 mm
 Pixel size: 5.2 µm (20,010 * 13,080 (PAN))
 Spectral channel: RGBN (>> 12 bits)
 Lens aperture: f=1/5.6
 Shutter system: 1/500 to 1/32
 Total field of view , cross track/along track: 66°/46°
 Frame rate per second: 1 frame per 1.8 seconds
 CCD signal to noise ratio: 72db
 Forward motion compensator : TDI controlled (50
pixel max.)
 Gyro-stabilized mount: available
 GPS/IMU device: available
 Weight: ~ 75 kg
 Size: 43 cm x 43 cm x 76 cm
16
Landsat 8
Technical Details
Operator:
NASA / USGS
Launch Date:
11 February 2013
Mission duration
5-10 years (planned)
Sensor band:
11 bands
Band 1 - Coastal / Aerosol
0.433 - 0.453 µm
30 m GSD
Band 2 - Blue
0.450 - 0.515 µm
30 m GSD
Band 3 - Green
0.525 - 0.600 µm
30 m GSD
Band 4 - Red
0.630 - 0.680 µm
30 m GSD
Band 5 - Near Infrared
0.845 - 0.885 µm
30 m GSD
Band 6 - Short Wavelength
Infrared
1.560 - 1.660 µm
30 m GSD
Band 7 - Short Wavelength
Infrared
2.100 - 2.300 µm
30 m GSD
Band 8 - Panchromatic
0.500 - 0.680 µm
15 m GSD
Band 9 - Cirrus
1.360 - 1.390 µm
30 m GSD
Band 10 - Long Wavelength
Infrared
10.30 - 11.30 µm
100 m GSD
Band 11 - Long Wavelength
Infrared
11.50 - 12.50 µm
100 m GSD
Landsat 8
Landsat 8 satellite image of HK
The Hong Kong and Pearl River
Delta Satellite Image Map Series
17
(PRDM 250S)
Landsat 8
Technical Details
Pixel size:
Operation Land Imager (OLI) multi-spectral bands 1-7,9: 30 meters
Operation Land Imager (OLI) panchromatic band 8: 15 meters
Thermal Infrared Sensor (TIRS) bands 10-11: collected at 100 meters but
resampled to 30 meters to match OLI multispectral bands
Data format:
GeoTIFF data format
Dynamic range:
16-bit pixel values
Revisit Cycle
16 days
Datum:
WGS84
Map projection:
UTM (Polar Stereographic projection for scenes with a center latitude
greater than or equal to -63.0 degrees)
Geolocation accuracy
12 meter circular error, 90% confidence global accuracy for OLI
41 meter circular error, 90% confidence global accuracy for TIRS
Swath width
185 km
Coverage
170 km north-south by 185 km east-west
File size:
Approximately 1 GB (compressed), approximately 2 GB (uncompressed)
Data charge:
Free of charge
18
WorldView-2
Technical Details
Operator:
DigitalGlobe
Launch date:
October 8, 2009
Mission duration:
7.25 years
Sensor Band:
8 bands
Band 1
Coastal
0.400 – 0.450 µm
Band 2
Blue
0.450 – 0.510 µm
Band 3
Green
0.510 – 0.580 µm
Band 4
Yellow
0.585 – 0.625 µm
Band 5
Red
0.630 – 0.690 µm
Band 6
Red Edge
0.705 – 0.745 µm
Band 7
Near-IR1
0.770 – 0.895 µm
Band 8
Near-IR2
0.860 – 1.040 µm
WorldView-2
Worldview-2 satellite image of HK
19
WorldView-2
Technical Details
Pixel size:
Panchromatic: 0.46 m GSD at nadir, 0.52 m
GSD at 20° off-nadir
Multispectral: 1.85 m GSD at nadir, 2.07 m
GSD at 20° off-nadir
Data format:
GeoTIFF, JPEG
Dynamic range:
11-bits pixel values
Revisit cycle:
1.1 days at 1 m GSD or less
3.7 days at 20° off-nadir or less (0.52 m GSD)
Datum:
NAD 83, WGS 84
Map projection:
UTM, State Plane
Geolocation accuracy:
Demonstrated <3.5 m CE90 without ground
control
Swath width
16.4 km at nadir
Max contiguous area Collected in a
single pass (30° off-nadir angle)
Mono: 138 x 112 km (8 strips)
Stereo: 63 x 112 km (4 pairs)
File size:
Depends on area of interest
Data charge
Price Per Sq Km: US$16.00
20
Resources Satellite 3
Technical Details
Operator:
China Aerospace Science and Technology
Cooperation
Launch Date:
1 January 2012
Mission duration
5 years
Sensor band:
4
Band 1 – Blue
0.45 – 0.52 µm
5.8 m GSD
Band 2 – Green
0.52 - 0.59 µm
5.8 m GSD
Band 3 – Red
0.63 - 0.69 µm
5.8 m GSD
Band 4 - NIR
0.77 – 0.89 µm
5.8 m GSD
Revisit cycle:
5 days
Swath width:
51 km
Coverage:
50 km x 50 km
Resources Satellite 3
Resource Satellite 3 image of
Forbidden City
Resource Satellite 3 image
21 of
Beijing National Stadium
Gaofen-2
Technical Details
Operator:
China Aerospace Science and Technology
Cooperation
Launching date:
19/8/2014
Pixel size:
Panchromatic: 0.8 m GSD at nadir
Multispectral: 3.2 m GSD at nadir
Gaofen-2 satellite image of Shanghai
Hongqiao International Airport
Gaofen-2 panchromatic image of
Shanghai
Gaofen-2
Gaofen-2 satellite image of
central axis of Beijing 22
How to select
Purpose
Survey accuracy
Site constraints
(extent,
topography,
surrounding
features, air
traffic control)
Cost
Data
Acquisition
 Geometric
characteristics of aerial
photos
Source of
Energy
Propagation
through the
atmosphere
Data
Processing
 Pre-processing
 Geo-referencing
Retransmission
through the
atmosphere
 Error budget
 Quality checking
24
Geometric characteristics of photo
 Obtain linear/height/angular/positional
measurements of ground features from aerial photos
 Geometric characteristics
 Vertical photo
 Projective projection
 Photo-scale
 Relief displacement
 GSD and Spatial resolution
 Stereopair photo
25
Vertical Photo
 Angle of tilt < 3°
 In real situation for J41: roll and pitch < 5 °
 Also compensated by gyro-stabilized mount: working
range ~±10°
 Gyro-stabilized mount on RC10A (1985)
 Gyro-stabilized mount and FMC on RMKTOP (1996)
26
Perspective projection
 Camera/exposure
station
 Focal length
 Image xy coordinate
system
 Principal point
27
Photo Scale (s)
 S = f/H’


f = focal length
H’ = height above
terrain
 Varies due to various
terrain height – cannot be
used as a map
 Nominal value for vertical
photo
 Barometric height from
aircraft and approx. focal
length
 Also by comparing to
known distance
28
Photo Scale (s)
 S = f/H’
Photo intentionally removed
P
29
Photo Scale (s)
 S = f/H’
 Ex. f = 300mm

H’ = 6,000 ft

S = 1: 6,000
 Ex. f = 150mm

H’ = 3,000 ft

S = 1:6,000
Photo intentionally removed
P
30
Photogrammetric measurements
(single photo)
 Apply to single vertical
photograph of flat terrain
 Planimetric : X = (H’/f) *a’b’
 Height : H’ = (f/a’b’) * AB
 H’ is the flying height
above terrains
 f = focal length
 a’b’ = image size (photo
measurements)
 AB = object size
31
Photogrammetric measurements
(single photo)
 Example – to determine size of footprint
 Assuming 230 mm * 230mm photo taken at 6,000
ft with 300 mm lens
 Footprint size = 1,380 m * 1,380 m
 If the actual H’ is 5,000 ft, then foot print size =
1,150 m * 1,150 m
 An error of 230 m or of 20%
 Can be an issue in GIS analysis application
 More precise H’ can be obtained with a DTM
model e.g. LandsD 3D Spatial Data
32
Relief Displacement (d)
 Causing aerial photos
cannot be used as a map
 Existence in all ground
features located above
reference datum
 Facilitate stereoscopic
viewing and height
measurements
33
Relief Displacement (d)
 d=r*h/H
 r = radial distance
 h = height of object
above datum
 H = flying height
above datum
34
Relief Displacement (d)
 d=r*h/H
 d  then r 


r = 0 then d = 0
(wide angle >
normal angle)
 d  then h 
 d  then H 
35
Relief Displacement (d)
230 mm
 d=r*h/H
 Ex.
 h = 100 m
 H = 3,000 ft (910 m)
 d = 8.8 mm on image
230 mm
 R = 80 mm
Photo
intentionally removed
80 mm
P
 If f = 150 mm, then S = 1:
6,000
 d = 52.8 m on ground
36
Relief Displacement (d)
 Ex. - Terraced field
 r = 100 mm
 h = 15 m
 H = 3,000 ft (910 m)
 d = 1.6 mm on image
 If f = 150 mm, then S = 1: 6,000
 d = 9.6 m on ground
 9.6 mm at 1:1,000 scale
requiring attention in DD
sheet correlation exercise
37
Relief Displacement (d)
 9.6 mm at 1:1,000 scale
 The error due to relief
displacement requiring special
attention in DD sheet
correlation exercise
particularly for large or hilly
areas
38
Ground Sampling Distance
 The corresponding size on ground of a pixel of a given image sensor at a
specified focal length and flying height
 Calculated GSD = pixel size * photo scale (flying height /focal length)
 Ex.
 For RMKTOP:
 flying ht at 6000 ft , focal length = 300 mm, photo scale = 1:6,000 , scanned
pixel size = 12.5 µm  GSD = 7.5 cm
 For UCE
 flying ht at 6,000 ft , focal length = 80 mm, photo scale = 1:22,860 , pixel
size = 5 µm  GSD = 11.5 cm
 flying ht at 6,000 ft , focal length = 210 mm, photo scale = 1:8,708 , pixel
size = 5 µm  GSD = 4.3 cm
39
Ground Sampling Distance
 Calculated GSD < > ground resolvable object size
 May be larger or smaller!
 When the spectral contrast, or colour, between
adjacent items is lower than the detectivity of the
scanning system or is less than the bandwidth of
the spectral channel  not detectable even OS >
GSD
 High spectral contrast  detectable even OS <
GSD e.g. roads, river, shadow of lamp post, other
linear features
40
Different Spatial Resolution/GRD – Object
size > GSD
Culvert:
1.2 m * 1.2m (ext)
0.9 m * 0.9 m (int.)
Photo scale = 1:3,000
GSD = 3.7 cm
Photo scale = 1:16,000
GSD = 0.2m
Different Spectral Contrast –
Object size > GSD
Photo scale = 1:16,000
GSD = 0.2m
Photo scale = 1: 16,000
GSD = 0.2m
42
Object size < GSD
Flag pole (4
cm dia. 2.5m
high)
Photo scale = 1:3,800 GSD = 4.8 cm
Spectral Contrast –
object size < GSD
Photo scale = 1:8,000
GSD = 10 cm
Spatial Resolution
 A term to describe ground resolvable distance
 In practice, the spatial resolution of the captured
image on film/image sensor is a combined effect of the
lens





size and types of film/image sensor
spectral resolution and spectral contrast
radiometric resolution
illumination conditions
image motion, etc.
 For aerial photos taken in SMO
 ~ 40 lp/mm to 80 lp/mm
 12.5 µm and 7 µm in width per line
 Actual measuring accuracy  spatial resolution
45
Ways to improve spatial resolution
 Lower flying height
 Longer focal length
 Larger B/H ratio
 Higher percentage of photo
overlapping %
 Use individual image sensor for
separate colour channel (Not Bayer
pattern sensor)
46
Photogrammetric measurements
(single photo)
Error sources
 Relief displacement
 Tilt
 Paper or film shrinkage
 Differential shrinkage
 Lens distortion
 Focal plane flatness
 Atmospheric distortion
 Earth curvature distortion
 Image measuring errors
47
Geometry of Overlapping Vertical Photos
X1, Y1 , Z1, ω1- ϕ1-κ1
X2, Y2 , Z2, ω2- ϕ2-κ2
48
Measurement of X-Parallax
 Parallax is the apparent
displacement in the position
of an object, with respect to a
frame of reference, caused by a
shift in the position of
observation
 Parallax of any point is directly
related to the elevation of the
point
 Parallax is greater for high
points than for low points
49
Photogrammetric Measurement - XParallax
A properly oriented stereopair,
Enable stereoviewing
Enable measuring the
planimetric position and
height of a point
50
Parallax equation
Parallax equation
 Xa = B * xa / Pa
 Ya = B * ya / Pa
 ha = H – (B*f)/Pa
 Where ha = the elevation of point A above datum
 Xa and Ya = ground coordinates of point A
 H = flying height above datum
 B = air base
 f = focal length
 Pa = x-parallax of point A
51
General Approach by Collinearity
Equation
 Transformation of coordinates from image space to ground
space or vice versa
 By space resection and space intersection
 Accuracy depends upon the angles of intersection
 Apply computer processing and least square bundle
adjustment
52
Collinearity Equation
Aerial case
X1, Y1 , Z1, ω1- ϕ1-κ1
Terrestrial case
X2, Y2 , Z2, ω2- ϕ2-κ2
XA, YA , ZA
Applicable to vertical photos,
tilted photos, terrestrial photo,
non-metric camera (UAV),
satellite imagery, 360 degree
panorama photos, aerial
triangulation, multi-ray
processing, GNSS/IMU georeferencing……
53
Collinearity Equation
xa = -f *
[m11(Xa-XL) + m12(Ya-YL) + m13(Za-ZL)]
[m31(Xa-XL) + m32(Ya-YL) + m33(Za-ZL)]
ya = -f *
[m21(Xa-XL) + m22(Ya-YL) + m23(Za-ZL)]
[m31(Xa-XL) + m32(Ya-YL) + m33(Za-ZL)]
Where
xa and ya are the image coordinates of point a
f is the focal length
M’s are functions of the rotation angles omega, phi and kappa
XL YL ZL are the ground coordinates of camera station
Xa Ya Za are the ground coordinates of point a
54
Space Resection by Collinearity
 Yields all six elements of
exterior orientation (of a single
photo) XL, YL and ZL and (ωϕ-κ)
 Minimum 3 full GCPs (X, Y, Z)
 6 equations for 6 unknowns
55
Space Intersection by Collinearity
 Known (XL1, YL1 , ZL1, ω1, ϕ1,κ1)
and (XL2, YL2 , ZL2, ω2, ϕ2,κ2)
 Determine X, Y, and Z ground
coordinates of new points
 4 equations for 3 unknowns
56
Stereoscopic Viewing
 Left and right eyes see the left
and right photos respectively
 Reconstruct the geometrical
relationship of the stereopair
at the time of photography
57
Stereoscopic Viewing
 Digital Photogrammetric
Workstation
 High-end computer
 3D Monitor
 Refresh rate/ graphic card
 Active/passive stereoscopic
glasses
 Synchronization
 Epipolar geometry
 Image pyramid
 3D Mouse
 Z thumbwheel
 Programmable button
58
Data Processing Workflow
 Pre-processing
 Geo-referencing
 Error budget
 Quality checking
59
Data Processing Workflow
Analog Workflow
Analog
Acquisition
Transfer
Film
Development
Georeferencing
and AT
Scanning
Application,
e.g. Stereo,
Mapping, Ortho
Analog -> Digital
Digital Workflow
Digital
Acquisition
Download
Image Preprocessing
Georeferencing
and AT
Application,
e.g. Stereo,
Mapping,
Ortho
Full Digital Workflow
60
Geo-referencing Method
 The process of determining X, Y and Z ground
coordinates of individual points
 Aerial triangulation with GCPs and/or GNSS/IMU
 Direct geo-referencing with GNSS/IMU data only
61
Aerial Triangulation
 Based on measurements from a block of photos
 Use of collinearity equations
 Least square bundle adjustment
 support post-adjustment statistical analysis for
error detection and indication of accuracy
 support photos of any focal length, tilt, and
flying height
 determine camera calibration data
 support GNSS/IMU data
62
Aerial Triangulation
 Applications
 extending or densifying ground control through
strips or blocks of photos for use in subsequent
photogrammetric operations
 surveys where precise ground coordinates are
needed e.g. define house corners used as
boundary evidence
 Create digital terrain model (dense DSM as a
point cloud model), etc.
63
GCPs Configuration on Photo Block
 Min. 60% endlap 20%




sidelap
Horizontal control around
the periphery of the area
Interior must have vertical
control
Control points should
appear on as many photos as
possible to increase the
redundancy
Min. 2 horizontal and 3
vertical control points
64
Accuracy Assessment
 Post-adjustment statistically analysis
 A priori measuring accuracy = N pixel
 RMS (image meas) < N pixel
 Max residual < 3N pixels
 RMS (Control point) < scale factor and
absolute positioning
 Check points < survey accuracy
 E.g. For 1:6,000 photos and ± 0.3 m and ± 0.4 m
in horiz and height position for 1:1000 mapping
 A priori acc. = 12.5 µm
 Resulting RMS = 6 µm < 12.5 µm
 Resulting max residual = 25 µm < 37.5 µm
 RMS xy = 0.1 m < 0.3 m
 RMS z = 0.2 m < 0.4 m
65
Direct georeferencing
 GNSS/IMU device to obtain EO parameters
 No GCPs needed for lower order accuracy
 To be applied in UltraCam Eagle
66
Image Pre-processing
for Satellite Imagery
Image Pre-processing for Satellite Imagery
Level 0
(raw)
Level 1A/1B
(radiometric &
geometric
correction)
Level 2A/2B
(map
projection/geo
-referenced)
Level 3A/3B
(Orthorectified/
Mosaicked)
Atmospheric
correction
(scattering/absor
ption/haze
removal)
Application,
e.g. NDVI,
Ortho
Level “X” Products
67
Preprocessing
Satellite images (Landsat 8)
 Level 0 product – raw data
 Level 1A product
 corrected for detector variation within the sensor
correction
 corrected for radiometric errors associated with detector

Line dropout, Banding or striping, Line start errors, Gain and
offset
 Level 1B
 Corrected for geometric distortion due to Earth’s
rotation

Mis-aligned scan lines and non-uniform pixel size
68
Preprocessing
 Level 2A
 Systematically mapped into a standard cartographic
map projection (approximately geo-referenced w/o
GCPs)
 Level 2B
 Geo-referenced with the use of GCPs
 by least square (bundle) adjustment using rational
polynomial camera model and collinearity equations,
rubber sheeting, etc.
 Level 3A
 Ortho-rectified with DTM
 Level 3B
 Mosaick of Level 3A scenes Atmospheric correction
69
Atmospheric correction
 Scattering of solar energy – increase DNs
 Absorption of solar energy – decrease DNs
 Haze removal, solar elevation (seasonal effects in
reflectance) and solar altitude (diurnal effect)
 Correction methods
 Using atmospheric model
 Dark pixel subtraction (no response features e.g. cloud
shadow, freshly paved parking lots, large bodies of open
water)
 linear regression (2 scenes of different dates)
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Geo-referencing Method
 Rational polynomial coefficients
 up to 78 RPCs (high resolution satellite imagery)
 25+ GCPs
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Error budgets
and quality checking
72
Error Budget on Photogrammetric
Measurements with DPW
Error sources (mostly corrected in georeferencing processes IO and AO)
 Relief displacement (Observables )
 Tilt (corrected in AO)
 Image distortion (film/scanning processes) (corrected in IO)
 Differential shrinkage (corrected in IO, negligible in digital image sensor)
 Lens distortion (corrected in IO)
 Focal plane flatness (corrected in IO, negligible in digital image sensor)
 Atmospheric distortion (corrected in IO)
 Earth curvature distortion (for high flying height > 20,000 ft (corrected
in IO)
 Unequal flying height (corrected in AO)
 Transferring principal points (corrected in AO)
 Image measuring error * √2
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Error Budget
Simplified photogrammetric equations for
stereoscopic measurements
Planimetric : X = H’/f (a’b’)
Height : dh = dP * (H’/f) * (H’/B) (parallax
equation for height)
 H = the flying height above terrains
 f = focal length
 I = image (photo measurements)
 dP = difference in parallax between 2 points
 B = air base
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Error Budget
Error estimation:
Planimetric : σX =σm * (H/f)
Height : σh =σp (H/f) * (H/B)
or σh = 1.4σm * (H/f) * (H/B)
 σp = measuring accuracy of parallax
 σm = measuring accuracy of image
coordinates (affected by spatial
resolution)
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Error Budget
Example
 In SMO for 1:1000 mapping jobs with RMK-TOP (with FMC
and gyro-stabilised mount ), σm = 12.5 µm
 Assuming H = 6,000 ft, f = 300mm, B:H ratio = 0.3 (60%
overlap), σm = 12.5 µm
 Gives photo scale = 1: 6,000 and GSD = 7.5 cm
 Therefore σXY = ± 7.5 cm and σh = ± 35 cm
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Control point error :
 Spatial resolution and positioning
error can be of two separate
aspects
 For 1:1000 mapping
 Positioning error of measured
point on aerial photos = ± 0.3 m
horizontal and ± 0.4 m vertical
 Ground control point error
 Planimetric control = ±5 cm
 Height control = ±10 cm
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Quality checking
NSSDA Positional Accuracy Assessment
 Positional accuracy (National Standard for Spatial
Data Accuracy by US FGDC)
 Select well identified points
 Tested by comparing to an independent data set of
greater accuracy of 3 times or more
 Use of 20+ check points to conduct a statistically
significant accuracy evaluation Ideally, evenly spaced
and distributed
 Compute r.m.s.e. and the corresponding values at 95%
confidence level
 Present accuracy statement at 95% confidence level
78
Data
Products
Data
Acquisition
Source of
Energy
Propagation
through the
atmosphere
Data
Processing
Pictorial
Digital
Retransmission
through the
atmosphere
 Photogrammetric plot
 Orthophoto
79
Data Products
Raw data products
 Aerial films
 Digital aerial image
 Simultaneous multiple-view images (aerial/terrestrial)
 Laser scanning point clouds
 Remote sensing data (visible/thermal/multispectral/radar spectral channels)
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Data Products
Derived data products
 Photogrammetric Plots
 Orthophoto (classic/true)
 360 degree panoramic images
 Geo-referenced video
 Digital Elevation Model (DEM)
 3D model
 Interferogram
 Post-processed thermal/multi-spectral/hyper-spectral
images
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Photogrammetric plots (photos)
 3D digitization and photo




interpretation on stereomodel
Feature extraction according to
mapping project specifications
Vector format
Incompletion due to obscured
area
Need field completion and
verification for quality
checking
82
Orthophoto
 Photos intentionally removed
83
Orthophoto
 Geometrically rectified aerial photo
 Advantages
 Show pictorial information of infinite number
of ground objects
 Geo-referencing product with uniform scale
support taking measurements
 Seamless
 Support GIS analysis
(Photo borrowed from SMO website)
 Limitations
 Existence of shadow areas
 Lack of height information and annotation
 Time consuming in producing true
orthophoto
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Production of Digital Orthophoto
Aerial
photography
Scanning (for
film only)
Geo-referencing
Seamline editing
Orthophoto
generation
DTM digitization
Colour Balancing
Mosaicking
QA/QC
Final Orthophoto
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DEM Generation
 DEM is generated to remove relief error
Building lean on Orthophoto
Design Parameters
 Determine smallest ground resolvable distance and
GSD(orthophoto)
 GSD(orthophoto) < 0.5 * GRD (Nyquist sampling rate)
 Ex. 1 m GRD for 1:5,000 DOP (0.2 mm at plan scale) , set
GSD = 0.5 m
 Selection of aerial photo
 GSD(aerial photos) ~ GSD(orthophoto)
 Accuracy and economy considerations
 Ex. 8,000 ft with wide angle = 1:16,000 photo scale
 Scanned at 12.5 µm gives GSD = 0.2 m
88
Design Parameters
 Determine orthophoto planimetric accuracy
 Sufficient suitable APCP for aerial triangulation
 Ex. 2 m for 1:5,000 , then GCP accuracy < 0.5 m
 Determine DTM accuracy
d=r*h/H
 σd =σh * (r/H) or σh =σd * (H/r)
 Ex. H = 8,000 ft, r = 80 mm and σd = 62.5 µm (= 5 pixels
on image = 1 m GRD)
 Therefore σh = 1.9 m
89
Design parameters
 Select 20+ check points and compute RMS
 Ex. RMS < 2 m
 Storing data of source image for traceability
 seamline polygon and associated aerial photo number
 shadow fill-up images
90
Quality indicators
 Planimetric positional accuracy
 Geo-referencing
 DTM editing
 Seamline editing and mosaicking
 Logical geometry
 Illogical building leaning direction
 Discontinued features
 Radiometric quality
 colour balancing and enhancement
91
Seamline
92
Discontinued feature
93
Discontinued feature
94
Inconsistent colour matching
95
True Orthophoto
Buildings show a leaning
appearance – existence relief
displacement distortion
Buildings shown in correct
planimetric position - relief
displacement corrected
96
True Orthophoto with Pixel-based DTM
Dense DTM
 Advanced pixel-based DTM
matching algorithm (semiglobal matching)
 High overlapping digital aerial
photos (80% endlap and 60%
sidelap)
 High-end computers
Above: True orthophoto
Below: Classic orthophoto
97
Data
Products
Data
Acquisition
Interpretation
& Analysis
Source of
Energy
Propagation
through the
atmosphere
Digital
Data
Processing
Pictorial
Data
Analysis
Retransmission
through the
atmosphere
Users
Information
Products
GIS Analysis
Visual
Digital
Internet or
Intranet
Information
Dissemination
98
Common Applications in HK
 Mapping
 Photo records to comply with statutory
requirements
 Freezing survey
 Land control and lease enforcement
 Photo evidences in adverse possession case
 NDVI Study for tree survey
 Heritage preservation
 Heat island study
99
References
 J.C. McGlone, (2004). Manual of Photogrammetry. USA: ASPRS
 S.Morain & S.L.Baros, (1996). Raster Imagery in Geographic






Information Systems. USA: OnWord Press
P.R.Wolf & B.A.Dewitt, (2000).Elements of Photogrammetry. USA:
McGraw-Hill
J.Shan & C.K.Toth, (2009). Topographic Laser Ranging and Scanning.
USA: CRC Press
T.M.Lillesand & R.W.Kiefer, (1994). Remote Sensing and Image
Interpretation. USA: John Wiley & Sons
K.H.Y.Ho & M.I.Wallace, (2006). A basis Guide to Air Photo
Interpretation in Hong Kong: Ove Arup & Partners Hong Kong Ltd.
R.Graham, (1998). Digital Imaging. UK: Whittles Publishing
Positional Accuracy Handbook, Minnesota Planning Land
Management Information Centre, October 1999
References
 Airliner.net - http://www.airliners.net/aircraft-data/stats.main?id=56
 Baidu - http://baike.baidu.com/view/2728902.htm
 Business Insider - http://www.businessinsider.com.au/pictures-from-chinas-newsatellite-gaofen-2-show-incredible-detail-right-down-to-pedestrian-crossings-2014-9
 Car Show Room - http://www.carshowroom.com.au/newcars/2013/Toyota/Hiace/O0213A
 DigitalGlobe http://www.digitalglobe.com/sites/default/files/DG_WorldView2_DS_PROD.pdf
 DJI - http://www.dji.com/product/phantom-2/spec
 MapMart - http://www.mapmart.com/Products/SatelliteImagery/WorldView2.aspx
 Microsoft UltraCam Blog - http://ultracam.wordpress.com/2011/10/11/geconnexionarticle-ordnance-survey-tells-about-implementing-the-ultracamxp/
 PointGrey - http://ww2.ptgrey.com/spherical-vision
 Satellite Imaging Cooperation – http://www.satimagingcorp.com/satellitesensors/worldview-2/
 SASMAC - http://sjfw.sasmac.cn/index/wxcp.jsp
 SMO - http://www.landsd.gov.hk/mapping/en/about/about.htm
 Space Flight 101 - http://www.spaceflight101.com/long-march-4b---gaofen-2-launch.html
 USGS - http://landsat.usgs.gov/landsat8.php
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THANK YOU
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