9.1 Physical Basics
9.2 Recording Techniques 9.3 Image Processing
9.4 Thematic Classification 9.5 Summary
9 Remote Sensing
http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf
• A geographic information system (GIS) is a computer hardware and software system designed to
– Collect – Manage – Analyze – Display
geographically referenced data (geospatial; spatial)
• It is a specialized information system consisting of a (spatial) database and a (special) database system
9 Remote Sensing
Visualization, Cartography
Spatial Data Management Collection of
Spatial Data
Analysis, Modelling
Functional Components Structural Components
• Recording on site
– Terrestrial survey techniques
• Global navigation satellite systems (e.g. GPS)
• Very long baseline interferometer (VLBI)
• Theodolite: measuring both horizontal and vertical angles optically
• Total station: electronic theodolite (transit) integrated with an
electronic distance meter
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 733
9 Remote Sensing
http://de.wikipedia.org/
www1.tu- darmstadt.de
www.photolib.noaa.gov
http://tu-dresden.de/
– Hydrographic survey
• Sounding
– Thematic survey
• Map digitization
• Survey by different sources
– Statistics
– Ministerial data
– Technical literature
• Aerial survey and survey by remote sensing
9 Remote Sensing
http://tu-dresden.de/die_
tu_dresden/…/papers/fuhrland.pdf
• Remote sensing is the acquisition of information of an object or phenomenon, by the use of device(s) that are not in physical or intimate contact with the
object
→ indirect observation technique
– That uses the electromagnetic radiation which is emitted by the observed object
– That carries receiving devices on aircraft or spacecraft
– That serves for the observation of the surface of the earth including all objects thereon, the oceans or the
atmosphere
9 Remote Sensing
http://www.etsu.edu/cas/geosciences/
• Photogrammetry
– Greek: photo - grammetry = image-measurement – Acquisition and analysis of images to determine the
properties, form and position of arbitrary objects – Remote sensing is the acquisition of
physical properties of objects whereas photogrammetry is the reconstruction of their geometric form
based on this data
9 Remote Sensing
http://www.gisdevelopment.net/…/mm063d_155.htm www.maps.google.de
• System Characteristics
– Recording techniques
• Radiometric resolution
• Geometric resolution
– Platform
• Kind of platform
• Altitude
• Orbit
• Period
– Mission
• Temporal coverage
• Spatial coverage
9 Remote Sensing
www.atmos.albany.edu/deas/
atmclasses/atm335/history.pdf
www.irs.uni-stuttgart.de
• Electromagnetic waves as information carrier
– Straight propagation with the speed of light – Speed of light = wavelength x frequency
– Longer wavelength, lesser energy → more difficult to sense
9.1 Physical Basics
electrical field distance
magnetic field M
E
c
speed of light
ν: frequency
λ: wavelength
number of cycles that passes a certain point per second
http://www.fe-lexikon.info/images/
ElektromagnetischeWelle.jpg
• Electromagnetic spectrum
– The electromagnetic spectrum is the range of all possible frequencies of electromagnetic radiation
9.1 Physical Basics
http://de.wikipedia.org/wiki/Bild:Elektro-magnetisches_Spektrum.JPG
• Behavior of electromagnetic waves at interfaces
9.1 Physical Basics
Reflection
Emission Absorption
Transmission
Scattering
Transmission + Reflection + Absorption = 1
9.1 Physical Basics
[Al09]
solar radiation
sensor
received signal
scattered light atmospheric absorption
and scattering sky radiation
reflection at the surface scattering at the surface absorption and reflection
in the water (suspended particles)
reflection at the ground
water depth
– The albedo (lat. albedo = „whiteness“), reflectivity
• The extent to which an object diffusely reflects light from the sun
9.1 Physical Basics
– Albedo depends on wavelength
• There is a strong difference between visual and infrared albedos of natural materials
9.1 Physical Basics
[Al09]
• The sun is the most important source of electromagnetic radiation
• With the exception of objects at absolute zero, all objects emit electromagnetic radiation
– The higher the temperature, the shorter the wavelength of maximum emission
9.1 Physical Basics
www.eduspace.esa.int/eduspac e/.../images/03.jpg
• Blackbody
– Hypothetical source of energy that behaves in an idealized manner
– It absorbs all incident radiation, none is reflected – It emits energy with perfect efficiency
– Its effectiveness as a radiator of energy varies only as temperature varies
9.1 Physical Basics
http://mynasadata.larc.nasa.gov/images/BB_illustration2.jpg
• Emissivity
– The ratio between the emitance of a given object and that of
blackbody at the same temperature
– Useful measure of the
effectiveness of objects as radiators
– Kirchhoff‘s law: At thermal
equilibrium, the emissivity of a body (or surface) equals its absorptivity
9.1 Physical Basics
surface emissivity (8-14 μm) blackbody 1
water, depending on pollution
0,973-0,979
water with oil film
0,96-0,979
snow 0,99
grass,
dense, short
0,92-0,97 Sands,
depending on water moisture
0,88-0,985
• Atmospheric window
– Ultraviolet 0.01 - 0.4 μm
• Reflected solar radiation
• Because of atmospheric absorption it can only be used on aircrafts flying at low altitude
• Main application: oil contamination detection in water (it is possible to identify the ship which has lost the oil!)
9.1 Physical Basics
www.geographie.ruhr-uni-bochum.de/agklima/vorlesung/strahlung/spektrum-atmosphaere.jpg
– Visible light 0.4 - 0.7 μm
• Reflected solar radiation
• Atmospheric influences particularly on blue and green light
• Several applications, e.g. land use mapping
– Near infrared 0.7 - 3 μm
• Reflected solar radiation
• Nearly no atmospheric influences
• Main application: Classification of vegetation, forest health survey (healthy green plants
strongly reflect near infrared radiation), classification of water (expanses of water seem dark as they absorb all)
9.1 Physical Basics
http://altmed.creighton.edu/
– Far infrared (thermal energy) 3 - 1000 μm (usually : 8 - 14 μm)
• Radiation emitted by the earth
• Nearly no atmospheric influences (but clouds are
impermeable, CO
2as well: greenhouse effect is measurable!)
• Applicable day and night
• Measurements beneath the surface to some extent
(pipelines and leaks...)
• Applications for which the temperature and its change are important, e.g. sea temperature, thermal properties of stone, tectonics
9.1 Physical Basics
http://www.qualitas1998.net/paul/
– Passive microwaves 1 - 300 mm
• Emitted radiation
• Nearly no atmospheric influences (capable to measure through clouds)
• Measurements beneath the surface to some extent
• Complex signal difficult to interpret
• Low ground resolution (weak signal)
• Disadvantageous SNR (Signal-to-Noise Ratio) → noisy images
• Main applications: Meteorology (temperature profiles of the atmosphere) und oceanography (ice observation)
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 750
9.1 Physical Basics
http://www.icefloe.net/hly0503/
– Active microwaves (radar) 1 - 300 mm
• Reflected, transmitted microwave radiation
• Nearly no atmospheric influences (except reaction on water drops)
• Applicable day and night
• Measurements beneath the surface to some extent
• Polarization effects
• Higher ground resolution as passive microwaves
• Complex signal
• Doppler effect allows detection of
moving objects (military applications), sea pollution
9.1 Physical Basics
http://www.wetteronline.de/
• Orbits
– Altitude, orbital period, – Apogee/perigee
• Greatest/least distance from the earth
– Inclination
• Angular distance of the orbital plane from the equator
9.1 Physical Basics
v orbital speed
R Earth‘s radius= 6 370 km g0
gravitational acceleration on the Earth‘s surface = 9,81 m/s2
r radius of the satellite orbit
r
R
gv
0www.satellitentracking.de/txt/ 04_satellitenbahnen.html
– Low Earth Orbit (LEO)
• Heights between 200 and 600 km
• Manned space stations: low inclination and heights above 400 km
• Satellites with biological or material experiments and astronomical satellites
• Spy satellites 90° inclination , perigee 200-250 km, apogee 600-900km
– Medium Earth Orbits (MEO)
• All orbits above 1000 km up to 36000 km
• Navigation satellite systems (GPS, Glonass)
• Small communication satellites
9.1 Physical Basics
http://www.tobedetermined.org/
– Geosynchronous/geostationary Orbit (GSO)
• Orbit height approximately 35786 km, 0° inclination
• Period is equal to the Earth's rotational period → It
maintains the same position relative to the Earth's surface
• Television satellites, weather satellites
– Sun Synchronous Orbit (SSO) or Polar Earth Orbit (PEO)
• Orbit height between 700 and 1000 km, inclination approximately 90°
• Orbit ascends or descends over any given point of the Earth's surface at the same local mean solar time so the
surface illumination angle will be nearly the same every time
• Earth observation satellites
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 754
9.1 Physical Basics
http://cimss.ssec.wisc.edu/sage/
• Passive systems: photography, scanner (optomechanical, optoelectronical)
• Active systems: radar sensors
9.2 Recording Techniques
reflected solar radiation thermal
radiation reflected artificial
radiation
R R
T/R
passive systems active systems
• Passive technique
• VIS and NIR (400-1000 nm)
• Analog storage medium
• Common types of films
– Black and white/panchromatic:
• Highest geometric resolution
– Infrared
• Unusual representation
• Contrastier
• Distinction between coniferous and deciduous forests
• Surfaces of water easier to identify
9.2 Photographic Systems
[Al09]
– Color/chromatic:
• Worse geometric resolution as black and white, better thematic interpretability
– Color infrared films:
• The blue-sensitive layer is replaced by an emulsion sensitive to a portion of the near infrared region
• Good thematic interpretability (vegetation).
9.2 Photographic Systems
[Al09]
• Example: aerial photo of Braunschweig
– Altitude approximately 1600 m – Ground resolution 10 cm
– Color reversal film – Central projection – 21. April 2005
9.2 Photographic Systems
www.braunschweig.de/.../luftbilder.html
• Example: Cosmos with KVR 1000 Camera
– Russian spy satellite
– Polar, sun-synchronous – Altitude 200km
– Ground resolution 2m – Black and white film – Durability 45 days
9.2 Photographic Systems
http://www.spotimage.fr/web/en/186-kvr-1000.php
• Disadvantages
– Difficult radiometric calibration – Low spectral bandwidth
– Analog data
• Advantages
– Relatively cheap – High resolution – „Spontaneous“
recording of areas
9.2 Photographic Systems
http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf
• Optomechanical scanner
• A rotating 45 degree scan
mirror continuously scans the Earth beneath the
platform perpendicular to the direction of flight
• The system collects data one pixel at a time sequentially
• A scan line (mirror rotation) is equivalent to the image swath
• The forward motion of the platform used to acquire a scene with sequential scan lines
9.2 Whisk Broom Scanner
http://www.mikroelektronik.fraunhofer.de/
9.2 Whisk Broom Scanner
scan direction
aperture angle
altitude
sensor platform
flight direction
a: geometric resolution > ground segment s: swath width
instantaneous field of view IFOV: pixel
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
motor
rotating mirror
radiation
optical system telescope
beam splitter dispersion prism
photodetectors beam splitter
interference grid
electronics
amplifier, converter
streamer
magnetic tape HDDT, CCT
• Radiation imaging
– Mirror rotates around an axis parallel to the flight direction – The radiation is split into its various wavelengths and focused
onto detectors
– Stored on magnetic tape (HDDT, CCT), remote data transmission
9.2 Whisk Broom Scanner
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
• Advantages
– Precise spectral and radiometric measurements
– Wide total field of view – Digital data, remote data
transmission
• Disadvantages
– Relatively short dwell-time – S-bend
– Panoramic distortion
– Low SNR → limited radiometric resolution
9.2 Whisk Broom Scanner
http://landsat.gsfc.nasa.gov/images/archive/c0005.html
• Landsat
– American satellite series
• Landsat 1: 1972-1978
• Landsat 2: 1975-1981
• Landsat 3: 1978-1983
• Landsat 4: 1982-1993
• Landsat 5: since 1984
• Landsat 6: 1993 failure
• Landsat 7: since1999
9.2 Whisk Broom Scanner
http://de.wikipedia.org/wiki/Landsat
1-3
6, 7 4, 5
– Orbit
• Near polar, sun synchronous
• Altitude: 907-913 km (Landsat 1-3), 705 km (Landsat 4-7 )
• Inclination: 99.2° (Landsat 1-3), 98.2° (Landsat 4-7)
• Orbital period:
approximately 100 minutes
→ 14 circulations per day
• Provide complete coverage
of the Earth every 18
(Landsat 1-3) respectively 16 days (Landsat 4-7)
9.2 Whisk Broom Scanner
ground trace for Landsat1-3 for one day [Al09]
LANDSAT 4,5 (1-3) LANDSAT 4,5 LANDSAT 7 sensor Multispectral Scanner
(MSS)
Thematic Mapper (TM) Enhanced Thematic Mapper Plus (ETM+) pixel size 79 x 79 m² 30 x 30 m² 30 x 30 m²
spectral channels
1 (4) 0,50 - 0,60 µm, green
2 (5) 0,60 - 0,70 µm, red
3 (6) 0,70 - 0,80 µm, near infrared
4 (7) 0,80 - 1,10 µm, near infrared
1 0,45 - 0,52 µm, blue- green
2 0,52 - 0,60 µm, green 3 0,63 - 0,69 µm, red 4 0,76 - 0,90 µm, near infrared
5 1,55 - 1,73 µm, mid infrared
7 2,08 - 2,35 µm , mid infrared
1 0,45 - 0,52 µm, blue- green
2 0,52 - 0,60 µm, green 3 0,63 - 0,69 µm, red 4 0,76 - 0,90 µm, near infrared
5 1,55 - 1,73 µm, mid infrared
7 2,08 - 2,35 µm , mid infrared
thermal channel 6 10,4 - 12,5 µm (120 x 120 m²)
6 10,4 - 12,5 µm (60 x 60 m²)
panchromatic channel 8 0,52 - 0,90 µm
(15 x 15 m²)
9.2 Whisk Broom Scanner
– Typical combination of channels
9.2 Whisk Broom Scanner
0,5-0,6 μm 0,8-0,9 μm
false colour composite
0,6-0,7 μm
true colour composite
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
infrared red
green
9.2 Whisk Broom Scanner
http://landsat.gsfc.nasa.gov/images/lg_jpg/f0012_77-89-06.jpg
• Optoelectronical scanner
• Employs a linear array of solid semi- conductive elements to acquire one entire line of spectral data
simultaneously
• Scan lines perpendicular to the direction of flight
• Forward motion of the platform to acquire a sequence of imaged lines to map a scene
• CCDs (charge coupled device) to serialize parallel analog signals
9.2 Push Broom Scanner
http://www.fotos.docoer-dig.de/
9.2 Push Broom Scanner
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
scan direction
: aperture angle
altitude
sensor platform
flight direction
a: geometric resolution > ground segment s: swath width
focal distance
lens
aperture angle sample mirror
CCD sensors
optical system radiation
• Radiation imaging
– Tilted mirror, sometimes fixed sometimes tiltable
– CCD image sensors in the image plane of the lens: line scan camera
– Data storage in parallel memory chips, remote data transmission
9.2 Push Broom Scanner
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
• Spot (Systeme Probatoire d'Oberservation de la Terre)
– French satellite series
• Spot-1: 1986-1990
• Spot-2: since 1990
• Spot-3: 1993-1997
• Spot-4: since 1998
• Spot-5: since 2002
– Two identical parallel sensors that can be operated
independently of one another
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 773
9.2 Push Broom Scanner
http://www.uni-potsdam.de/...
/febasis/febasis06_04-1206.pdf
http://www.fe-lexikon.info/images/Spot5.jpg
1-3
4
5
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
angled
view nadir-
looking
– Pivoting of the sensors can be employed for stereoscopy and also for a higher repeat circle – Sensors are operated from the ground stations
9.2 Push Broom Scanner
http://www.terraengine.com/Dgroundstation.cfm
– Orbit
• Sun synchronous
• Altitude: 822 km
• Inclination 98,7°
• Orbital period 101,4 min
→ approximately 14 circulations per day
9.2 Push Broom Scanner
SPOT 1-3 SPOT 4 SPOT 5
sensor HRV (Instrument Haute Résolution Visible)
HRVIR (High Resolution Visible and Infrared)
HRG (High Resolu- tion Geometric) geometric
resolution
20 m (XS), 10 m (PN)
20 m (XS), 10 m (P)
10 m (VIS, NIR), 2,5/5 m (PAN), 20 m (MIR) radiometric
resolution
0,5-0,9 μm:
3 VIS, 1 NIR
0,5-1,75 μm:
3 VIS, 1 NIR, 1 MIR
0,45-1,75 μm:
2 VIS, 2 NIR, 1 MIR
http://spot5.cnes.fr/.../35.htm
9.2 Push Broom Scanner
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
Spot-1 HRV P-Modus
San Diego(USA), panchromatic, resolution 20 m
Spot-1 HRV XS-Modus
Detroit(USA), false colour
composite, resolution 30 m
Spot-5 HRG XS-Modus: stereo
9.2 Push Broom Scanner
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
Dead sea (Jordan), panchromatic, 11/2002 resolution 2,5 m
• Radio Detection And Ranging
• Principle:
– Transmitting radar pulses (microwaves) and recording the reflected radiation
→ active
– The transit time and the strength of the reflected signal is measured
9.2 Radar
[LKC08]
• Nadir:
– The local vertical direction pointing in the direction of the force of gravity at that location
• Range:
– Line of sight
• Azimuth:
– Direction of flight
9.2 Radar
http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf
• Recording parameters
– Polarization
• Direction of the electric field which is perpendicular to the direction of propagation in the transmitted radar signal (H = horizontal, V = vertical)
→ 4 possibilities: HH, VV, HV, VH
– Depression angle θ
d– Pulse length
– Wavelength is divided into 5 bands
9.2 Radar
http://ladamer.org/.../FE1-06-Radar.pdf
K-band X-band C-band L-band P-band 0,7-1 cm 2,4-4,5 cm 4,5-7,5 cm 15-30 cm 77-136 cm
B GR2
GR1
R2 R1
A
A β B
• Azimuth resolution AR depends on beam
width(β) and the ground range distance (GR)
→ Azimuth resolution is better in the near range
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 781
9.2 Radar
[LKC08]
GR
AR
L
and L: antenna length
λ: wavelength where
• Ground range resolution (GRR) depends on the pulse length (τ) and the depression angle(θ)
– Distinction between
A and B only possible
if the pulse passed A completely before reaching B
→ Better ground range resolution in the far range
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 782
9.2 Radar
Pulse length τ
Front of return wave from A
Front of return wave from B
A B
τ
< 2
Rear of
outgoing wave
cos 2 c GRR
[LKC08]
• In order to improve the resolution
– Ground range
• Decrease pulse length
– Azimuth
• Decrease wavelength
• Increase antenna length
• The azimuth resolution
is unacceptably coarse for systems operating at satellite altitudes
9.2 Radar
http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf
• Synthetic aperture radar (SAR)
– Scene is illuminated over an interval of time → history of reflections
– The further an object the longer the time it is illuminated
– As changes in frequency are systematic separate components of the
reflected signal can be assigned to their correct position
9.2 Radar
http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf
• Doppler-effect
– Approaching → increase in frequency
– Receding → decrease in frequency
• Physical antenna as small as possible
• Azimuth resolution
independent of GR and λ
9.2 Radar
http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf
synthetic aperture
radar pulse with frequency v2
frequency v2
object
v1 – v2 > 0 v3 – v2 < 0
• Comparison of the resolution between systems with real (a) and synthetic (b) aperture
9.2 Radar
http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf
• Interactions between radar signals and materials very complex as it depends on:
– Wavelength
– Incidence angle
– Electrical properties – Moisture
– Surface property
9.2 Radar
http://www.meteo.physik.uni-muenchen.de/.../fe_boden_micro.html
• Penetration depths of microwaves
– Increases with decreasing wavelength – Decreases with increasing
conductivity, which is also influenced by moisture
– Is higher for smoother surfaces
9.2 Radar
vegetation
dry alluvium
glacier
[Al09]
• Problem-oriented quantitative analysis of radar images is difficult as it relies mostly on hardly comprehensible interdependencies
9.2 Radar
C-Band L-Band P-Band
http://www.ccrs.nrcan.gc.ca/resource/tutor/gsarcd/pdf/bas_intro_e.pdf
• ERS (European Remote Sensing Satellite)
– ERS-1: 1991-1999 – ERS-2: since 1995 – Envisat: since 2002 – Orbit:
• Sun synchronous
• 800 km altitude
• 98,5° inclination
• Orbital period 100 min
• Repeat circle 35 days
9.2 Radar
http://www.esa.int/esaEO/
GGGWBR8RVDC_index_0.html
http://www.raumfahrer.net/raumfahrt/envisat/ablauf.shtml
– Instruments
• SAR two modes of operation:
image mode and wave mode in combination with the wind
scatterometer (WS)
• WS, active microwaves to measure ocean surface wind speed and direction
• RA (Radar Altimeter); active:
Ku-Band (13.8 GHz) measures variations in the satellite’s
height above sea level and ice with an accuracy of a few
centimetres
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 791
9.2 Radar
http://ceos.cnes.fr:8100/.../ers/earonc00.htm
• GOME (Global Ozone Monitoring Experiment) Spectrometer (UV and VIS) provides information on ozone
• ATSR (Along-Track Scanning Radiometer) an Imaging Infrared Radiometer (IRR: 4 channels, temperature) and a passive
Microwave Sounder (MWS: 2 channels providing measurements of the total water content of the atmosphere within a 20 km footprint)
• PRARE (Precise Range and Range Rate Equipment), all-weather microwave ranging system designed to provide measurements used for highly precise orbit determination and geodetic
applications, such as movements of the Earth’s crust
• LRR (Laser-Retroreflector) passive optical device(IR) used as a target by ground-based laser ranging stations to determine the precise altitude
9.2 Radar
• ATSR image of Crete
9.2 Radar
http://earth.esa.int/earthimages/
• SAR image of Vorpommern
– Three images acquired in September 1991 were overlaid each in one of the primary colors
– Considerable changes of surface structure and moisture due to farming
9.2 Radar
http://earth.esa.int/earthimages/
• SAR image of the coast of Norway
– In situations with little wind many different features
appear on the ocean surface
• Linear elements:
current shear
• Black areas:
very light winds
• Linear features and internal waves:
currents alternated by the bottom topography, in shallow sea
9.2 Radar
http://earth.esa.int/earthimages/
• Comparison of the wavelengths used by different satellites
9.2 Recording Techniques
http://www.fe-lexikon.info/images/sp_sat.gif
• Light Detection and Ranging
• Active sensor
• Laser beams (UV, VIS near IR) to measure
– Distance – Speed
– Chemical composition and concentrations
• Often imprecisely called "laser-radar"
• LASER (Light Amplification by Stimulated Emission of Radiation)
– Device that emits an intense
narrow low-divergence beam of a specific wavelength
9.2 LIDAR
[SX08]
• Airborne Laserscanning
– The distance between the sensor and the surface to be measured is determined from the runtime of a light pulse
– By deflection of the laser beam and the forward movement of the aircraft a wide strip is scanned
9.2 LIDAR
elliptical scanning fibre scanner swiveling mirror
– Parameters
• Sampling rate
• Scan angle
• Scan frequency
• Altitude
• Aircraft speed
• Distance between the trajectories
– Recorded data
• Position
• Orientation of the aircraft
• Angle of every emitted beam
• Measured distance
9.2 LIDAR
http://www.fht-stuttgart.de/fbv/fbvweb/veranstaltungen/GIS- Day/Rueckblick/gis_day2004_guelch.pdf
Last return (DTM)
Primary return (DOM)
– One laser beam might be reflected at different heights, e.g. in presence of vegetation:
• Primary return: originate from the first objects a lidar pulse encounters, often the upper surface of a vegetation canopy
• Well suited to create a
digital object model (DOM)
9.2 LIDAR
http://www.fht-stuttgart.de/.../gis_day2004_guelch.pdf
• Secondary returns: lower
vegetation layers and the ground surface
• Last return provides data for a digital terrain model (DTM) if the vegetation is not too dense
9.2 LIDAR
http://publik.tuwien.ac.at/files/PubDat_166922.pdf
emitted pulse
first echo last echo
time time
time signal
strength
scrup terrain
discrete echo determination
full waveform digitisation signal
strength
signal strength
– Coordinates of the reflection points:
• Calculated from the
position and orientation of the sensor (by GPS and INS), the deflection angle of the beam and the distance between sensor and reflection point
– Result: 3D point set along the trajectory
9.2 LIDAR
http://www.photo.verm.tu-muenchen.de/.../EFE03_Kap23.pdf
– Advantages
• Uniform, dense acquisition of points
• Acquisition of height information for DOM (with vegetation), as well as for DTM (without vegetation)
• Accuracy in height between 50 and 15 cm in position1m
• Fast area-wide acquisition
• Active measuring method, nearly independent of illumination
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 803
9.2 LIDAR
http://www.fht-stuttgart.de/.../gis_day2004_guelch.pdf
– Disadvantages
• Arbitrary points, no structure elements (prominent terrain points, borders)
• Only single points, interpolation necessary
• Relatively noisy
9.2 LIDAR
http://www.fht-stuttgart.de/fbv/fbvweb/veranstaltungen/GIS-Day/Rueckblick/gis_day2004_guelch.pdf
• Comparison between topographic maps and remotely sensed images
9.3 Image Processing
Properties
Remotely sensed image Topographic map Mapping not true to scale,
image scales are only approximations, additional errors if terrain is uneven
Mapping true to scale, only minor changes due to generalization Mapping not positional accurate,
influenced by sensor alignment, grade, earth curvature, etc.
Mapping positional accurate, only minor changes due to generalization
No parallel projection Orthogonal parallel projection of the
earth‘ s surface on the map reference
plane
9.3 Image Processing
Content
Remotely sensed image Topographic map Communicating information in
images
Information coded by graphic symbols Content defined causally by
physical-chemical processes
Content defined conventionally, stipulated map symbols, explained in a legend
High information density, but irrelevant data included
Low information density, but all topographically relevant
Unlimited diversity of forms Limited number of map symbols
Snap shot, contains transient data Contains only topographically stable data content scale independent, no
selection
content scale dependent, reduction of information by generalization
Up to date , short production time Not up to date, long production time,
problem of revision
9.3 Image Processing
Readability and interpretation
Remotely sensed image Topographic map Varying image quality Uniform map quality
No readability, objects have to be interpreted
Objects are directly readable as they are represented by clearly defined symbols
Ambiguous, as interpretation depends on the interpreter
Unambiguous independent of the user
Real 3d impression possible, if third dimension by stereoscopy captured
No real 3d impression, third
dimension may only be coded by symbols
Interpretation scale dependent,
resolution determines if objects can be recognized
Readability scale independent,
granted by generalization
9.3 Image Processing
http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_18112004.pdf
• Geometric errors, distortions
– Inaccurate position and form of objects – Causes
• Recording techniques and system
• Relief
• Platform (instability, motion)
• Radiometric errors
– Faulty pixel values – Causes
• Atmospheric interference
• Topographical effects
• Technical defects (sensors, data transfer)
9.3 Image Processing
http://www.fas.org/irp/
• Goals of geometric corrections
– Represent objects in uniform scale and true geometry (system correction)
– Register overlapped images of a scene from different dates and views (image to image registration)
– Register the image to real world map coordinates (image to map registration)
• The planimetrically
corrected image
is called
orthophoto
9.3 Geometric Errors
[Al09]
aerial photo, uncorrected corrected → orthophoto
• Relief displacement
– Points above the chosen reference plane are moved radially away from the center
– Points below the chosen
reference plane are moved radially towards the center
– Radial displacement is
larger near the border
– Displacement diminishes
at the center
9.3 Geometric Errors in Photographic Systems
http://homepage.univie.ac.at/.../lba_fe_28102004.pdf
invisible space invisible space
reference plane
side view
9.3 Geometric Errors in Photographic Systems
[SX08]
• Varying scale
– Mapping scale changes with variations in terrain
– The scale of objects closer to the camera is larger than that of objects being further away
– The mapping of a rectangle that covers a terrace is not a rectangle
9.3 Geometric Errors in Photographic Systems
higher
lower Map:
constant scale
Aerial photo:
varying scale
terrace
http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_28102004.pdf
• Capturing a scene (image) takes a certain time
• During the recording time the earth rotates
eastward, so that the starting point of the last scan line is further west than that of the first line
• The displacement depends on the relative speed of the satellite and the earth rotation and also on the size of the image
• Example (Landsat 7):
– 33,8°S (Sidney)
– Image size: 185 km
→ Offset: 10,82 km (ca 6%)
9.3 Geometric Errors in Scanners
pixel
satellite motion↓
earth rotation →
http://ladamer.org/Feut/pdf/Kursbegleitung/dbv_vl/dbv_vl_kapitel3.pdf
• Whiskbroom scanner
– The distance between sensor and terrain increases towards the edges
– Size of scanning spots increases towards the edges
9.3 Geometric Errors in Scanners
[Al09]
scan direction flight
direction
↑
http://ladamer.org/Feut/pdf/Kursbegleitung/
dbv_vl/dbv_vl_kapitel3.pdf
– If the angular speed is constant, the image seems to be increasingly compressed towards the edges
– More elevated surfaces are perpendicular moved away from the flight direction
9.3 Geometric Errors in Scanners
[Al09]
http://homepage.univie.ac.at/.../lba_fe_28102004.pdf
• Image geometry depends on the depression angle and the terrain
• Oblique perspective (i.e. side-looking) leads to relief displacement
– The type and degree of relief displacement in the radar image is a function of the angle at which the radar beam hits the ground, i.e. it depends upon the local slope of the ground
9.3 Geometric Errors in Radar Systems
http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf
• Foreshortening
– Compression of those features in the scene which are tilted toward the radar
– Foreshortening effects are reduced with increasing incident angles
– Maximum when a steep slope
is orthogonal to the radar beam
9.3 Geometric Errors in Radar Systems
http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf
• Radar shadow
– Areas not illuminated by the radar
– Caused by either concave or convex relief features if the slope on the opposite side of the antenna is larger than the depression angle
– Typical in high relief terrain
– Occur in the down- range direction
– Most prominent
with large incidence angle illumination
9.3 Geometric Errors in Radar Systems
http://www.ccrs.nrcan.gc.ca/resource/tutor/gsarcd/pdf/bas_intro_e.pdf
• Layover
– Occurs when the reflected energy from the upper portion of a feature is received
before the return from its lower – The top of the feature will be
displaced, or “laid over” relative to its base
9.3 Geometric Errors in Radar Systems
http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf
• Instability of the platform (aircraft)
9.3 Geometric Errors
change of flight speed
pitching change of
altitude rolling
yawing
[Al09]
http://wdc.dlr.de/data_products/SURFACE/LCC/diplomarbeit_u_gessner_2005.pdf
• Model-based correction algorithm
– Develop a model for a given recording techniques and platform that considers all its
inherent causes for distortions
– Parameterize the model to fit the actual conditions under which the image was taken
– Suitable if the kind and cause of the distortion is known, as earth rotation, satellite orbit or positional parameters of the platform
9.3 Geometric Corrections
http://www.der-schweighofer.at/
• Mathematical function to map the positions of pixels on the coordinates of the same points in a map
– Independent of the sensor platform, commonly used – Uses ground control points i.e. features visible on the
image with known ground coordinates
– Assign to each pixel a new position in the reference grid – Involves the following steps:
I. Choice of a suitable function (mapping)
II. Coordinate transformation III. Resampling (interpolation)
9.3 Geometric Corrections
corrected image raw image
e
n e = f (c,r) r c
n = f (c,r)
• Example: Image to Image Geocorrection
– Matching the coordinate systems or column and row systems of two digital images
– One image acting as a reference image and the other as the image to be rectified
• Reverence Image
– Satellite imagery from GoogleMaps
• Input Image
– Mathematically distorted reference image
9.3 Image Rectification
• Reference Image
9.3 Image Rectification
• Mathematical distortions
– Central Projection – Change of altitude – Pitching
– Rolling – Yawing
9.3 Image Rectification
• Distorted image
9.3 Image Rectification
• Ground control point (GCP)
– Need to be accurately located on the image, e.g.
highway crossings, building corners
– Should be well distributed on the reference and the distorted image
– Number of necessary GCPs depends on the function used for rectification
– Can be used to determine the quality of the
rectification, if more GCPs than needed are defined
9.3 Image Rectification
• Reference image with ground
control points
9.3 Image Rectification
• Distorted image with ground
control points
9.3 Image Rectification
• Mapping functions
– Polynomials are often used
• Degree 1 needs 3 GCPs
• Degree 2 needs 6 GCPs
• Degree 3 needs 10 GCPs
9.3 Image Rectification
http://en.wikipedia.org/wiki/Polynomial
• Polynomial of degree 1
9.3 Image Rectification
• Polynomial of degree 2
9.3 Image Rectification
• Polynomial of degree 3
9.3 Image Rectification
• Reference image
9.3 Image Rectification
• Radiometric corrections
– Dark pixel subtraction
• Assumption: the minimum value of every channel is 0 → for each channel the smallest measured value is subtracted from every value as it has to be an atmospheric influence, very simplifying
– Radiance to reflectance conversion
• Correction of values by known reflection values for certain surface properties
– Atmospheric modeling
• Develop a complex model for the transfer of EM energy under the
atmospheric conditions (e.g. vapor content, ozone, temperature, etc.) to the time the image was taken
– Determining missing pixels or rows by interpolation
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 836
9.3 Image Processing
http://www.spacegrant.montana.edu/
• Emphasizing structures
– High pass filter
• Noise reduction (smoothing)
– Low pass filter
9.3 Image Enhancement
[Al09]
0 -1 0 -1 5 -1
0 -1 0
1 9 1 9
1 9 1 9
1 9 1 9 1 9 1 9 1 9
• Contrast enhancement
– Alters each pixel value in the old image to produce a new set of values that
exploits the full range of values – E.g. linear stretching
• Chose a new minimum and maximum value
• Intermediate values are scaled proportionally
g‘(x,y) = (g(x,y)+ c2 )⋅ c1 with c1 =255/[max(g(x,y)) – min(g(x,y))], c2 = -min(g(x,y))
9.3 Image Enhancement
0 0 255
http://ivvgeo.uni-muenster.de/Vorlesung/FE_Script/3_2.html 255
VV
V V
• Assignment of objects, features, or areas to
classes based on their appearance on the imagery
• Distinction between 3 levels of confidence
– Detection: determination of the presence or absence of a feature
– Recognition: object can be assigned an identity in a general class or category
– Identification: object or feature can be assigned to a very specific class
9.4 Thematic Classification
• Eight elements of image interpretation
– Image tone
• Lightness or darkness of a region within an image
• Refers ultimately to the brightness of an area of ground as portrayed by the film
• Influenced by vignetting, i.e. the image becomes darker near the edges
9.4 Thematic Classification
[Ca07]
– Image texture
• Apparent roughness or smoothness of an image region
• Caused by the pattern of highlighted and shadowed areas created when an irregular surface is illuminated from an oblique angle
9.4 Thematic Classification
[Ca07]
– Shadow
• May reveal characteristics of its size or shape that would not be obvious from the overhead view alone
• Important clue in the interpretation of individual objects
9.4 Thematic Classification
[Ca07]
– Pattern
• Arrangement of individual objects into distinctive recurring forms
• Usually follows from a functional relationship between the individual features that compose the pattern
9.4 Thematic Classification
[Ca07]
– Association
• Specifies the occurrence of certain objects or features, without a strict spatial arrangement
• Identification of a class implies that objects of another class are likely to be found nearby
– Site
• Refers to topographic position
• E.g. sewage treatment facilities are positioned at low topographic sites near streams or rivers
9.4 Thematic Classification
http://maps.google.de/
– Shape
• Obvious clue to the identity of objects
• Often shape alone might be sufficient to provide clear identification
– Size
• Relative size of an object in relation to other objects on the image provides the interpreter with an intuitive notion of its scale and resolution
• Can be measured, permit derivation of quantitative information
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 845
9.4 Thematic Classification
http://maps.google.de/
• Classification key
– Provide a pictorial, exemplary representation of the examined areas or objects
9.4 Thematic Classification
http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_02122004.pdf
spruce
silver fir
douglas fir beech
oak pine
9.4 Thematic Classification
http://homepage.univie.ac.at/thomas.engleder/index_20072008.html
• Multispectral classification
– Ideally every class is defined by a typical multispectral signature, caused by a statistical distribution of the pixels of each class → Examination of the pixels of a multispectral image by mathematical algorithms
• With regard to their homogeneity
• Spatial distribution
– Two types of classifiers
• Unsupervised, autonomous
• Supervised, interactive
9.4 Thematic Classification
http://www.gepdata.ch/
– After parameterization the multispectral feature space may be divided
into
• Primary feature spaces (reflectance, temperature etc.)
• Linear transformed feature spaces
9.4 Thematic Classification
http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_25112004.pdf
• Unsupervised classification
– Assignment of pixels to spectral classes without prior knowledge of the existence or names of these classes – Cluster-algorithms to define spectral classes
– Collateral information is used to define thematic classes a posteriori, e.g.:
• Terrain surveys
• Spectral measurements
• Maps
– Particularly suited to determine spectral properties of relevant thematic classes
9.4 Thematic Classification
http://2.bp.blogspot.com/
soil vegetation
water
control limits Band 5
Band 7
• Supervised classification
– Analytical method to extract quantitative information – Assumption: every class in the feature space can be
described by a probability distribution
• Distribution assigns to every pixel the probability that it belongs to the class in whose area it is located
• Usually Gaussian distribution
• Number of variables
= number of channels
9.4 Thematic Classification
http://ladamer.org/Feut/pdf/Kursbegleitung/dbv_vl/dbv_vl_kapitel8.pdf
• Physical basics
– Electromagnetic radiation – Orbits
• Recording techniques
– Photographic systems (Aerial camera, Cosmos) – Whiskbroom scanner(Landsat)
– Pushbroom scanner (SPOT) – Radar (ERS)
– LIDAR (Airborne Laserscanning)
9.5 Summary
• Image processing
– Comparison between remotely sensed images and topographic maps
– Causes of geometric errors – Image rectification
– Image enhancement
• Thematic classification
– Visual interpretation
– Quantitative image analysis
9.5 Summary
9.5 Summary
GIS
objects