Transcript
9 Remote Sensing 9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary
http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf 704
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9 Remote Sensing • 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9 Remote Sensing • 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
www1.tudarmstadt.de
http://de.wikipedia.org/
www.photolib.noaa.gov
http://tu-dresden.de/ Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
706
9 Remote Sensing – Hydrographic survey • Sounding
– Thematic survey
• Map digitization • Survey by different sources – Statistics – Ministerial data – Technical literature
http://tu-dresden.de/die_ tu_dresden/…/papers/fuhrland.pdf
• Aerial survey and survey by remote sensing Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
707
9 Remote Sensing • 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 http://www.etsu.edu/cas/geosciences/ aircraft or spacecraft – That serves for the observation of the surface of the earth including all objects thereon, the oceans or the atmosphere Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9 Remote Sensing • 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
http://www.gisdevelopment.net/…/mm063d_155.htm Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
www.maps.google.de 709
9 Remote Sensing • System Characteristics – Recording techniques • Radiometric resolution • Geometric resolution
– Platform • • • •
Kind of platform Altitude Orbit Period
– Mission
www.atmos.albany.edu/deas/ atmclasses/atm335/history.pdf
www.irs.uni-stuttgart.de
• Temporal coverage • Spatial coverage Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics • 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 electrical field E
λ: wavelength
distance
magnetic field
M c
http://www.fe-lexikon.info/images/ ElektromagnetischeWelle.jpg
ν: frequency
speed of light
number of cycles that passes a certain point per second
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics • Electromagnetic spectrum – The electromagnetic spectrum is the range of all possible frequencies of electromagnetic radiation
http://de.wikipedia.org/wiki/Bild:Elektro-magnetisches_Spektrum.JPG
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics • Behavior of electromagnetic waves at interfaces Transmission
Scattering
Reflection
Absorption
Emission
Transmission + Reflection + Absorption = 1 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics sensor solar radiation
sky radiation
received signal
atmospheric absorption and scattering
reflection at the surface absorption and reflection in the water (suspended particles)
scattered light
scattering at the surface
water depth
reflection at the ground
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
[Al07] 714
9.1 Physical Basics – The albedo (lat. albedo = „whiteness“), reflectivity • The extent to which an object diffusely reflects light from the sun
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
715
9.1 Physical Basics – Albedo depends on wavelength • There is a strong difference between visual and infrared albedos of natural materials
[Al07] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
716
9.1 Physical Basics • 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
www.eduspace.esa.int/eduspac e/.../images/03.jpg 717
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.1 Physical Basics • 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
http://mynasadata.larc.nasa.gov/images/BB_illustration2.jpg Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics • 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
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, 0,92-0,97 dense, short Sands, depending on water moisture
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
0,88-0,985
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9.1 Physical Basics • 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!)
www.geographie.ruhr-uni-bochum.de/agklima/vorlesung/strahlung/spektrum-atmosphaere.jpg Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics – 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 http://altmed.creighton.edu/ • 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) Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics – Far infrared (thermal energy) 3 - 1000 μm (usually : 8 - 14 μm) • Radiation emitted by the earth • Nearly no atmospheric influences (but clouds are impermeable, CO2 as well: greenhouse effect is measurable!) • Applicable day and night • Measurements beneath the surface to some extent (pipelines and leaks...) http://www.qualitas1998.net/paul/ • Applications for which the temperature and its change are important, e.g. sea temperature, thermal properties of stone, tectonics Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics • 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
http://www.icefloe.net/hly0503/
– Passive microwaves 1 - 300 mm
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9.1 Physical Basics – Active microwaves (radar) 1 - 300 mm
http://www.wetteronline.de/
• 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics • Orbits – Altitude, orbital period, – Apogee/perigee • Greatest/least distance from the earth
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
– Inclination • Angular distance of the orbital plane from the equator
www.satellitentracking.de/txt/ 04_satellitenbahnen.html Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics – 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 http://www.tobedetermined.org/ Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.1 Physical Basics – Geosynchronous/geostationary Orbit (GSO)
– Sun Synchronous Orbit (SSO) or Polar Earth Orbit (PEO)
http://cimss.ssec.wisc.edu/sage/
• 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
• 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
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9.2 Recording Techniques • Passive systems: photography, scanner (optic, mechanical, optoelectronic) • Active systems: radar sensors active systems
T/R
reflected artificial radiation
passive systems
R
R
thermal radiation
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
reflected solar radiation 728
9.2 Photographic 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
[Al07] 729
9.2 Photographic Systems – 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).
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
[Al07] 730
9.2 Photographic Systems • Example: aerial photo of Braunschweig – Altitude approximately 1600 m – Ground resolution 10 cm – Color reversal film – Central projection – 21. April 2005
www.braunschweig.de/.../luftbilder.html Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Photographic Systems • Example: Cosmos with KVR 1000 Camera – Russian spy satellite – Polar, sun-synchronous – Altitude 200km – Ground resolution 2m – Black and white film – Durability 45 days
http://www.spotimage.fr/web/en/186-kvr-1000.php Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Photographic Systems • Disadvantages – Difficult radiometric calibration – Low spectral bandwidth – Analog data
• Advantages – Relatively cheap – High resolution – „Spontaneous“ recording of areas http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Whisk Broom Scanner • Opto-mechanical 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Whisk Broom Scanner sensor platform aperture angle
altitude
instantaneous field of view IFOV: pixel flight direction scan direction a: geometric resolution > ground segment s: swath width http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
735
9.2 Whisk Broom Scanner • 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 beam splitter optical system telescope
rotating mirror
motor
dispersion prism electronics amplifier, converter
beam splitter interference grid
radiation
photodetectors
streamer magnetic tape HDDT, CCT
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf 736 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.2 Whisk Broom Scanner • 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 http://landsat.gsfc.nasa.gov/images/archive/c0005.html Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Whisk Broom Scanner • 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
4, 5
1-3
6, 7 http://de.wikipedia.org/wiki/Landsat Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Whisk Broom Scanner – 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) ground trace for Landsat1-3 for one day Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
[Al07] 739
9.2 Whisk Broom Scanner LANDSAT 4,5 (1-3) sensor Multispectral Scanner (MSS) pixel size 79 x 79 m² spectral 1 (4) 0,50 - 0,60 µm, channels 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
thermal channel panchromatic channel
LANDSAT 4,5 Thematic Mapper (TM) 30 x 30 m² 1 0,45 - 0,52 µm, bluegreen 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 6 10,4 - 12,5 µm (120 x 120 m²)
LANDSAT 7 Enhanced Thematic Mapper Plus (ETM+) 30 x 30 m² 1 0,45 - 0,52 µm, bluegreen 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 6 10,4 - 12,5 µm (60 x 60 m²) 8 0,52 - 0,90 µm (15 x 15 m²)
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Whisk Broom Scanner – Typical combination of channels
green
0,5-0,6 μm
false colour composite
red
0,6-0,7 μm
infrared
0,8-0,9 μm
true colour composite http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Whisk Broom Scanner
http://landsat.gsfc.nasa.gov/images/lg_jpg/f0012_77-89-06.jpg 742
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.2 Push Broom Scanner • Optoelectronical scanner • Employs a linear array of solid semiconductive 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Push Broom Scanner sensor platform : aperture angle
altitude
scan direction flight direction
a: geometric resolution > ground segment s: swath width http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
744
9.2 Push Broom Scanner • 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 CCD sensors focal distance
sample mirror
optical system radiation
lens
aperture angle http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
745
9.2 Push Broom Scanner • Spot (Systeme Probatoire d'Observation de la 1-3 Terre) – French satellite series • • • • •
Spot-1: 1986-1990 Spot-2: since 1990 Spot-3: 1993-1997 Spot-4: since 1998 Spot-5: since 2002
4
http://www.uni-potsdam.de/... /febasis/febasis06_04-1206.pdf
5
– Two identical parallel sensors that can be operated independently of one another http://www.fe-lexikon.info/images/Spot5.jpg 746
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.2 Push Broom Scanner – Pivoting of the sensors can be employed for stereoscopy and also for a higher repeat circle – Sensors are operated from the ground stations
angled view
http://www.terraengine.com/Dgroundstation.cfm
nadirlooking
http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
747
9.2 Push Broom Scanner – Orbit • • • •
Sun synchronous Altitude: 822 km Inclination 98,7° Orbital period 101,4 min → approximately 14 circulations per day http://spot5.cnes.fr/.../35.htm
geometric resolution
SPOT 1-3 HRV (Instrument Haute Résolution Visible) 20 m (XS), 10 m (PN)
SPOT 4 HRVIR (High Resolution Visible and Infrared) 20 m (XS), 10 m (P)
radiometric resolution
0,5-0,9 μm: 3 VIS, 1 NIR
0,5-1,75 μm: 3 VIS, 1 NIR, 1 MIR
sensor
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
SPOT 5 HRG (High Resolution Geometric) 10 m (VIS, NIR), 2,5/5 m (PAN), 20 m (MIR) 0,45-1,75 μm: 2 VIS, 2 NIR, 1 MIR 748
9.2 Push Broom Scanner Spot-1 HRV XS-Modus
Spot-1 HRV P-Modus
Detroit(USA), false colour composite, resolution 30 m
San Diego(USA), panchromatic, resolution 20 m http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf 749
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.2 Push Broom Scanner Spot-5 HRG XS-Modus: stereo
Dead sea (Jordan), panchromatic, 11/2002 resolution 2,5 m http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Radar • 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 [LKC08] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
751
9.2 Radar • 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
http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
752
9.2 Radar • 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 θd – Pulse length – Wavelength is divided into bands 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
http://ladamer.org/.../FE1-06-Radar.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
753
9.2 Radar • Azimuth resolution AR depends on beam width(β) and the ground range distance (GR)
β [LKC08]
B
GR1
R1
A
B
GR2
R2 A
→ Azimuth resolution is better in the near range Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
754
9.2 Radar • 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
[LKC08]
→ Better ground range resolution in the far range Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
755
9.2 Radar • 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 http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Radar • 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 http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
757
9.2 Radar • Doppler-effect
• Physical antenna as small as possible • Azimuth resolution independent of GR and λ
synthetic aperture
– Approaching → increase in frequency – Receding → decrease in frequency
radar pulse with frequency v2
object frequency v2
v1 – v2 > 0 v3 – v2 < 0 http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
758
9.2 Radar • Comparison of the resolution between systems with real (a) and synthetic (b) aperture
http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
759
9.2 Radar • Interactions between radar signals and materials very complex as it depends on: – Wavelength – Incidence angle – Electrical properties – Moisture – Surface property
http://www.meteo.physik.uni-muenchen.de/.../fe_boden_micro.html Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
760
9.2 Radar • Penetration depths of microwaves – Increases with decreasing wavelength – Decreases with increasing conductivity, which is also influenced by moisture vegetation – Is higher for smoother surfaces dry alluvium
glacier [Al07] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
761
9.2 Radar • Problem-oriented quantitative analysis of radar images is difficult as it relies mostly on hardly comprehensible interdependencies
C-Band
L-Band
P-Band
http://www.ccrs.nrcan.gc.ca/resource/tutor/gsarcd/pdf/bas_intro_e.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Radar • 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
http://www.esa.int/esaEO/ GGGWBR8RVDC_index_0.html
http://www.raumfahrer.net/raumfahrt/envisat/ablauf.shtml 763
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.2 Radar – 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 http://ceos.cnes.fr:8100/.../ers/earonc00.htm Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Radar • 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Radar • ATSR image of Crete
http://earth.esa.int/earthimages/ Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
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9.2 Radar • 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
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
http://earth.esa.int/earthimages/ 767
9.2 Radar • 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
http://earth.esa.int/earthimages/ 768
9.2 Recording Techniques • Comparison of the wavelengths used by different satellites
http://www.fe-lexikon.info/images/sp_sat.gif Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
769
9.2 LIDAR • 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 [SX08] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
770
9.2 LIDAR • 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
elliptical scanning
fibre scanner
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
swiveling mirror 771
9.2 LIDAR – 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 http://www.fht-stuttgart.de/fbv/fbvweb/veranstaltungen/GISDay/Rueckblick/gis_day2004_guelch.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
772
9.2 LIDAR – 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)
http://www.fht-stuttgart.de/.../gis_day2004_guelch.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
773
9.2 LIDAR • 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 emitted signal pulse strength
first echo
last echo
time
signal strength scrup
signal strength
discrete echo determination
full waveform digitisation
terrain
time
time
http://publik.tuwien.ac.at/files/PubDat_166922.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
774
9.2 LIDAR – 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 http://www.photo.verm.tu-muenchen.de/.../EFE03_Kap23.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
775
9.2 LIDAR – 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
http://www.fht-stuttgart.de/.../gis_day2004_guelch.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
776
9.2 LIDAR – Disadvantages • Arbitrary points, no structure elements (prominent terrain points, borders) • Only single points, interpolation necessary • Relatively noisy
http://www.fht-stuttgart.de/fbv/fbvweb/veranstaltungen/GIS-Day/Rueckblick/gis_day2004_guelch.pdf 777
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.3 Image Processing • Comparison between topographic maps and remotely sensed images Properties Remotely sensed image
Topographic map
Mapping not true to scale, Mapping true to scale, only minor image scales are only approximations, changes due to generalization additional errors if terrain is uneven 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
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
778
9.3 Image Processing Content Remotely sensed image
Topographic map
Communicating information in images Content defined causally by physical-chemical processes High information density, but irrelevant data included Unlimited diversity of forms Snap shot, contains transient data
Information coded by graphic symbols
content scale independent, no selection Up to date , short production time
content scale dependent, reduction of information by generalization Not up to date, long production time, problem of revision
Content defined conventionally, stipulated map symbols, explained in a legend Low information density, but all topographically relevant Limited number of map symbols Contains only topographically stable data
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
779
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
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
780
9.3 Image Processing
http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_18112004.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
781
9.3 Image Processing • 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) Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
http://www.fas.org/irp/
782
9.3 Geometric Errors • 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
aerial photo, uncorrected
corrected → orthophoto
[Al07] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
783
9.3 Geometric Errors in Photographic Systems
• 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 reference plane larger near the border invisible space invisible space – Displacement diminishes at the center side view http://homepage.univie.ac.at/.../lba_fe_28102004.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
784
9.3 Geometric Errors in Photographic Systems
[SX08] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
785
9.3 Geometric Errors in Photographic Systems
• 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 Map: Aerial photo: constant scale
varying scale higher terrace
lower
http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_28102004.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
786
9.3 Geometric Errors in Scanners • 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): earth rotation → satellite – 33,8°S (Sidney) – Image size: 185 km → Offset: 10,82 km (ca 6%)
motion↓ pixel
http://ladamer.org/Feut/pdf/Kursbegleitung/dbv_vl/dbv_vl_kapitel3.pdf 787
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.3 Geometric Errors in Scanners • Whiskbroom scanner
flight direction ↑
– The distance between sensor and terrain increases towards the edges – Size of scanning spots increases towards the edges
[Al07]
scan direction
http://ladamer.org/Feut/pdf/Kursbegleitung/ dbv_vl/dbv_vl_kapitel3.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
788
9.3 Geometric Errors in Scanners – 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
http://homepage.univie.ac.at/.../lba_fe_28102004.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
[Al07] 789
9.3 Geometric Errors in Radar Systems
• 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
http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf 790
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.3 Geometric Errors in Radar Systems
• 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
http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
791
9.3 Geometric Errors in Radar Systems • 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 downrange direction – Most prominent with large incidence angle illumination http://www.ccrs.nrcan.gc.ca/resource/tutor/gsarcd/pdf/bas_intro_e.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
792
9.3 Geometric Errors in Radar Systems
• 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
http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf 793
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.3 Geometric Errors • Instability of the platform (aircraft) yawing
rolling
pitching
change of altitude
change of flight speed http://wdc.dlr.de/data_products/SURFACE/LCC/diplomarbeit_u_gessner_2005.pdf
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
[Al07]
794
9.3 Geometric Corrections • 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
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
795
9.3 Geometric Corrections • 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: e = f (c,r) r c n I.
Choice of a suitable function (mapping) II. Coordinate transformation III. Resampling (interpolation)
n = f (c,r)
e
corrected image
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
raw image
796
9.3 Image Processing • 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
797
9.3 Image Enhancement • Emphasizing structures – High pass filter 0
-1
0
-1
5
-1
0
-1
0
• Noise reduction (smoothing) – Low pass filter 19 19 19 19 19 19 19 19 19 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
[Al07] 798
9.3 Image Enhancement • 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)⋅ c1 + c2 with c1 =255/[max(g(x,y)) – min(g(x,y))], c2 = -min(g(x,y)) 255
0 0
http://ivvgeo.uni-muenster.de/Vorlesung/FE_Script/3_2.html Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
255 799
9.4 Thematic Classification • 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
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
800
8.4 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
[Ca07] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
801
8.4 Thematic Classification – 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
[Ca07] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
802
9.4 Thematic Classification – 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
[Ca07] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
803
9.4 Thematic Classification – Pattern • Arrangement of individual objects into distinctive recurring forms • Usually follows from a functional relationship between the individual features that compose the pattern
[Ca07] Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
804
9.4 Thematic Classification – 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
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
805
9.4 Thematic Classification – 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
806
9.4 Thematic Classification • Classification key – Provide a pictorial, exemplary representation of the examined areas or objects
spruce
pine
douglas fir
silver fir
beech
oak http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_02122004.pdf 807
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
9.4 Thematic Classification
http://homepage.univie.ac.at/thomas.engleder/index_20072008.html Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
808
9.4 Thematic Classification • 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
809
9.4 Thematic Classification – After parameterization the multispectral feature space may be divided into • Primary feature spaces (reflectance, temperature etc.) • Linear transformed feature spaces
http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_25112004.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
810
9.4 Thematic Classification • 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 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
811
9.4 Thematic Classification • 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 Band 5 belongs to the class in whose Band area it is located 7 • Usually Gaussian distribution • Number of variables = number of channels
water
control limits vegetation
soil http://ladamer.org/Feut/pdf/Kursbegleitung/dbv_vl/dbv_vl_kapitel8.pdf Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
812
9.6 Summary • Physical basics – Electromagnetic radiation – Orbits
• Recording techniques – Photographic systems (Aerial camera, Cosmos) – Whiskbroom scanner(Landsat) – Pushbroom scanner (SPOT) – Radar (ERS) – LIDAR (Airborne Laserscanning) Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
813
9.6 Summary • Image processing – Comparison between remotely sensed images and topographic maps – Causes of geometric errors – Image enhancement
• Thematic classification – Visual interpretation – Quantitative image analysis
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
814
9.6 Summary collect
GIS
display
analyse
physics
manage
remote sensing
objects
classification
recording techniques
image enhancements / corrections
Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig
815
