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9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 724 9 Remote Sensing http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf
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Page 1: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

9.1 Physical Basics

9.2 Recording Techniques

9.3 Image Processing

9.4 Thematic Classification

9.5 Summary

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 724

9 Remote Sensing

http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf

Page 2: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 725

9 Remote Sensing

Visualization, Cartography

Spatial Data Management

Collection of Spatial Data

Analysis, Modelling

Functional Components Structural Components

Page 3: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 726

9 Remote Sensing

http://de.wikipedia.org/

www1.tu- darmstadt.de

www.photolib.noaa.gov

http://tu-dresden.de/

Page 4: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Hydrographic survey

• Sounding

– Thematic survey

• Map digitization

• Survey by different sources

– Statistics

– Ministerial data

– Technical literature

• Aerial survey and survey by remote sensing

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 727

9 Remote Sensing

http://tu-dresden.de/die_ tu_dresden/…/papers/fuhrland.pdf

Page 5: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 728

9 Remote Sensing

http://www.etsu.edu/cas/geosciences/

Page 6: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 729

9 Remote Sensing

http://www.gisdevelopment.net/…/mm063d_155.htm www.maps.google.de

Page 7: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• System Characteristics

– Recording techniques • Radiometric resolution

• Geometric resolution

– Platform • Kind of platform

• Altitude

• Orbit

• Period

– Mission

• Temporal coverage

• Spatial coverage

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 730

9 Remote Sensing

http://www.wdr.de/tv/quarks/ http://www.dlr.de/

http://www.chip.de/

http://www.maritime-technik.de/

Page 8: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 731

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

Page 9: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Electromagnetic

spectrum

– The electromagnetic

spectrum is the range

of all possible

frequencies of

electromagnetic

radiation

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 732

9.1 Physical Basics

htt

p:/

/en

.wik

iped

ia.o

rg/

Page 10: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Behavior of electromagnetic waves at interfaces

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 733

9.1 Physical Basics

Reflection

Emission Absorption

Transmission

Scattering

Transmission + Reflection + Absorption = 1

Page 11: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 734

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

Page 12: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 735

9.1 Physical Basics

Page 13: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Albedo depends on wavelength

• There is a strong difference between visual and infrared

albedos of natural materials

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 736

9.1 Physical Basics

[Al09]

Page 14: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 737

9.1 Physical Basics

www.eduspace.esa.int/eduspac e/.../images/03.jpg

Page 15: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 738

9.1 Physical Basics

http://mynasadata.larc.nasa.gov/images/BB_illustration2.jpg

Page 16: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 739

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

Page 17: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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!)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 740

9.1 Physical Basics

www.geographie.ruhr-uni-bochum.de/agklima/vorlesung/strahlung/spektrum-atmosphaere.jpg

Page 18: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 741

9.1 Physical Basics

http://altmed.creighton.edu/

Page 19: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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...)

• 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 742

9.1 Physical Basics

http://www.qualitas1998.net/paul/

Page 20: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 743

9.1 Physical Basics

htt

p:/

/ww

w.ic

eflo

e.n

et/h

ly0

50

3/

Page 21: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 744

9.1 Physical Basics

htt

p:/

/ww

w.w

ette

ron

line.

de/

Page 22: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Orbits

– Altitude, orbital period,

– Apogee/perigee

• Greatest/least distance from the earth

– Inclination

• Angular distance of the orbital plane from the equator

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 745

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

gRv 0

www.satellitentracking.de/txt/ 04_satellitenbahnen.html

Page 23: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 746

9.1 Physical Basics

http://www.tobedetermined.org/

Page 24: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 747

9.1 Physical Basics

htt

p:/

/cim

ss.s

sec.

wis

c.ed

u/s

age/

Page 25: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– To scale

representation

of the Earth,

LEO, and MEO

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 748

9.1 Physical Basics

MEO

Page 26: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Passive systems: photography, scanner

(optomechanical, optoelectronical)

• Active systems: radar sensors

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 749

9.2 Recording Techniques

reflected solar radiation

thermal radiation

reflected artificial radiation

R R T/R

passive systems active systems

Page 27: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 750

9.2 Photographic Systems

[Al09]

Page 28: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 751

9.2 Photographic Systems

[Al09]

Page 29: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Example: aerial photo of Braunschweig

– Altitude approximately 1600 m

– Ground resolution 10 cm

– Color reversal film

– Central projection

– 21. April 2005

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 752

9.2 Photographic Systems

www.braunschweig.de/.../luftbilder.html

Page 30: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Example: Cosmos with KVR 1000 Camera

– Russian spy satellite

– Polar, sun-synchronous

– Altitude 200km

– Ground resolution 2m

– Black and white film

– Durability 45 days

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 753

9.2 Photographic Systems

http://www.spotimage.fr/web/en/186-kvr-1000.php

Page 31: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Disadvantages

– Difficult radiometric calibration

– Low spectral bandwidth

– Analog data

• Advantages

– Relatively cheap

– High resolution

– „Spontaneous“

recording of areas

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 754

9.2 Photographic Systems

http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf

Page 32: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 755

9.2 Whisk Broom Scanner

http://www.mikroelektronik.fraunhofer.de/

Page 33: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 756

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

Page 34: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 757

9.2 Whisk Broom Scanner

http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf

Page 35: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 758

9.2 Whisk Broom Scanner

http://landsat.gsfc.nasa.gov/images/archive/c0005.html

Page 36: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 759

9.2 Whisk Broom Scanner

http://de.wikipedia.org/wiki/Landsat

1-3

6, 7

4, 5

Page 37: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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) Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 760

9.2 Whisk Broom Scanner

ground trace for Landsat1-3 for one day [Al09]

Page 38: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

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)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 761

9.2 Whisk Broom Scanner

Page 39: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Typical combination of channels

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 762

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

Page 40: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 763

9.2 Whisk Broom Scanner

http://landsat.gsfc.nasa.gov/images/lg_jpg/f0012_77-89-06.jpg

Page 41: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 764

9.2 Push Broom Scanner

http://www.fotos.docoer-dig.de/

Page 42: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 765

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

Page 43: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 766

9.2 Push Broom Scanner

http://www.uni-potsdam.de/.../febasis/febasis06_04-1206.pdf

Page 44: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 767

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

Page 45: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 768

9.2 Push Broom Scanner

http://www.terraengine.com/Dgroundstation.cfm

Page 46: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Orbit

• Sun synchronous

• Altitude: 822 km

• Inclination 98,7°

• Orbital period 101,4 min

→ approximately 14 circulations per day

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 769

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

Page 47: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 770

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

Page 48: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spot-5 HRG XS-Modus: stereo

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 771

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

Page 49: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 772

9.2 Radar

[LKC08]

Page 50: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 773

9.2 Radar

http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf

Page 51: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 5 bands

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 774

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

Page 52: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

B

GR2

GR1

R2

R1 A

A

B β

• 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 775

9.2 Radar

[LKC08]

GRARL

and

L: antenna length

λ: wavelength where

Page 53: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 776

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

cos2

cGRR

[LKC08]

Page 54: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 777

9.2 Radar

http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf

Page 55: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 778

9.2 Radar

http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf

Page 56: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Doppler-effect

– Approaching → increase in

frequency

– Receding → decrease in

frequency

• Physical antenna as small

as possible

• Azimuth resolution

independent of GR and λ

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 779

9.2 Radar

http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf

syn

thet

ic a

pe

rtu

re

radar pulse with frequency v2

frequency v2

object

v1 – v2 > 0 v3 – v2 < 0

Page 57: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Comparison of the resolution between systems

with real (a) and synthetic (b) aperture

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 780

9.2 Radar

http://ladamer.org/Feut/studium/fe1/FE1-06-Radar.pdf

Page 58: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Interactions between radar signals and materials

very complex as it depends on:

– Wavelength

– Incidence angle

– Electrical properties

– Moisture

– Surface property

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 781

9.2 Radar

http://www.meteo.physik.uni-muenchen.de/.../fe_boden_micro.html

Page 59: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Penetration depths of microwaves

– Increases with decreasing wavelength

– Decreases with increasing

conductivity, which is also

influenced by moisture

– Is higher for smoother

surfaces

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 782

9.2 Radar

vegetation

dry alluvium

glacier

[Al09]

Page 60: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Problem-oriented quantitative analysis of radar

images is difficult as it relies mostly on hardly

comprehensible interdependencies

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 783

9.2 Radar

C-Band L-Band P-Band http://www.ccrs.nrcan.gc.ca/resource/tutor/gsarcd/pdf/bas_intro_e.pdf

Page 61: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 784

9.2 Radar

http://www.esa.int/esaEO/ GGGWBR8RVDC_index_0.html

http://www.raumfahrer.net/raumfahrt/envisat/ablauf.shtml

Page 62: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 785

9.2 Radar

http://ceos.cnes.fr:8100/.../ers/earonc00.htm

Page 63: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 786

9.2 Radar

Page 64: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• ATSR image of Crete

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 787

9.2 Radar

http://earth.esa.int/earthimages/

Page 65: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 788

9.2 Radar

http://earth.esa.int/earthimages/

Page 66: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 789

9.2 Radar

http://earth.esa.int/earthimages/

Page 67: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Comparison of the wavelengths used by different

satellites

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 790

9.2 Recording Techniques

http://www.fe-lexikon.info/images/sp_sat.gif

Page 68: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 791

9.2 LIDAR

[SX08]

Page 69: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 792

9.2 LIDAR

elliptical scanning swiveling mirror fibre scanner

Page 70: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 793

9.2 LIDAR

http://www.fht-stuttgart.de/fbv/fbvweb/veranstaltungen/GIS-Day/Rueckblick/gis_day2004_guelch.pdf

Page 71: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

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)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 794

9.2 LIDAR

http://www.fht-stuttgart.de/.../gis_day2004_guelch.pdf

Page 72: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 795

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

Page 73: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 796

9.2 LIDAR

http://www.photo.verm.tu-muenchen.de/.../EFE03_Kap23.pdf

Page 74: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 797

9.2 LIDAR

http://www.fht-stuttgart.de/.../gis_day2004_guelch.pdf

Page 75: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Disadvantages

• Arbitrary points, no structure elements (prominent terrain

points, borders)

• Only single points, interpolation

necessary

• Relatively noisy

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 798

9.2 LIDAR

http://www.fht-stuttgart.de/fbv/fbvweb/veranstaltungen/GIS-Day/Rueckblick/gis_day2004_guelch.pdf

Page 76: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Reconstruction of buildings from airborne LIDAR

point clouds is still subject of research

• Building polyhedral models by intersecting detected planes

• Bottom-up reconstruction using a given number of building

parts

• Top-down

statistical

reconstruction

of building roofs

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 799

9.2 LIDAR

[HBS11]

Page 77: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Comparison between topographic maps and remotely sensed images

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 800

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

Page 78: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 801

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

Page 79: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 802

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

Page 80: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 803

9.3 Image Processing

http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_18112004.pdf

Page 81: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 804

9.3 Image Processing

http://www.fas.org/irp/

Page 82: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 805

9.3 Geometric Errors

[Al09]

aerial photo, uncorrected corrected → orthophoto

Page 83: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 806

9.3 Geometric Errors in Photographic Systems

http://homepage.univie.ac.at/.../lba_fe_28102004.pdf

invisible space invisible space

reference plane

side view

Page 84: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 807

9.3 Geometric Errors in Photographic Systems

[SX08]

Page 85: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 808

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

Page 86: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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%)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 809

9.3 Geometric Errors in Scanners

pixel

satellite motion↓

earth rotation →

http://ladamer.org/Feut/pdf/Kursbegleitung/dbv_vl/dbv_vl_kapitel3.pdf

Page 87: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Whiskbroom scanner

– The distance between sensor and

terrain increases towards the edges

– Size of scanning spots increases towards

the edges

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 810

9.3 Geometric Errors in Scanners

[Al09]

scan direction

flight direction

http://ladamer.org/Feut/pdf/Kursbegleitung/ dbv_vl/dbv_vl_kapitel3.pdf

Page 88: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 811

9.3 Geometric Errors in Scanners

[Al09] http://homepage.univie.ac.at/.../lba_fe_28102004.pdf

Page 89: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 812

9.3 Geometric Errors in Radar Systems

Page 90: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Foreshortening

– Compression of those features in the scene which are

tilted toward the radar

– Foreshortening effects are

reduced with increasing

incident

angles

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 813

9.3 Geometric Errors in Radar Systems

http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf http://www.geoinformation.net/

Page 91: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 814

9.3 Geometric Errors in Radar Systems

http://www.ccrs.nrcan.gc.ca/resource/tutor/gsarcd/pdf/bas_intro_e.pdf

Page 92: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 815

9.3 Geometric Errors in Radar Systems

http://www.ccrs.nrcan.gc.ca/.../bas_intro_e.pdf http://history.nasa.gov/

Page 93: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Instability of the platform (aircraft)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 816

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

Page 94: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 817

9.3 Geometric Corrections

htt

p:/

/ww

w.d

er-s

chw

eigh

ofe

r.at

/

Page 95: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 818

9.3 Geometric Corrections

corrected image raw image

e

n c r e = f (c,r)

n = f (c,r)

Page 96: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

819 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 97: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Reference

Image

9.3 Image Rectification

820 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 98: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Mathematical distortions

– Central Projection

– Change of altitude

– Pitching

– Rolling

– Yawing

9.3 Image Rectification

821 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 99: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Distorted

image

9.3 Image Rectification

822 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 100: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

823 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 101: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Reference

image with

ground

control points

9.3 Image Rectification

824 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 102: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Distorted

image with

ground

control points

9.3 Image Rectification

825 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 103: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 826 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 104: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Polynomial of

degree 1

9.3 Image Rectification

827 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 105: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Polynomial of

degree 2

9.3 Image Rectification

828 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 106: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Polynomial of

degree 3

9.3 Image Rectification

829 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 107: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Reference

image

9.3 Image Rectification

830 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

Page 108: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 831

9.3 Image Processing

http://www.spacegrant.montana.edu/

Page 109: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 832

9.3 Image Processing

http://www.windows2universe.org/

Page 110: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Emphasizing structures

– High pass filter

• Noise reduction

(smoothing)

– Low pass filter

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 833

9.3 Image Enhancement

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

htt

p:/

/ww

w.k

op

pfo

to.d

e/

Page 111: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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))

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 834

9.3 Image Enhancement

0

0

255

255 http://ivvgeo.uni-muenster.de/Vorlesung/FE_Script/3_2.html

VV

VV

Page 112: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Example:

aerosols over

northern India

and Bangladesh

(redmin= 12,

redmax= 200,

greenmin = 20,

greenmax= 196,

bluemin= 0,

bluemax= 170)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 835

9.3 Image Enhancement

htt

p:/

/up

load

.wik

imed

ia.o

rg/

Page 113: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 836

9.4 Thematic Classification

Page 114: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 837

9.4 Thematic Classification

[Ca07]

Page 115: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 838

9.4 Thematic Classification

[Ca07]

Page 116: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 839

9.4 Thematic Classification

[Ca07]

Page 117: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Pattern

• Arrangement of individual objects into distinctive recurring

forms

• Usually follows from a functional relationship between the

individual features that compose the pattern

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 840

9.4 Thematic Classification

[Ca07]

Page 118: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 841

9.4 Thematic Classification

http://maps.google.de/

Page 119: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– 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 842

9.4 Thematic Classification

http://maps.google.de/

Page 120: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• Classification key

– Provide a pictorial, exemplary representation of the

examined areas or objects

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 843

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

Page 121: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 844

9.4 Thematic Classification

http://homepage.univie.ac.at/thomas.engleder/index_20072008.html

Page 122: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 845

9.4 Thematic Classification

http://www.gepdata.ch/

Page 123: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– After parameterization

the multispectral feature

space may be divided

into

• Primary feature spaces

(reflectance, temperature

etc.)

• Linear transformed

feature spaces

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 846

9.4 Thematic Classification

http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_25112004.pdf

Page 124: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Example:

multispectral image

• Water, soil, vegetation

• λ1 : blue, λ2 : green, λ3 : red

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 847

9.4 Thematic Classification

Page 125: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 848

9.4 Thematic Classification

http://2.bp.blogspot.com/

Page 126: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Example:

classification with iterative k-means clustering

(k=3 was chosen)

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 849

9.4 Thematic Classification

Page 127: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

– Example:

aerial photo

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 850

9.4 Thematic Classification

http://www.koppfoto.de/

k-means (k=2)

Page 128: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 851

9.4 Thematic Classification

http://ladamer.org/Feut/pdf/Kursbegleitung/dbv_vl/dbv_vl_kapitel8.pdf

Page 129: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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 852

9.5 Summary

Page 130: 9 Remote Sensing - TU Braunschweig9.1 Physical Basics 9.2 Recording Techniques 9.3 Image Processing 9.4 Thematic Classification 9.5 Summary Spatial Databases and GIS – Karl Neumann,

• 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

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 853

9.5 Summary

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Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 854

9.5 Summary

GIS

objects

recording techniques

collect

manage

analyse

display

classification

remote sensing

image enhancements/ corrections

physics


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