9 Remote Sensing

(1)

9.1 Physical Basics

9.2 Recording Techniques 9.3 Image Processing

9.4 Thematic Classification 9.5 Summary

9 Remote Sensing

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

(2)

• A geographic information system (GIS) is a computer hardware and software system designed to

– Collect – Manage – Analyze – Display

geographically referenced data (geospatial; spatial)

• It is a specialized information system consisting of a (spatial) database and a (special) database system

9 Remote Sensing

Visualization, Cartography

Spatial Data Management Collection of

Spatial Data

Analysis, Modelling

Functional Components Structural Components

(3)

• 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

– Hydrographic survey

• Aerial survey and survey by remote sensing

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 697

9 Remote Sensing

http://i00.i.aliimg.com/

(4)

• 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

9 Remote Sensing

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

(5)

– That uses the electromagnetic radiation

which is emitted by the observed object

– That carries receiving devices on aircraft or spacecraft

– That serves for the observation of the surface of the earth including all objects thereon, the oceans or the atmosphere

9 Remote Sensing

http://www.aero-news.net/

(6)

• Photogrammetry

– Greek: photo - grammetry = image-measurement – Acquisition and analysis of images to determine the

properties, form and position of arbitrary objects – Remote sensing is the acquisition of

physical properties of objects whereas photogrammetry is the reconstruction of their geometric form

based on this data

9 Remote Sensing

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

(7)

• System characteristics

– Recording techniques

• Radiometric resolution

• Geometric resolution

– Platform

• Kind of platform

• Altitude

• Orbit

• Period

– Mission

• Spatial coverage

• Temporal coverage

9 Remote Sensing

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

http://www.dlr.de/

http://www.giga.de/

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

(8)

• Electromagnetic waves as information carrier

– Straight propagation with the speed of light – Speed of light = wavelength x frequency

– Longer wavelength, lesser energy → more difficult to sense

9.1 Physical Basics

electrical field distance

magnetic field M

E

c

speed of light

ν: frequency

λ: wavelength

number of cycles that passes a certain point per second

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

ElektromagnetischeWelle.jpg

(9)

• Electromagnetic spectrum

– The electromagnetic spectrum is the range of all possible

frequencies of electromagnetic radiation

9.1 Physical Basics

http://en.wikipedia.org/

(10)

• Behavior of electromagnetic waves at interfaces

9.1 Physical Basics

Reflection

Emission Absorption

Transmission

Scattering

Transmission + Reflection + Absorption = 1

(11)

9.1 Physical Basics

[AS14]

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

(12)

– The albedo (lat. albedo = "whiteness"), reflectivity

• The extent to which an object diffusely reflects light from the sun

9.1 Physical Basics

(13)

– Albedo depends on wavelength

• There is a strong difference between visual and infrared albedos of natural materials

9.1 Physical Basics

[AS14]

(14)

• The sun is the most important source of electromagnetic radiation

• With the exception of objects at absolute zero, all objects emit electromagnetic radiation

– The higher the temperature, the shorter the wavelength of maximum emission

9.1 Physical Basics

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

(15)

• Blackbody

– Hypothetical source of energy that behaves in an idealized manner

– It absorbs all incident radiation, none is reflected – It emits energy with perfect efficiency

– Its effectiveness as a radiator of energy varies only as temperature varies

9.1 Physical Basics

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

(16)

• Emissivity

– The ratio between the emitance of a given object and that of

blackbody at the same temperature

– Useful measure of the

effectiveness of objects as radiators

– Kirchhoff‘s law: At thermal

equilibrium, the emissivity of a body (or surface) equals its absorptivity

9.1 Physical Basics

surface emissivity (8-14 μm) blackbody 1

water, depending on pollution

0,973-0,979

water with oil film

0,96-0,979

snow 0,99

grass,

dense, short

0,92-0,97 Sands,

depending on water moisture

0,88-0,985

(17)

• Atmospheric window(s)

– Portion(s) of the electromagnetic spectrum that can be transmitted through the atmosphere

9.1 Physical Basics

http://www.geographie.ruhr-uni-bochum.de/agklima/

(18)

– 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

– 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

9.1 Physical Basics

http://www.samtgemeinde-nord-elm.de/

(19)

– Near infrared 0.7 - 3 μm

• Reflected solar radiation

• Nearly no atmospheric influences

• Main application: Classification of vegetation, forest health survey (healthy green plants strongly reflect near infrared radiation), classification of water (expanses of water seem dark as they absorb all)

9.1 Physical Basics

http://www.forestwatch.sr.unh.edu/

(20)

– Far infrared (thermal energy) 3 - 1000 μm (usually : 8 - 14 μm)

• Radiation emitted by the earth

• Nearly no atmospheric influences (but clouds are

impermeable, CO

₂

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

9.1 Physical Basics

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

(21)

– 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 signal-to-noise ratio → noisy images

• Main applications: Meteorology (temperature profiles of the atmosphere) and oceanography (ice observation)

9.1 Physical Basics

http://nsidc.org/cryosphere/

(22)

– Active microwaves (radar) 1 - 300 mm

• Reflected, transmitted microwave radiation

• Nearly no atmospheric influences (except reaction on water drops)

• Applicable day and night

• Measurements beneath the surface to some extent

• Polarization effects

• Higher ground resolution as passive microwaves

• Complex signal

• Doppler effect allows detection of

moving objects (military applications), sea pollution

9.1 Physical Basics

http://www.wetteronline.de/

(23)

• Orbits

– Altitude, orbital period,

9.1 Physical Basics

v orbital speed R

Earth‘s

radius= 6 370 km

g₀

gravitational acceleration on the Earth‘s surface = 9,81 m/s²

r radius of the satellite orbit

r

R

g

v 

⁰

v ^[km/s]

r ^[km]

(24)

– Apogee/perigee

• Greatest/least distance from the earth

– Inclination

• Angular distance of the orbital plane from the equator

9.1 Physical Basics

http://www.skyandtelescope.com/ http://vro.agriculture.vic.gov.au/

(25)

– Low Earth Orbit (LEO)

• Heights between 200 and 600 km

• Manned space stations: low inclination and heights above 400 km

• Satellites with biological or material experiments and astronomical satellites

• Spy satellites 90° inclination , perigee 200-250 km, apogee 600-900km

– Medium Earth Orbits (MEO)

• All orbits above 1000 km up to 36000 km

• Navigation satellite systems (GPS, Glonass)

• Small communication satellites

9.1 Physical Basics

http://www.tobedetermined.org/

(26)

– 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

9.1 Physical Basics

http://cimss.ssec.wisc.edu/sage/

(27)

– To scale

representation of the Earth, LEO, and MEO

9.1 Physical Basics

MEO

(28)

• Passive systems: photography, scanner (optomechanical, optoelectronical)

• Active systems: radar sensors

9.2 Recording Techniques

reflected solar radiation thermal

radiation reflected artificial

radiation

R R

T/R

passive systems active systems

(29)

• Passive technique

• VIS and NIR (400-1000 nm)

• Analog storage medium

• Common types of films

– Black and white/panchromatic:

• Highest geometric resolution

– Infrared

• Unusual representation

• Contrastier

• Distinction between coniferous and deciduous forests

• Surfaces of water easier to identify

9.2 Photographic Systems

[AS14]

(30)

– Color/chromatic:

• Worse geometric resolution as black and white, better thematic interpretability

– Color infrared films:

• The blue-sensitive layer is replaced by an emulsion sensitive to a portion of the near infrared region

• Good thematic interpretability (vegetation)

9.2 Photographic Systems

[AS14]

(31)

• Example: Cosmos with KVR 1000 Camera

– Russian spy satellite

– Polar, sun-synchronous – Altitude 200km

– Ground resolution 2m – Black and white film – Durability 45 days – Missions 1981–2000

9.2 Photographic Systems

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

(32)

• Example: digital

aerial orthophotos of Braunschweig

– Central projection – Planimetrically

corrected

– 30. March 2014

9.2 Photographic Systems

https://www.braunschweig.de/

(33)

• Disadvantages

– Difficult radiometric calibration – Low spectral bandwidth

– Analog data

• Advantages

– Relatively cheap – High resolution – "Spontaneous"

recording of areas

9.2 Photographic Systems

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

(34)

• Optomechanical scanner

• A rotating 45 degree scan

mirror continuously scans the Earth beneath the

platform perpendicular to the direction of flight

• The system collects data one pixel at a time sequentially

• A scan line (mirror rotation) is equivalent to the image swath

• The forward motion of the platform used to acquire a scene with sequential scan lines

9.2 Whisk Broom Scanner

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

(35)

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

(36)

motor

rotating mirror

radiation

optical system telescope

beam splitter dispersion prism

photodetectors beam splitter

interference grid

electronics

amplifier, converter

streamer

magnetic tape HDDT, CCT

• Radiation imaging

– Mirror rotates around an axis parallel to the flight direction – The radiation is split into its various wavelengths and focused

onto detectors

– Stored on magnetic tape (HDDT, CCT), remote data transmission

9.2 Whisk Broom Scanner

(37)

• Advantages

– Precise spectral and radiometric measurements

– Wide total field of view – Digital data, remote data

transmission

• Disadvantages

– Relatively short dwell-time – S-bend

– Panoramic distortion

– Low SNR → limited radiometric resolution

9.2 Whisk Broom Scanner

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

(38)

• Landsat

– American satellite series

• Landsat 1: 1972-1978

• Landsat 2: 1975-1981

• Landsat 3: 1978-1983

• Landsat 4: 1982-1993

• Landsat 5: 1984-2013

• Landsat 6: 1993 failure

• Landsat 7: since1999

• Landsat 8: since 2013

9.2 Whisk Broom Scanner

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

1-3

6, 7 4, 5

(39)

– Orbit

• Near polar, sun synchronous

• Altitude: 907-913 km (Landsat 1-3), 705 km (Landsat 4-7 )

• Inclination: 99.2° (Landsat 1-3), 98.2° (Landsat 4-7)

• Orbital period:

approximately 100 minutes

→ 14 circulations per day

• Provide complete coverage

of the Earth every 18

(Landsat 1-3) respectively 16 days (Landsat 4-7)

9.2 Whisk Broom Scanner

ground trace for Landsat1-3 for one day [AS14]

(40)

LANDSAT 4,5 (1-3) LANDSAT 4,5 LANDSAT 7 sensor Multispectral Scanner

(MSS)

Thematic Mapper (TM) Enhanced Thematic Mapper Plus (ETM+) pixel size 79 x 79 m² 30 x 30 m² 30 x 30 m²

spectral channels

1 (4) 0,50 - 0,60 µm, green

2 (5) 0,60 - 0,70 µm, red

3 (6) 0,70 - 0,80 µm, near infrared

4 (7) 0,80 - 1,10 µm, near infrared

1 0,45 - 0,52 µm, blue- green

2 0,52 - 0,60 µm, green 3 0,63 - 0,69 µm, red 4 0,76 - 0,90 µm, near infrared

5 1,55 - 1,73 µm, mid infrared

7 2,08 - 2,35 µm , mid infrared

1 0,45 - 0,52 µm, blue- green

2 0,52 - 0,60 µm, green 3 0,63 - 0,69 µm, red 4 0,76 - 0,90 µm, near infrared

5 1,55 - 1,73 µm, mid infrared

7 2,08 - 2,35 µm , mid infrared

thermal channel 6 10,4 - 12,5 µm (120 x 120 m²)

6 10,4 - 12,5 µm (60 x 60 m²)

panchromatic channel 8 0,52 - 0,90 µm

(15 x 15 m²)

9.2 Whisk Broom Scanner

(41)

– Typical combination of channels

9.2 Whisk Broom Scanner

0,5-0,6 μm 0,8-0,9 μm

false colour composite

0,6-0,7 μm

true colour composite

infrared red

green

(42)

9.2 Whisk Broom Scanner

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

(43)

• Optoelectronical scanner

• Employs a linear array of solid semi- conductive elements to acquire one entire line of spectral data

simultaneously

• Scan lines perpendicular to the direction of flight

• Forward motion of the platform to acquire a sequence of imaged lines to map a scene

• CCDs (charge coupled device) to serialize parallel analog signals

9.2 Push Broom Scanner

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

(44)

9.2 Push Broom Scanner

scan direction

: aperture angle

altitude

sensor platform

flight direction

a: geometric resolution > ground segment s: swath width

(45)

focal distance

lens

aperture angle sample mirror

CCD sensors

optical system radiation

• Radiation imaging

– Tilted mirror, sometimes fixed sometimes tiltable

– CCD image sensors in the image plane of the lens: line scan camera

– Data storage in parallel memory chips, remote data transmission

9.2 Push Broom Scanner

(46)

• Spot (Systeme Probatoire d'Oberservation de la Terre) – French satellite series

• Spot-1: 1986-1990

• Spot-2: 1990-2009

• Spot-3: 1993-1997

• Spot-4: since 1998

• Spot-5: since 2002

• Spot 6: since 2012

• Spot 7: since 2014

– Two identical parallel sensors that can be operated independently

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

(47)

angled

view nadir-

looking

– Pivoting of the sensors can be employed for stereoscopy and also for a higher repeat circle – Sensors are operated from the ground stations

9.2 Push Broom Scanner

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

(48)

– Orbit

• Sun synchronous

• Altitude: 822 km

• Inclination 98,7°

• Orbital period 101,4 min

→ approximately 14 circulations per day

9.2 Push Broom Scanner

SPOT 1-3 SPOT 4 SPOT 5

sensor HRV (Instrument Haute Résolution Visible)

HRVIR (High Resolution Visible and Infrared)

HRG (High Resolu- tion Geometric) geometric

resolution

20 m (XS), 10 m (PN)

20 m (XS), 10 m (P)

10 m (VIS, NIR), 2,5/5 m (PAN), 20 m (MIR) radiometric

resolution

0,5-0,9 μm:

3 VIS, 1 NIR

0,5-1,75 μm:

3 VIS, 1 NIR, 1 MIR

0,45-1,75 μm:

2 VIS, 2 NIR, 1 MIR

http://spot5.cnes.fr/.../35.htm

(49)

9.2 Push Broom Scanner

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

(50)

Spot-5 HRG XS-Modus: stereo

9.2 Push Broom Scanner

Dead sea (Jordan), panchromatic, 11/2002 resolution 2,5 m

(51)

• Radio Detection And Ranging

• Principle:

– Transmitting radar pulses (microwaves) and recording the reflected radiation

→ active

– The transit time and the strength of the reflected signal is measured

9.2 Radar

[LKC15]

(52)

• Nadir:

– The local vertical direction pointing in the direction of the force of gravity at that location

• Range:

– Line of sight

• Azimuth:

– Direction of flight

9.2 Radar

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

(53)

• Recording parameters

– Polarization

• Direction of the electric field which is perpendicular to the direction of propagation in the transmitted radar signal (H = horizontal, V = vertical)

→ 4 possibilities: HH, VV, HV, VH

– Depression angle θ

_d

– Pulse length

– Wavelength is divided into 5 bands

9.2 Radar

http://ladamer.org/.../FE1-06-Radar.pdf

K-band X-band C-band L-band P-band 0,7-1 cm 2,4-4,5 cm 4,5-7,5 cm 15-30 cm 77-136 cm

(54)

B GR₂

GR₁

R₂ R₁

A

A β B

• Azimuth resolution AR depends on beam width (β) and the ground range distance (GR)

→ Azimuth resolution is better in the near range

9.2 Radar

[LKC15]





 GR

AR

L







and L: antenna length

λ: wavelength where

(55)

• 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

9.2 Radar

Pulse length τ

Front of return wave from A

Front of return wave from B

A B

τ

< 2

Rear of

outgoing wave



 cos 2

 c GRR

[LKC15]

(56)

• In order to improve the resolution

– Ground range

• Decrease pulse length

– Azimuth

• Decrease wavelength

• Increase antenna length

• The azimuth resolution

is unacceptably coarse for systems operating at satellite altitudes

9.2 Radar

(57)

• Synthetic aperture radar (SAR)

– Scene is illuminated over an interval of time → history of reflections – The further an object

the longer the time it is illuminated

– As changes in frequency are systematic separate components of the

reflected signal can be assigned to their correct position

9.2 Radar

(58)

• Doppler-effect

– Approaching → increase in frequency

– Receding → decrease in frequency

• Physical antenna as small as possible

• Azimuth resolution

independent of GR and λ

9.2 Radar

synthetic aperture

radar pulse with frequency v₂

frequency v₂

object

v₁ – v₂ > 0 v₃ – v₂ < 0

(59)

• Comparison of the resolution between systems with real (a) and synthetic (b) aperture

9.2 Radar

(60)

• Interactions between radar signals and materials very complex as it depends on:

– Wavelength

– Incidence angle

– Electrical properties – Moisture

– Surface property

9.2 Radar

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

(61)

• Penetration depths of microwaves

– Increases with decreasing wavelength – Decreases with increasing

conductivity, which is also influenced by moisture

– Is higher for smoother surfaces

9.2 Radar

vegetation

dry alluvium

glacier

[AS14]

(62)

• Problem-oriented quantitative analysis of radar images is difficult as it relies mostly on hardly comprehensible interdependencies

9.2 Radar

C-Band L-Band P-Band

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

(63)

• Sentinel-1

– SAR satellites in the Copernicus program

– Sentinel-1A launched on 3 April 2014, Sentinel-1B on 25 April 2016

– Orbit

• Sun synchronous

• 693 km altitude

• 98.2° inclination

• Orbital period 98.5 min

• Repeat circle 6 days (two satellites)

9.2 Radar

http://104.131.251.97/copernicus/

(64)

– Mass: 2300 kg (including 130 kg fuel)

– Size: 2.8 m long, 2.5 m wide, 4 m high

with 2×10 m-long solar arrays and a 12 m-long radar antenna

– Solar array average power: 5900 W

– Battery capacity: 324 Ah

– Azimuth resolution:

5, 20, 40 m

– Ground range resolution: 5, 20 m

9.2 Radar

http://104.131.251.97/copernicus/

(65)

• Image of Ireland (May 2015)

– Blue: strong changes in bodies of water or

agricultural activities within 12 days

– Yellow: urban centers – Green: vegetated fields

and forests – Red and orange: bare

soil and rocks

9.2 Radar

https://directory.eoportal.org/

(66)

• Nepal earthquake displacement

– Image shows how and where the land uplifted and sank from the 7.8-

magnitude

earthquake that struck

Nepal on 25 April 2015

9.2 Radar

http://www.esa.int/

(67)

• Map of Greenland ice sheet velocity

– January–March 2015

– About 1200 radar scenes were used

– Colour scale in meters per day

9.2 Radar

http://www.esa.int/

(68)

• 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"

9.2 LIDAR

(69)

• Airborne Laserscanning

– The distance between the sensor and the surface to be measured is determined from the runtime of a light pulse

– By deflection of the laser beam and the forward movement of the aircraft a wide strip is scanned

9.2 LIDAR

elliptical scanning fibre scanner swiveling mirror

(70)

– Parameters

• Sampling rate

• Scan angle

• Scan frequency

• Altitude

• Aircraft speed

– Recorded data

• Position

• Orientation of the aircraft

• Angle of every emitted beam

• Measured distance

9.2 LIDAR

https://www.e-education.psu.edu/geog481/

(71)

Last return (DTM)

Primary return (DOM)

– One laser beam might be reflected at different heights, e.g. in presence of vegetation:

• Primary return: originate from the first objects a lidar pulse encounters, often the upper surface of a vegetation canopy

• Well suited to create a

digital object model (DOM)

9.2 LIDAR

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

(72)

• Secondary returns: lower

vegetation layers and the ground surface

• Last return provides data for a digital terrain model (DTM) if the vegetation is not too dense

9.2 LIDAR

http://publik.tuwien.ac.at/files/PubDat_166922.pdf

emitted pulse

first echo last echo

time time

time signal

strength

scrup terrain

discrete echo determination

full waveform digitisation signal

strength

signal strength

(73)

– Coordinates of the reflection points:

• Calculated from the

position and orientation of the sensor (by GPS and INS), the deflection angle of the beam and the distance between sensor and reflection point

– Result: 3D point set along the trajectory

9.2 LIDAR

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

(74)

– 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

9.2 LIDAR

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

(75)

– Disadvantages

• Arbitrary points, no structure elements (prominent terrain points, borders)

• Only single points, interpolation necessary

• Relatively noisy

9.2 LIDAR

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

(76)

– 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

9.2 LIDAR

[HBS11]

(77)

• Comparison between remotely sensed images and topographic maps

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

(78)

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

(79)

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

(80)

9.3 Image Processing

Visual comparison

Remotely sensed image Topographic map

[AS14]

(81)

• Geometric errors, distortions

– Inaccurate position and form of objects – Causes

• Recording techniques and system

• Relief

• Platform (instability, motion)

• Radiometric errors

– Faulty pixel values – Causes

• Atmospheric interference

• Topographical effects

• Technical defects (sensors, data transfer)

9.3 Image Processing

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

(82)

• Goals of geometric corrections

– Represent objects in uniform scale and true geometry (system correction)

– Register overlapped images of a scene from different dates and views (image to image registration)

– Register the image to real world map coordinates (image to map registration)

• The planimetrically

corrected image

is called

orthophoto

9.3 Geometric Errors

[AS14]

aerial photo, uncorrected corrected → orthophoto

(83)

• Radial displacement

– Causes objects to be displaced outward from the nadir

– Increases with the height of the object and distance from the nadir

– E.g. tops of buildings are

displaced outward relative to the bases

9.3 Geometric Errors in Photographic Systems

(84)

9.3 Geometric Errors in Photographic Systems

[SX08]

(85)

• Varying scale

– Mapping scale changes with variations in terrain

– The scale of objects closer to the camera is larger than that of objects being further away

– The mapping of a rectangle that covers a terrace is not a rectangle

9.3 Geometric Errors in Photographic Systems

higher

lower Map:

constant scale

Aerial photo:

varying scale

terrace

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

(86)

• 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

• Displacement depends on the relative speed of the satellite, the earth rotation, and the size of the image

• Example (Landsat 7):

– 33.8°S (Sidney)

– Image size: 185 km

→ Offset: 10.82 km (~ 6%)

9.3 Geometric Errors in Scanners

pixel satellite

motion↓ earth rotation →

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

(87)

• Whiskbroom scanner

– The distance between sensor and terrain increases towards the edges

– Size of scanning spots increases towards the edges

9.3 Geometric Errors in Scanners

[AS14]

scan direction flight

direction

↑

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

dbv_vl/dbv_vl_kapitel3.pdf

(88)

– If the angular speed is constant, the image seems to be increasingly compressed towards the edges

– More elevated surfaces are perpendicular moved away from the flight direction

9.3 Geometric Errors in Scanners

[AS14]

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

(89)

• 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

9.3 Geometric Errors in Radar Systems

(90)

• Foreshortening

– Compression of those features in the scene which are tilted toward the radar

– Foreshortening effects are reduced with increasing

incident angles

9.3 Geometric Errors in Radar Systems

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

(91)

• Radar shadow

– Areas not illuminated by the radar

– Caused by either concave or convex relief features if the slope on the opposite side of the antenna is larger than the depression angle

– Typical in high relief terrain

– Occur in the down- range direction

– Most prominent

with large incidence angle illumination

9.3 Geometric Errors in Radar Systems

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

(92)

• Layover

– Occurs when the reflected energy from the upper portion of a feature is received before the return from its lower

– The top of the feature will be

displaced, or "laid over"

relative to its base

9.3 Geometric Errors in Radar Systems

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

(93)

• Instability of the platform (aircraft)

9.3 Geometric Errors

change of flight speed

pitching change of

altitude rolling

yawing

[AS14]

http://wdc.dlr.de/data_products/SURFACE/LCC/diplomarbeit_u_gessner_2005.pdf

(94)

• Model-based correction algorithm

– Develop a model for a given recording technique and platform that considers all its

inherent causes for distortions

– Parameterize the model to fit the actual conditions under which the image was taken

– Suitable if the kind and cause of the distortion is known, as earth rotation, satellite orbit or positional parameters of the platform

9.3 Geometric Corrections

http://www.der-schweighofer.at/

(95)

• 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 (GCPs)

i.e. features visible on the image with

known ground coordinates

9.3 Geometric Corrections

corrected image raw image e

n e = f (c,r) r c

n = f (c,r)

(96)

– Assigns to each pixel a new position in the reference grid

– Needs 6 GCPs for two-dimensional second order

polynomials (12 unknowns)

– Involves the following steps:

I. Choice of a suitable function (mapping)

II. Coordinate transformation III. Resampling (interpolation)

9.3 Geometric Corrections

(97)

• 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

(98)

• Reference image

9.3 Image Rectification

(99)

• Mathematical distortions

– Central projection – Change of altitude – Pitching

– Rolling – Yawing

9.3 Image Rectification

(100)

• Distorted image

9.3 Image Rectification

(101)

• 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

+ +

+

(102)

• Reference image with ground

control points

9.3 Image Rectification

(103)

• Distorted image with ground

control points

9.3 Image Rectification

(104)

• 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

(105)

• Polynomial of degree 1

9.3 Image Rectification

(106)

• Polynomial of degree 2

9.3 Image Rectification

(107)

• Polynomial of degree 3

9.3 Image Rectification

(108)

• Reference image

9.3 Image Rectification

(109)

• 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

9.3 Image Processing

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

(110)

– 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

9.3 Image Processing

http://www.windows2universe.org/

(111)

• Emphasizing structures

– High pass filter

• Noise reduction (smoothing)

– Low pass filter

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

http://www.koppfoto.de/

(112)

• Contrast enhancement

– Alters each pixel value in the old image to produce a new set of values that exploits the full range of values – E.g. linear stretching

• Chose a new minimum and maximum value

• Intermediate values are scaled proportionally

g‘(x,y) = (g(x,y)+c₂)⋅ c₁ with c₁=255/[max(g(x,y)) – min(g(x,y))], c₂ = -min(g(x,y))

9.3 Image Enhancement

0 0 255

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

VV

V V

(113)

• Example:

aerosols over northern India

and Bangladesh

(red

_min

= 12, red

_max

= 200,

green

_min

= 20, green

_max

= 196,

blue

_min

= 0,

blue

_max

= 170)

9.3 Image Enhancement

http://upload.wikimedia.org/

(114)

• Assignment of objects, features, or areas to

classes based on their appearance on the imagery

• Distinction between 3 levels of confidence

– Detection: determination of the presence or absence of a feature

– Recognition: object can be assigned an identity in a general class or category

– Identification: object or

feature can be assigned to a very specific class

9.4 Thematic Classification

http://www.bing.com/maps/

(115)

• Eight elements of image interpretation

– Image tone

• Lightness or darkness of a region within an image

• Refers ultimately to the brightness of an area of ground as portrayed by the film

• Influenced by vignetting, i.e. the image becomes darker near the edges

9.4 Thematic Classification

[CW11]

(116)

– Image texture

• Apparent roughness or smoothness of an image region

• Caused by the pattern of highlighted and shadowed areas created when an irregular surface is illuminated from an oblique angle

9.4 Thematic Classification

[CW11]

(117)

– Shadow

• May reveal characteristics of its size or shape that would not be obvious from the overhead view alone

• Important clue in the interpretation of individual objects

9.4 Thematic Classification

[CW11]

(118)

– Pattern

• Arrangement of individual objects into distinctive recurring forms

• Usually follows from a functional relationship between the individual features that compose the pattern

9.4 Thematic Classification

(119)

– Association

• Specifies the occurrence of certain objects or features, without a strict spatial arrangement

• Identification of a class implies that objects of another class are likely to be found nearby

– Site

• Refers to topographic position

• E.g. sewage treatment facilities are positioned at low topographic sites near streams or rivers

9.4 Thematic Classification

http://maps.google.de/

(120)

– 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

9.4 Thematic Classification

http://maps.google.de/

(121)

• Classification key

– Provide a pictorial, exemplary representation of the examined areas or objects

9.4 Thematic Classification

http://homepage.univie.ac.at/thomas.engleder/lba_fe/lba_fe_02122004.pdf

spruce

silver fir

douglas fir beech

oak pine

(122)

9.4 Thematic Classification

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

(123)

• Multispectral classification

– Ideally every class is defined by a typical multispectral signature, caused by a statistical distribution of the pixels of each class → Examination of the pixels of a multispectral image by mathematical algorithms

• With regard to their homogeneity

• Spatial distribution

– Two types of classifiers

• Unsupervised, autonomous

• Supervised, interactive

9.4 Thematic Classification

http://www.gepdata.ch/

(124)

– After parameterization the multispectral feature space may be divided

into

• Primary feature spaces (reflectance, temperature etc.)

• Linear transformed feature spaces

9.4 Thematic Classification

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

(125)

– Example:

multispectral image

• Water, soil, vegetation

• λ

₁

: blue, λ

₂

: green, λ

₃

: red

9.4 Thematic Classification

(126)

• 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