9 remote sensing...9.1 physical basics 9.2 recording techniques 9.3 image processing 9.4 thematic...

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 695

9 Remote Sensing

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

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

– Collect

– Manage

– Analyze

– Display

geographically referenced data (geospatial; spatial)

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


9 Remote Sensing

Visualization, Cartography

Spatial Data Management

Collection of Spatial Data

Analysis, Modelling

Functional Components Structural Components

• Recording on site

– Terrestrial survey techniques

• Global navigation satellite systems (e.g. GPS)

• Very long baseline interferometer (VLBI)

• Theodolite: measuring both horizontal and vertical angles optically

• Total station: electronic theodolite (transit) integrated with an electronic distance meter

– Hydrographic survey

• Aerial survey and survey by remote sensing


9 Remote Sensing

htt

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• 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/

– 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/

• Photogrammetry

– Greek: photo - grammetry = image-measurement

– Acquisition and analysis of images to determine the

properties, form and position of arbitrary objects

– Remote sensing is the acquisition of

physical properties of objects whereas

photogrammetry is the reconstruction

of their geometric form

based on this data


9 Remote Sensing

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

• System characteristics

– Recording techniques • Radiometric resolution

• Geometric resolution

– Platform • Kind of platform

• Altitude

• Orbit

• Period

– Mission

• 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/

• Electromagnetic waves as information carrier

– Straight propagation with the speed of light

– Speed of light = wavelength x frequency

– Longer wavelength, lesser energy → more difficult to

sense


9.1 Physical Basics

electrical field

distance

magnetic field M

E

c speed of light

ν: frequency

λ: wavelength

number of cycles that passes a certain point per second

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

• Electromagnetic

spectrum

– The electromagnetic

spectrum is the range

of all possible

frequencies of

electromagnetic

radiation


9.1 Physical Basics

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• Behavior of electromagnetic waves at interfaces


9.1 Physical Basics

Reflection

Emission Absorption

Transmission

Scattering

Transmission + Reflection + Absorption = 1


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

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

• The extent to which an object diffusely reflects light from

the sun


9.1 Physical Basics

– Albedo depends on wavelength

• There is a strong difference between visual and infrared

albedos of natural materials


9.1 Physical Basics

[AS14]

• The sun is the most important source of

electromagnetic radiation

• With the exception of objects at absolute zero, all

objects emit electromagnetic radiation

– The higher the temperature,

the shorter the wavelength

of maximum emission


9.1 Physical Basics

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

• Blackbody

– Hypothetical source of energy that behaves in an

idealized manner

– It absorbs all incident radiation, none is reflected

– It emits energy with perfect efficiency

– Its effectiveness as a radiator of energy varies only as

temperature varies


9.1 Physical Basics

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

• Emissivity

– The ratio between the emitance of a given object and that of blackbody at the same temperature

– Useful measure of the effectiveness of objects as radiators

– Kirchhoff‘s law: At thermal equilibrium, the emissivity of a body (or surface) equals its absorptivity


9.1 Physical Basics

surface emissivity (8-14 μm)

blackbody 1

water, depending on pollution

0,973-0,979

water with oil film

0,96-0,979

snow 0,99

grass, dense, short

0,92-0,97

Sands, depending on water moisture

0,88-0,985

• Atmospheric window(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/

– 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


• 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/

– Near infrared 0.7 - 3 μm


• 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/

– 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


9.1 Physical Basics

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– 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/

– 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

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• 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

gRv 0

v [km/s]

r [km]

– 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/

– Low Earth Orbit (LEO)

• Heights between 200 and 600 km

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

• Satellites with biological or material experiments and astronomical satellites

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

– Medium Earth Orbits (MEO)

• All orbits above 1000 km up to 36000 km

• Navigation satellite systems (GPS, Glonass)

• Small communication satellites


9.1 Physical Basics

http://www.tobedetermined.org/

– Geosynchronous/geostationary Orbit (GSO)

• Orbit height approximately 35786 km, 0° inclination

• Period is equal to the Earth's rotational period → It maintains the same position relative to the Earth's surface

• Television satellites, weather satellites

– Sun Synchronous Orbit (SSO) or Polar Earth Orbit (PEO)

• Orbit height between 700 and 1000 km, inclination approximately 90°

• Orbit ascends or descends over any given point of the Earth's surface at the same local mean solar time so the surface illumination angle will be nearly the same every time

• Earth observation satellites


9.1 Physical Basics

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– To scale

representation

of the Earth,

LEO, and MEO


9.1 Physical Basics

MEO

• Passive systems: photography, scanner

(optomechanical, optoelectronical)

• Active systems: radar sensors


9.2 Recording Techniques

reflected solar radiation

thermal radiation

reflected artificial radiation

R R T/R

passive systems active systems

• Passive technique

• VIS and NIR (400-1000 nm)

• Analog storage medium

• Common types of films

– Black and white/panchromatic:

• Highest geometric resolution

– Infrared • Unusual representation

• Contrastier

• Distinction between coniferous and deciduous forests

• Surfaces of water easier to identify


9.2 Photographic Systems

[AS14]

– 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)



[AS14]

• 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



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

• Example: digital

aerial orthophotos

of Braunschweig

– Central projection

– Planimetrically corrected

– 30. March 2014



https://www.braunschweig.de/

• Disadvantages

– Difficult radiometric calibration

– Low spectral bandwidth

– Analog data

• Advantages

– Relatively cheap

– High resolution

– "Spontaneous"

recording of areas



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

• 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/



scan direction

aperture angle altitude

sensor platform

flight direction

a: geometric resolution > ground segment s: swath width

instantaneous field of view IFOV: pixel

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

motor

rotating mirror

radiation

optical system telescope

beam splitter dispersion prism

photodetectors

beam splitter interference grid

electronics amplifier, converter

streamer magnetic tape HDDT, CCT

• Radiation imaging

– Mirror rotates around an axis parallel to the flight direction

– The radiation is split into its various wavelengths and focused onto detectors

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




• Advantages – Precise spectral and radiometric

measurements

– Wide total field of view

– Digital data, remote data transmission

• Disadvantages – Relatively short dwell-time

– S-bend

– Panoramic distortion

– Low SNR → limited radiometric resolution



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

• 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



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

1-3

6, 7

4, 5

– Orbit

• Near polar, sun synchronous

• Altitude: 907-913 km (Landsat 1-3),

705 km (Landsat 4-7 )

• Inclination: 99.2° (Landsat 1-3),

98.2° (Landsat 4-7)

• Orbital period:

approximately 100 minutes

→ 14 circulations per day

• Provide complete coverage

of the Earth every 18

(Landsat 1-3) respectively 16

days (Landsat 4-7) Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 733


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

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)



– Typical combination of channels



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



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

• Optoelectronical scanner

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

• Scan lines perpendicular to the direction of flight

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

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


9.2 Push Broom Scanner

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




scan direction

: aperture angle

altitude

sensor platform

flight direction

a: geometric resolution > ground segment s: swath width

focal distance

lens

aperture angle

sample mirror

CCD sensors

optical system

radiation

• Radiation imaging – Tilted mirror, sometimes fixed sometimes tiltable

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

– Data storage in parallel memory chips, remote data transmission




• 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



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

http://www.fe-lexikon.info/images/Spot5.jpg

1-3

4

5


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



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

– Orbit

• Sun synchronous

• Altitude: 822 km

• Inclination 98,7°

• Orbital period 101,4 min

→ approximately 14 circulations per day



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




Spot-1 HRV P-Modus

San Diego(USA), panchromatic, resolution 20 m

Spot-1 HRV XS-Modus

Detroit(USA), false colour composite, resolution 30 m

Spot-5 HRG XS-Modus: stereo




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

• Radio Detection And Ranging

• Principle:

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

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


9.2 Radar

[LKC15]

• Nadir:

– The local vertical direction pointing in the direction of

the force of gravity at that location

• Range:

– Line of sight

• Azimuth:

– Direction of flight


9.2 Radar

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

• Recording parameters

– Polarization

• Direction of the electric field which is perpendicular to the direction of propagation in the transmitted radar signal (H = horizontal, V = vertical) → 4 possibilities: HH, VV, HV, VH

– Depression angle θd

– Pulse length

– Wavelength is divided into 5 bands


9.2 Radar

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

K-band X-band C-band L-band P-band

0,7-1 cm 2,4-4,5 cm 4,5-7,5 cm 15-30 cm 77-136 cm

B

GR2

GR1

R2

R1 A

A

B β

• 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]

GRARL

and

L: antenna length

λ: wavelength where

• Ground range resolution (GRR) depends on the

pulse length (τ) and the depression angle (θ)

– Distinction between

A and B only possible

if the pulse passed A

completely before

reaching B

→ Better ground range resolution in the far range


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

[LKC15]

• 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


• 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


• 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


syn

thet

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radar pulse with frequency v2

frequency v2

object

v1 – v2 > 0 v3 – v2 < 0

• Comparison of the resolution between systems

with real (a) and synthetic (b) aperture


9.2 Radar


• Interactions between radar signals and materials

very complex as it depends on:

– Wavelength

– Incidence angle

– Electrical properties

– Moisture

– Surface property


9.2 Radar

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

• Penetration depths of microwaves

– Increases with decreasing wavelength

– Decreases with increasing

conductivity, which is also

influenced by moisture

– Is higher for smoother

surfaces


9.2 Radar

vegetation

dry alluvium

glacier

[AS14]

• 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

• 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/

– 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/

• 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

htt

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• 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/

• 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/

• 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

• 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 swiveling mirror fibre scanner

– 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/

Last return (DTM)

Primary return (DOM)

– One laser beam might be reflected at different heights,

e.g. in presence of vegetation:

• Primary return: originate from the first objects a lidar pulse

encounters, often the upper surface of a vegetation canopy

• Well suited to create a

digital object model (DOM)


9.2 LIDAR

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

• Secondary returns: lower vegetation layers and the ground surface

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


9.2 LIDAR

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

emitted pulse

first echo last echo

time

time

time

signal strength

scrup terrain

discrete echo determination

full waveform digitisation

signal strength

signal strength

– Coordinates of the

reflection points:

• Calculated from the

position and orientation

of the sensor (by GPS

and INS), the deflection

angle of the beam and

the distance between

sensor and reflection

point

– Result: 3D point set

along the trajectory


9.2 LIDAR

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

– Advantages

• Uniform, dense acquisition of points

• Acquisition of height information for

DOM (with vegetation), as well as

for DTM (without vegetation)

• Accuracy in height between 50 and

15 cm in position1m

• Fast area-wide acquisition

• Active measuring method, nearly

independent of illumination


9.2 LIDAR

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

– Disadvantages

• Arbitrary points, no structure elements (prominent terrain

points, borders)

• Only single points, interpolation

necessary

• Relatively noisy


9.2 LIDAR

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

– 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]

• Comparison between remotely sensed images and topographic maps



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



Content


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



Readability and interpretation


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



Visual comparison


[AS14]

• 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)



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

• Goals of geometric corrections

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

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

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

• The planimetrically corrected image is called orthophoto


9.3 Geometric Errors

[AS14]

aerial photo, uncorrected corrected → orthophoto

• 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



[SX08]

• Varying scale

– Mapping scale changes with variations in terrain

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

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



higher

lower

Map: constant scale

Aerial photo: varying scale

terrace

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

• 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/

• Whiskbroom scanner

– The distance between sensor and

terrain increases towards the edges

– Size of scanning spots increases towards

the edges



[AS14]

scan direction

flight direction

↑

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

– If the angular speed is constant, the image seems to be

increasingly compressed towards the edges

– More elevated surfaces are perpendicular moved away

from the flight direction



[AS14] http://homepage.univie.ac.at/.../lba_fe_28102004.pdf

• Image geometry depends on the depression angle

and the terrain

• Oblique perspective (i.e. side-looking) leads to

relief displacement

– The type and degree

of relief displacement

in the radar image is a

function of the angle

at which the radar

beam hits the ground


9.3 Geometric Errors in Radar Systems

• Foreshortening

– Compression of those features in the scene which are

tilted toward the radar

– Foreshortening effects are

reduced with increasing

incident

angles



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

• 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



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

• Layover

– Occurs when the reflected energy from the upper

portion of a feature is received before the return

from its lower

– The top of the feature will be

displaced,

or "laid

over"

relative to

its base



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

• 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

• 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

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• 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



corrected image raw image

e

n c r e = f (c,r)

n = f (c,r)

– 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)



• 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

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

• Reference

image



• Mathematical distortions

– Central projection

– Change of altitude

– Pitching

– Rolling

– Yawing



• Distorted

image



• 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



+

+

+

+

• Reference

image with

ground

control points



• Distorted

image with

ground

control points



• Mapping functions

– Polynomials are often used

• Degree 1 needs 3 GCPs




http://en.wikipedia.org/wiki/Polynomial 798 Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig

• Polynomial of

degree 1



• Polynomial of

degree 2



• Polynomial of

degree 3



• Reference

image



• 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



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

– 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



http://www.windows2universe.org/

• Emphasizing structures

– High pass filter

• Noise reduction

(smoothing)

– Low pass filter


9.3 Image Enhancement

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9

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• 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))



0

0

255

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

VV

VV

• Example:

aerosols over

northern India

and Bangladesh

(redmin= 12,

redmax= 200,

greenmin = 20,

greenmax= 196,

bluemin= 0,

bluemax= 170)



htt

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/up

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.wik

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• 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



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

• 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



[CW11]

– 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



[CW11]

– 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



[CW11]

– Pattern

• Arrangement of individual objects into distinctive recurring

forms

• Usually follows from a functional relationship between the

individual features that compose the pattern



https://jameystillingsprojects.com/ ©1980-2017 Jamey Stillings, All Rights Reserved

– 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



http://maps.google.de/

– Shape

• Obvious clue to the identity of

objects

• Often shape alone might be sufficient to

provide clear identification

– Size

• Relative size of an object in relation to other objects on the

image provides the interpreter with an intuitive notion of its

scale and resolution

• Can be measured, permit derivation of quantitative

information



http://maps.google.de/

• Classification key

– Provide a pictorial, exemplary representation of the

examined areas or objects



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

spruce

silver fir

douglas fir beech

oak

pine



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

• Multispectral classification

– Ideally every class is defined by a typical multispectral

signature, caused by a statistical distribution of the

pixels of each class → Examination of the pixels of a

multispectral image by mathematical algorithms

• With regard to their homogeneity

• Spatial distribution

– Two types of classifiers

• Unsupervised, autonomous

• Supervised, interactive



http://www.gepdata.ch/

– After parameterization

the multispectral feature

space may be divided

into

• Primary feature spaces

(reflectance, temperature

etc.)

• Linear transformed

feature spaces



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

– Example:

multispectral image

• Water, soil, vegetation

• λ1 : blue, λ2 : green, λ3 : red



• 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



– Example:

classification with iterative k-means clustering

(k=3 was chosen)



– Example:

aerial photo



http://www.koppfoto.de/

k-means (k=2)

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



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

• Physical basics

– Electromagnetic radiation

– Orbits

• Recording techniques

– Photographic systems (Cosmos, Aerial camera)

– Whiskbroom scanner (Landsat)

– Pushbroom scanner (SPOT)

– Radar (Sentinel-1)

– LIDAR (Airborne Laserscanning)


9.5 Summary

• Image processing

– Comparison between remotely sensed images and

topographic maps

– Causes of geometric errors

– Image rectification

– Image enhancement

• Thematic classification

– Visual interpretation

– Quantitative image analysis


9.5 Summary


9.5 Summary

GIS

objects

recording techniques

collect

manage

analyse

display

classification

remote sensing

image enhancements/ corrections

physics

9 remote sensing...9.1 physical basics 9.2 recording techniques 9.3 image processing 9.4 thematic...

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