PDF (14c)

Department of Geography
Grundlagen Fernerkundung - 14
Wrap up
GEO123.1, FS2015
Michael Schaepman & Hendrik Wulf,
5/22/15
Page 2
Department of Geography
Fernerkundung !
! ist das berührungsfreie Messen und Interpretieren von reflektierter oder
emittierter elektromagnetischer Strahlung.
! umfasst die gesamte Erdoberfläche einschließlich der Erdatmosphäre.
! wird durch satelliten-, flugzeug-, dronen- und handgetragende Sensoren
(Kameras und Scanner) ermöglicht.
Department of Geography
Systeme & Anwendungen
Bei der Fernerkundung finden passive oder aktive Systeme Verwendung.
Passive Systeme zeichnen die von der Erdoberfläche reflektierte
Sonnenstrahlung auf sowie die von der Erdoberfläche emittierte
Eigenstrahlung (z.B. Thermalkamera). Im Gegensatz dazu senden aktive
Systeme Mikrowellen- oder Laserstrahlen aus und empfangen deren
reflektierte Anteile (z.B. Radarsysteme und Laseraltimeter).
Fernerkundungsdaten sind insbesondere in den Geowissenschaften/
Geographie von großer Bedeutung, da eine globale Beobachtung der
Erdoberfläche/Atmosphäre in hoher räumlicher Auflösung nur mit Hilfe
von Fernerkundungssensoren möglich ist. Neben dem synoptischen
Überblick über große Räume ermöglichen satellitengestützte
Fernerkundungssensoren zudem eine wiederholte (zum Teil tägliche)
Abdeckung ein und desselben Gebietes.
Department of Geography
Strahlungspfade der Fernerkundung
Department of Geography
Strahlungskomponenten an einem Sensor
Ls
E0
Latm
L gnd
"u
"d
L g,adj
Lg,dir
Edif
Egnd
!
Department of Geography
Das elektromagnetische Spektrum
< 0.3 µm
Ultraviolet / UV
0.7 µm – 1.3 µm
‘near IR’ / NIR
0.4 µm – 0.5 µm
‘blue’ / VIS
1.3. µm – 3 µm
‘shortwave IR’ / SWIR
0.5 µm – 0.6 µm
‘green’ / VIS
3 µm – 14 µm
‘thermal IR’ / TIR
0.6 µm – 0.7 µm
‘red’ / VIS
1 mm – 1 m
‘microwave’
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Solar radiation spectrum
Solarkonstante
1’361 W/m2
Department of Geography
Räumliche, spektrale und zeitliche Auflösung
Department of Geography
Spektralbereiche und Systeme
Überblick über Fernerkundungssensoren und Systeme
System
Spektralbereich
Photographische Kameras
UV – NIR
Solid State Kameras
VIS – IR
Multispektralscanner
UV – IR
Abbildende Spektrometer
VIS – IR
Radiometer
UV – MW
Radar, SAR
MW
Lidar
VIS – NIR
Sonar
Audiowellen
Department of Geography
Spektrale Auflösung
Department of Geography
Die atmosphärische Interaktion
4 Typen der Streuung der Strahlung in der Atmosphäre
- Rayleigh Streuung
- Raman Streuung
- Mie Streuung
- unselektive Streuung
Department of Geography
Definition des räumlichen Referenzsystems
Department of Geography
Spekulare und diffuse Reflektanz
Department of Geography
Geometrische Effekte, die eine Veränderung der
Reflektanz zur Folge haben
Department of Geography
Direktionale Effekte
09:58
13:40
17:12
Department of Geography
Komponenten einer auf ein Laubblatt
eintreffenden Strahlung
Department of Geography
Charakteristische Reflexionskurve eines grünen
Blattes
Department of Geography
Reflexionskurven für Blätter mit
unterschiedlichem Wassergehalt
Department of Geography
Characterizing Land Surface Processes – Temporal!
Photos: M. Kneubühler
09.04.1999
!
!
!
!
!
!
!
09.06.1999
!
!
!
!
!
!
!
17.07.1999
!02.05.1999
!27.05.1999!
!24.06.1999
!05.07.1999!
!26.07.1999
!12.08.1999!
Department of Geography
Characterizing Land Surface Processes – Spectral!
Daten: M. Kneubühler
Department of Geography
Imaging Spectroscopy
In literature, the terms imaging spectroscopy, imaging spectrometry,
hyperspectral, superspectral, and ultraspectral imaging are often used
interchangeably. Even though semantic differences might exist, a
common definition is:
–" Imaging spectrometry is the simultaneous acquisition of spatially coregistered images, in many, spectrally contiguous bands, measured in
calibrated radiance units, from a remotely operated platform.
–" Imaging spectroscopy is the simultaneous acquisition of spatially coregistered images, in many, spectrally contiguous bands, measured as
reflectance, from a remotely operated platform.
Department of Geography
Image Cube Concept
!"#$%&'()*+',-./&01/2')3345'6./07&%'()5',89:';/2<=>>?'>@'A&1>7&',&2B"2#*''
Department of Geography
Data cube – Spectral information
Department of Geography
Data
Acquisition
a)" Film camera
b)" Frame camera
c)" Scanner
d)" Pushbroom imager
e)" Whiskbroom imager
f)" Pushbroom imaging
spectrometer
Department of Geography
Begriffe
Mikrowellen: Elektromagnetische Wellen
- Wellenlängen:1 m - 1 mm
- Frequenzen: 300 MHz - 300 GHz
Radiometer: Instrument zur (passiven) Messung elektromagnetischer
Strahlung
Bildgebender passiver Sensor
- Imager:
- Sounder:
Radar:
Sonar:
Instrument zur Messung von Profilen
RAdio Detection And Ranging
- aktives System, Detektion und Distanzmessung
- SAR:
Synthetic Aperture Radar
- SLAR:
Side-Looking Airborne Radar
- Altimeter:
Höhenmessung (nicht abbildend)
- Scatterometer: Messung der Rückstreuung (nicht abbildend)
SOund Navigation And Ranging
- Aktives System analog zu Radar, arbeitet mit Schallwellen
Department of Geography
Strahlengang bei einem passiven MikrowellenSystem
Department of Geography
Ursprung von passiven Mikrowellenstrahlen
Emitted from object:
!" z.B. Wärme-Abgabe, radioaktive Strahlung, Sonnenenergie
Emitted by atmosphere:
!" z.B. Polarlicht, chemische Prozesse wie Ozon-Abbau
Reflected from Surface:
!" Sonnenenergie
Transmitted from subsurface:
!" Erdstrahlen, radioaktive Strahlung, elektromagnetische Wellen
hervorgerufen durch seismische Phänomene
Department of Geography
Summary: Passive Microwaves Applications
Oceans:
!" Sea Surface Temperature & Salinity
!" Sea Ice
!" Surface wind velocities
Land:
!" Soil moisture
!" Snow melt & water equivalent
Atmosphere:
!" Water vapor
Department of Geography
Aktive Mikrowellen - Fernerkundung
Aktive Sensoren
!" Radar
!" Altimeter
!" Scatterometer
!" SLAR / SAR (abbildend)
Quelle der Strahlung
!" System selber
Vorteile
!" Unabhängig von Beleuchtung (Sonne) und somit Zeit (Tag/Nacht)
!" System-Design (Art der Quellstrahlung) ist definierbar
Department of Geography
Aktive Mikrowellen - Fernerkundung
Systeme mit realer Apertur
Systeme mit synthetischer Apertur
(Real Aperture Radar RAR)
Tracking Radars
Altimeter
Scatterometer
SLAR
SAR
Side-Looking Airborne Radar
Synthetic Aperture Radar
Abbildende Verfahren
Department of Geography
Aktive Mikrowellensysteme: Seitensichtradar
Department of Geography
Konzept-Vergleich: Synthetischen vs. Reale Apertur
Ein Radar mit synthetischer Apertur erlaubt eine sehr gute
Auflösung in Flugrichtung (Bewegungsrichtung des Sensors).
Dies wird durch synthetisches Zusammenfügen vieler Radarechos erreicht,
welche ein Objekt aus verschiedenen Winkeln zeigen.
Department of Geography
Vergleich SLAR- vs. SAR
Gurnigel, BE
Gute Auflösungen in beiden
Bilddimensionen
Bilder © RSL / Fraunhofer FHR
Department of Geography
Effekte der Geländegeometrie auf das SARRadarbild III
© University of California, Santa Barbara
Department of Geography
Reflexionseigenschaften und Eindringtiefen
Volumen-Streuung
volume scattering
Oberflächen-Streuung
Surface scattering
Doppelreflexion
double bounce
Department of Geography
Begriffe
LiDAR:
Light Detection And Ranging
- aktives System analog zu RADAR
- funktioniert im UV, VIS, IR Bereich
- primäre Anwendung: Distanzmessung
Laser:
ALS:
Light Amplification by Stimulated Emission of Radiation
- hohe Intensität, enger Frequenzbereich, grosse Koheränzlänge
Airborne Laser Scanning
- flugzeug oder helikoptergestütztes System
- Erstellung von Gelände und Oberflächenmodellen
Department of Geography
LiDAR & Laser Scanning - Unterschiede
LiDAR - nur Distanzmessung
topographic LiDAR - Distanzmessung + Position/Ausrichtung zur
Bestimmung einer Koordinate, profilierender LiDAR (z.B. GLAS,
SLICER)
(Airborne) Laser Scanning (ALS) - Distanzmessung + Position/Ausrichtung
+ Scanner, zur Strahlablenkung quer zur Flugrichtung, Abdeckung eines
Schwates
d.h. ein LiDAR ist Teil eines ALS, aber nicht das Gleiche!
Department of Geography
Range
Messprinzip III
First Echo
Full waveform
Last Echo
Intensity
Department of Geography
Oberflächen- und Terrain-Modelle
Digitales Geländemodell
(DGM)
Digitales Oberflächenmodell (DOM)
40
Department of Geography
Anwendungsbeispiele
GIS
Orthorektifizierung von Luftbildern
Infrastruktur und Planung
Gefahren- und Risikomanagement
Forstwesen
...
Referenzdaten fuer die SAR-Geokodierung
Überall dort wo eine präzise Modellierung der Erdoberfläche benötigt wird
Department of Geography
Anwendungsbeispiele
Messung der Ozonkonzentration in ...
–" ... bodennahen Luftschichten
–" ... der Stratosphäre
Detektion von Aerosolen
Detektion von Wasserdampf, Stickstoff und Schwefelverbindungen
Windmessungen (Doppler - LiDAR)
Department of Geography
Satellite Orbits
5/22/15
Page 43
Department of Geography
Terms & Definitions: Orbits
Inclination: orbit angle with respect to the equator
•"
near polar orbit = close to 90°
•"
equatorial orbit = 0°
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•" #$%&'(')%*(+,"%+-)'!".(/"012333"45"
•" &6*7&,*.8+%*%6&!"9337:33"45"
(')$*&!"%#0"&%)&/)012"%"&)3"&)+(#%&45)6&
•" ;(*<&('!"=3>"45?"@:/@"5)*A%+-)'?"B9/>"+$C%D6')%*&"E$+"<(,"
•" FGG!"933"45?"@H/:"5)*A%+-)'?"B>/9"+$C%D6')%*&"E$+"<(,"
+,%-#*)$-"./)*00$12.#$3'!"
•"
#$*$+(DD,"-$'I$$*"B3"(5"(*<"H"E5
5/22/15
Page 44
Department of Geography
Terms & Definitions: Sensor characteristics
Spatial resolution: ground surface area represented by one pixel
•"
Instantaneous field of view (IFOV)
•"
Ground sampling distance (GSD)
Temporal resolution: time between two image acquisitions for a given location
•" Revisit time or repeat cycle (measured in days)
Spectral resolution: number of spectral bands and their wavelength intervals
•" Panchromatic, multispectral, imaging spectroscopy
Radiometric resolution: effective bit-depth of the sensor
•"
Gain settings: range of brightness sensitivity
•"
Signal to noise ratio
5/22/15
Page 45
Department of Geography
Landsat 8 (Landsat Data Continuity Mission)
•" Launched: February 11, 2013
•" Scientific goal: Characterize and monitor
land-cover use and change over time
•" Applications: Carbon Cycle, Earth Surface,
Ecosystems, and Biogeochemistry
•" Sensors: Operational Land Imager
Thermal Infrared Sensor
•" Data: for the general public (no costs)
Department of Geography
Landsat 7: Spectral bands
0.42 – 0.52 µm
0.52 – 0.60 µm
0.63 – 0.69 µm
0.76 – 0.90 µm
1.55 – 1.75 µm
2.08 – 2.35 µm
10.4 – 12.5 µm
Department of Geography
MODIS (Moderate Resolution Imaging Spectroradiometer)
•" Launched: December 18, 1999 (1st of 2 sat.)
•" Scientific goal: provide measurements of
large-scale global dynamics
•" Applications: cloud cover, radiation budget
and oceanic terrestrial and lower
atmospheric processes
•" Sensor: multispectral radiometer
•" Data: for the general public (no costs)
Department of Geography
MODIS products overview
•
Surface temperature (land and ocean)
and fire detection;
•"
Ocean color, currents;
•"
Global vegetation and change maps;
•"
Cloud characteristics;
•"
Aerosol concentrations and properties;
•"
Temperature and moisture soundings;
•"
Snow cover and characteristics;
5/22/15
Page 49
Department of Geography
ESA’s Earth Observation Programme
5/22/15
Page 50
Department of Geography
MERIS!
MEdium Resolution Imaging
Spectrometer!
ASAR!
Advanced Synthetic Aperture
Radar!
GOMOS!
Global Ozone Monitoring by
Occultation of Stars!
AATSR!
Advanced Along Track
Scanning Radiometer!
RA-2!
Radar Altimeter 2!
SCIAMACHY! SCanning Imaging Absorption
SpectroMeter for Atmospheric
CartograpHY!
MIPAS!
Michelson Interferometer for
Passive Atmospheric Sounding!
MWR!
MicroWave Radiometer!
LRR!
Laser RetroReflector!
DORIS!
Doppler Orbitography and
Radiopositioning Integrated by
Satellite!
Department of Geography
ESA’s Earth Explorers
Objective:
Satellit
Better understanding of
Earth Science in various
GOCE
fields of interest based on
innovative satellite
SMOS
technology
Ziel der globalen
Forschungen
Start
Bestimmung des
Erdschwerefeldes
17.03.2009
Bodenfeuchte,
Salzgehalt der Meere
02.11.2009
CryoSat
Erfassung der planetaren
08.04.2010
Eismassen
SWARM
Erdmagnetfeld und Klima 22.11.2013
ADM-Aeolus
Dynamik der
Erdatmosphäre
2015 (geplant)
EarthCARE
Wolken und Aerosole
2016 (geplant)
Biomass
Biomasse der Wälder
2020 (geplant)
Department of Geography
VHR satellite imagery - Applications
Defense & Security
Oil, Gas, Mining
Civil Engineering
Agriculture
Mapping & 3D
Forest & Environment
Disasters & Crisis
Culture & Heritage
Department of Geography
Very high resolution satellites
Satellite
Organization
Launch date
IKONOS
GeoEye
1999
Quickbird (3x)
DigitalGlobe
2001-2008
WorldView-1, 2, 3
DigitalGlobe
2007, 2009, 2014
Cartosat-2 (2x)
ISRO
2007-2010
GeoEye-1
GeoEye
2008
Pleiades (2x)
CNES
2011-2012
Skysat 1-2 (15x)
Skybox Imaging
2013-2014
Copernicus pillars
Department of Geography
European
independence &
contribution to global
observing system
Space
Component
Global, timely and
easily accessible
information
In-Situ
Component
5/22/15
Services
Component
Page 55
The Sentinel Family
Department of Geography
Sentinel 1 – SAR imaging
All weather, day/night applications, interferometry
2014 / 2015
Sentinel 2 – Multi-spectral imaging
Land applications: urban, forest, agriculture,..
Continuity of Landsat, SPOT
Sentinel 3 – Ocean and global land monitoring
Wide-swath ocean color, vegetation, sea/land
surface temperature, altimetry
Sentinel 4 – Geostationary atmospheric
Atmospheric composition monitoring, transboundary pollution
Sentinel 5 / 5P – Low-orbit atmospheric
Atmospheric composition monitoring
(S5 Precursor launch in 2015)
2015 / 2016
2015 / 2017
2020
2015, 2021
Department of Geography
Spectral bands: Sentinel-2 vs. Landsat-8
Department of Geography
Sentinel-1 applications: (1) Land
5/22/15
Page 58
Department of Geography
Sentinel-1 applications: (2) Sea
5/22/15
Page 59
Department of Geography
Sentinel-2 applications
Agriculture, Forestry and Range
!" e.g. discriminating vegetation type & state
Land Use/Cover Changes
!" e.g. monitoring urban growth
Geology
!" e.g. mapping geologic landforms
Hydrology
!" e.g. determining snow and ice cover
Coastal Resources
!" e.g. tracking shoreline erosion and flooding
Environmental Monitoring
!" e.g. monitoring deforestation
5/22/15
Page 60
Department of Geography
Sentinel-3 applications
Marine and Coastal Environment
!" e.g. Sea-surface topography &
temperature, circulation, water quality,
wave height
Polar Environment
!" e.g. Sea-ice thickness
Global Change Ocean
!" e.g. Sea-level rise, CO2 flux
Land Cover & Land-Use Change
!" e.g. Forest monitoring, land-use
mapping
Risk Management
!" e.g. Fire detection, Burnt area mapping
5/22/15
Page 61
Department of Geography
Histogram or Contrast stretching
DR sensor (0-255)
DR display (0-255)
DR sensor (60-158)
DR display (0-255)
Lillesand Fig. 7.13
Department of Geography
Level slicing
•" Discontinuous color mapping
•" Subdividing the continuous range of values into discontinuous but
sequential groups (called bins or classes)
•" Simplest way of making classes based on spectral values
0 – 10
aquamarine
11 – 50
sienna
51 – 100
dark green
101 – 255
color scale light
green to white
Department of Geography
Band combinations
Each spectral band represents a grey-scale image. Three of these bands
can be assigned to the display colors red (R), green (G) and blue (B) to
obtain a full-color image.
3 bands, 0-255 each = 24 bit ‘color depth’
(16.7 million colors)
blue
green
red
Department of Geography
False-color images using 7 Landsat bands
Landsat bands
1 0.45-0.52 "m
2 0.52-0.60 "m
3 0.63-0.69 "m
4 0.76-0.90 "m
5 1.55-1.75 "m
6 10.40-12.50 "m
7 2.08-2.35 "m
Blue
Green
Red
Near IR
Mid-IR
Thermal IR
Mid-IR
Department of Geography
Maximizing spectral contrast
Green, dense
Red
Infrared
For vegetation:!
•"
Reflectance is highest in NIR and
lowest in RED!
•"
The ratio NIR / RED gives therefore
the highest contrast and the best
way to quantify changes!
••"
!
!
This ratio changes under stress
stress!
Brown or sparse
Red
Infrared
Department of Geography
Spatial Image Filtering
•" Filtering manipulates the image elements
•" Filters are applied using kernels composed of size and weights
•" Most common in image analysis: high-pass and low-pass filters
Department of Geography
High-pass filter (sharpening)
•" Used to enhance high-frequency variations
•" Disadvantage: enhances noise as well
•" Kernel typically has high central value surrounded by
(partially) negative weights; sum is 0 or higher
•" Special case: Laplacian (2nd derivative) filter
0 -1 0
-1 5 -1
0 -1 0
Department of Geography
Low-pass filter (smoothing)
•" Used to suppress high-frequency variation and noise
•" Kernel with small positive values. Simplest case: all
values (1 / kernel size) and thus sum equals 1
•" Kernel size (3x3, 5x5, !) determines degree of smoothing
•" Special case: Gaussian filter (or “Gaussian blur”)
1/9 1/9 1/9
1/9 1/9 1/9
1/9 1/9 1/9
Department of Geography
Classification methods
Albertz, 2001
Unsupervised classification
Supervised classification
Clustering, (Segmentation)
...
Parallelepiped, Minimum distance,
Maximum likelihood
. . .
Department of Geography
Feature space: NIR vs RED
Department of Geography
Common classification algorithms: overview
Parallelepiped
Minimum Distanz
Maximum Likelihood
Department of Geography
Type 1 (commission) and type 2 (omission) error
Klassifikation
Referenz/ ground truth
Klassifikation
Referenz/ ground truth
A
B
C
D
"
A
15
0
0
0
15
B
0
9
0
0
9
C
3
1
24
2
30
D
0
0
0
10
10
"
18
10
24
12
64
Incorrectly classified
classification # reference
-"
Type 1:
Commission Error
Pixels were included in
the class, although they
should not have been
-"
Type 2:
Omission Error
Pixels were not
included in the class,
although they should
have been
Department of Geography
Producer‘s Accuracy (PA)
Klassifikation
Referenz
Klassifikation
Referenz/ ground truth
A
B
C
D
"
A
15
0
0
0
15
B
0
9
0
0
9
C
3
1
24
2
30
D
0
0
0
10
10
"
18
10
24
12
64
83.33
90
100 83.33
PA
The producer needs to
know how well her/his
classification (e.g. for
class A) matches with the
reference
== Omission Error
How many pixels should have
been in the class but were not
count of correctly classified pixels in class
Producer‘s
=
Accuracy
count of pixels in same reference class
=
15
= 0.8333
18
(~83.3%)
Department of Geography
User‘s Accuracy (UA)
Klassifikation
Referenz
Klassifikation
Referenz/ ground truth
A
B
C
D
"
UA
A
15
0
0
0
15
100
B
0
9
0
0
9
100
C
3
1
24
2
30
80
D
0
0
0
10
10
100
"
18
10
24
12
64
The user needs to know
how well a class (e.g. A)
matches with the reality
== Commission Error
How many pixels are in the
class but should not have been
count of correctly classified pixels in class
User‘s
=
Accuracy
count of all pixels in that class
=
15
15
=
1
(100%)
Department of Geography
Overall/ Total Accuracy (OA)
Klassifikation
Referenz
Overall
=
Accuracy
Klassifikation
Referenz/ ground truth
A
B
C
D
"
A
15
0
0
0
15
B
0
9
0
0
9
C
3
1
24
2
30
D
0
0
0
10
10
"
18
10
24
12
64
Count of correctly classified pixels
Grand total (total pixel count)
=
58
= 0.90625
64
(~90.6%)
Department of Geography
Accuracy metrics – OA, PA, UA
A
B
C
D
"
If I classified a pixel as forest
(A), there is in 100% of the
UA [%] cases indeed forest at that
location
15
0
0
0
15
100
Referenz/ ground truth
Klassifikation
Referenz
Klassifikation
A
B
0
9
0
0
9
100
C
3
1
24
2
30
80
D
0
0
0
10
10
100
"
18
10
24
12
64
PA [%] 83.33 90
100 83.33
OA [%] 90.63
I have captured 100% of the
existing arable land (C) with my
classification
But: 20% of the classified
arable land (C) pixels has
another land cover in reality
But: 16.67% of the existing
forest (A) was not captured
Department of Geography
Radialdeformation
Image taken on Sept. 23, 2001 from an altitude of 3,300 feet
using a Leica/LH systems RC30 camera
Department of Geography
Zentralperspektive und orthogonale Kartenprojektion
Quelle: Bundesamt für Landestopographie swisstopo und Grundlagen Luftbildmessung 2
Department of Geography
Stereoskopische Parallaxe und Höhenmessung
bg
hg
H1, H2
R
S
pS=pS1+pS2
#p1, #p2
#p=#p1+#p2
bp
f
#h
R’1, R’2
S’1, S’2
pR1, pR2
#P
Flugbasis
Flughöhe über Grund
Bildhauptpunkt
Kopfpunkt Objekt
Fusspunkt Objekt
Absolute Parallaxe für S
Parallaxdifferenz Objekt, LB1, 2
Parallaxdifferenz im Luftbildpaar
Photobasis
Brennweite
Objekthöhe
Kopfpunkt im Luftbild 1, 2
Fusspunkt im Luftbild 1, 2
Absolute Parallaxe für R
Parallaxdifferenz in der Bezugsebene S
(Gelände)
Parallaxe für R: pR = pR1-pR2
Parallaxe für S: pS = pS1-pS2
Parallaxedifferenz #p: pR-pS
#h=(#p*Hg)/pR

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