introduction on remote sensing - fotografie.hfg...

e-GEOS

Legal OfficeContrada Terlecchie 75100 Matera - Italy

Headquarters Via Cannizzaro 7100156 Roma - Italy

Introduction on Remote Sensing

Axel Oddone

Head of Collection Planning and Data Access Services

e-GEOS Proprietary June 22, 2010

History of Remote Sensing



• Invention of Photography and the Camera over 150 years ago

• 1858: first aerial photograph from a hot-air balloon (Bièvre, France)



• 1906: first “aerial photo” (San Francisco earthquake, using 17 kites)



1903, Bavaria



• 1903: Wright brothers first flight

• 1909 William Wright took first image from an airplane (Centocelle, Italy)

• More than 1,000,000 aerial pictures acquired in World War 1, especially by UK, France and US



• In Wold War 2 intensive use of aerial photography for all the players

• UK developed radar systems for aircraft and ship detection

• First camera on a rocket: captured German V2 launched in US



• October 1957: Soviet Union launches the first satellite, the Sputnik-1

• February 1958: first US satellite, the Explorer-1

• August 1960: first spy satellite, start of the US Corona program

• April 1962: first Soviet Union spy satellite, the Zenit-2

• Rush in the development of aerial and satellite systems for militar Earth Observation: Cold War



• Non military EO satellites:

– 1960: the US weather satellite TIROS-1

– 1960s: the various Apollo missions (1969 Apollo-11 on the Moon)

– 1972: the first satellite of the new era for EO, the US Landsat

– 1979: starts the NOAA / AVHRR global monitoring of weather and

vegetation

– 1981: starts the Space Shuttle program

– 1986: the first non-US EO satellite, the French SPOT

– 1991: the first ESA radar satellite, ERS-1

– 1999: starts the new era of Very High Resolution, with the launch of

IKONOS-2

– 2007: starts the new era of Very High Resolution SAR, with the launch of

COSMO-SkyMed 1


Landsat 1 MSS image, 26 June 1976

© ESA


Declassified US military images

Keyhole-7, 20 Mar 1966 Corona, 25 Sep 1967


GeoEye-1, 19 September 2009

© GeoEye


http://peacesong.bobsinclar.com/

GeoEye-1, 19 September 2009


24 acquisitions over Beijing

e-GEOS Proprietary June 22, 2010© DigitalGlobe


24 acquisitions over Beijing

Please, never ask for a similar acquisition!


GeoEye-1: Washington DC - January 20, 2009

© GeoEye


GeoEye-1: Ad Dakhla, 8 May 2010

© GeoEye


Theory


Remote Sensing

• The mixture of techniques, instruments and interpretation tools that allow to get from a distance qualitative and quantitative information about objects and processes, without touching them

• RS is all about deriving information about a feature, analyzing the energy reflected or emitted from it

• Sources of energy:

– Natural: Sun, every object, …

Passive sensors (e.g. optical satellites)

– Artificial: flash, lamp, radar signal, …

Active sensors (e.g. radar satellites)


Active and Passive sensors


Electromagnetic Spectrum


Who sees thermal infrared information?

• A snake

• A mosquito

• A special camera

• A Terminator!


Electromagnetic energy and the atmosphere


Atmospheric scattering

• Redirection of electromagnetic energy by suspended particles (e.g. dust and smoke) and large molecules of atmospheric gasses (e.g. water vapor)

• Depends on

– size and abundance of particles

– wavelength of radiation

– Distance radiation travels within atmosphere

• Effects:

– Visibility in shadows

– Blue sky

– Orange/Red sunrise and sunset

– Reduces contrast in RS images (especially in Blue field)

Photo © Axel Oddone


Atmospheric absorption

• Energy absorbed by the atmosphere, subsequently reradiated at longer wavelengths

• 3 atmospheric gases account most absorption:

– Water vapor (H2O), most important

– Carbon dioxide (CO2)

– Ozone (O3)

• Water vapor content depends on:

– Region and Season

– Day time

• Effects:

– Severe limitation of imaging over “humid” areasPhoto © Axel Oddone


Atmospheric windows

• Transmission of the Earth’s atmosphere varies with wavelength:



Bodies behaviour

ENERGY

FROM THE SUN

Energy absorbed

Energy transmitted

Energy reflected



Bodies behaviour


Spectral signature


From energy to image


Classical Photography

• Film used to detect and record the image

• Chemical reaction (oxidation) that varies according to energy (light) intensity

• Smooth image due to random position of sensible crystals

• Possibility to have 1 layer (B&W) or 3 layers (Color) film


The Russian Kometa mission

• 17 Feb 1998: Soyuz-U booster launches the

Kometa spacecraft

• 3 Apr 1998: recovery of the module with the exposed film in the taiga forest


Digital Photography

• Instead of a film, there is a digital sensor, composed by a regular grid of detectors

• Each detector evaluates the level of energy that it receives

• The information is stored in a digital memory

• Through the use of a software, the information stored in the memory generates an image composed by pixel (= picture element)

Example: 12.1 Mpx


RGB: digital photography

Sensor

1 x 1 mm


Digital Scanners

• Instead of a grid of detectors, there is a linear array of detectors

• The scanning is done through the movement of the platform where the detectors are, in 2 modalities:

– Fixed lines (pushbroom)

– Strips through an optical / mechanical movement (whiskbroom)

• Possibility to have 1 or more arrays working simultaneously


RGB: multispectral scanner

Red

Green

Blue

RGB


RADAR sensors

• RADAR = RAdio Detecting And Ranging

– Active instrument (has its own source of Energy)

– The image is created by interpreting the quantity of Energy returned (back-scattered) to the satellite and the time the signal needed to come back

• Generally the radar systems are composed by a transmitter and a receiver that use the same antenna, which changes continuosly and very quicly between the 2 modes


Who else has a “radar”?

• A bat

• A shark

• A jet fighter


RADAR sensors


Which microwaves?


Which microwaves?

Band Name Frequency Range Wavelength Range Notes

HF 3–30 MHz 10–100 m coastal radar systems, over-the-horizon (OTH) radars; 'high frequency'

P < 300 MHz 1 m+ 'P' for 'previous', applied retrospectively to early radar systems

VHF 50–330 MHz 0.9-6 m very long range, ground penetrating; 'very high frequency'

UHF 300–1000 MHz 0.3-1 m very long range (e.g. ballistic missile early warning), ground penetrating, foliage penetrating; 'ultra high frequency'

L 1–2 GHz 15–30 cm long range air traffic control and surveillance; 'L' for 'long'

S 2–4 GHz 7.5–15 cm terminal air traffic control, long range weather, marine radar; 'S' for 'short'

C 4–8 GHz 3.75-7.5 cm Satellite transponders; a compromise (hence 'C') between X and S bands; weather

X 8–12 GHz 2.5-3.75 cm missile guidance, marine radar, weather, medium-resolution mapping and ground surveillance; in the USA the narrow range 10.525 GHz ±25 MHz is used for airport radar. Named X band because the frequency was a secret during WW2.

Ku 12–18 GHz 1.67-2.5 cm high-resolution mapping, satellite altimetry; frequency just under K band (hence 'u')

K 18–27 GHz 1.11-1.67 cm from German kurz, meaning 'short'; limited use due to absorption by water vapour, so Ku and Ka were used instead for surveillance. K-band is used for detecting clouds by meteorologists, and by police for detecting speeding motorists. K-band radar guns operate at 24.150 ± 0.100 GHz.

Ka 27–40 GHz 0.75-1.11 cm mapping, short range, airport surveillance; frequency just above K band (hence 'a') Photo radar, used to trigger cameras which take pictures of license plates of cars running red lights, operates at 34.300 ± 0.100 GHz.

mm 40–300 GHz 7.5 mm - 1 mm millimetre band, subdivided as below. The letter designators appear to be random, and the frequency ranges dependent on waveguide size. Multiple letters are assigned to these bands by different groups. These are from Baytron, a now defunct company that made test equipment.

Q 40–60 GHz 7.5 mm - 5 mm Used for Military communication.

V 50–75 GHz 6.0–4 mm Very strongly absorbed by the atmosphere.

E 60–90 GHz 6.0–3.33 mm

W 75–110 GHz 2.7 - 4.0 mm used as a visual sensor for experimental autonomous vehicles, high-resolution meteorological observation, and imaging.


RADAR

• The backscattering of any surface depends from the electromagnetic energy emitted from the radar sensor:

– Frequency and amplitude

– Polarization and phases

– Direction of the signal (viewing angle)

• And from the surface structure:

– Roughness

– Humidity

– Resistivity

– Texture

– Position

e-GEOS Proprietary June 22, 2010Envisat © ESA


Satellite Orbits


Orbits

• Speed / height of satellite depends on Gravitation law (Newton)

• Elliptical orbits (Kepler’s laws)

• 2 possibilities:

– Geostationary orbits

– Polar orbits


Geostationary Orbits


Orbits

• Geostationary orbits

– 36 000 Km height

– Lower resolution

– Fixed view

– Full 24 hrs visibility

• Used for

– Meterological satellites

– TV & Telecom


Polar Orbits - 2


Orbits

• Polar orbits

– 300 – 1 000 Km height

– Higher resolution

– Full Earth visibility in a certain number of days

– Generally sun-synchronous• Descending orbit Day

• Ascending orbit Night

• Used for

– EO satellites

– Militar satellites


Resolution


Resolutions

• Spatial Resolution

– Ground Sample Distance (GSD)

– Image size

• Radiometric and Spectral Resolution

– Number and typology of bands

– Bit depth

• Temporal Resolution

– Revisit

– Satellite programming and data reception

– Clouds


Spatial Resolution

• Ground Sample Distance (GSD)

– A pixel size of n meters means that every pixel represents a surface on the ground of n x n m2

– Each detector reads all the information that comes from an n x n m2 surface and mixes everything into a single digital information

• “Resolution”

– The smallest feature discernable in an image


GSD: 1 Km

1 Km


GSD: 30 meters

1 Km


GSD: 60 cm

1 Km

© DigitalGlobe


GSD: 1 Km

700 Km


GSD: 30 meters

21 Km

© ESA


GSD: 60 cm

0.42 Km

© DigitalGlobe


Detectability: a 60 cm example

© DigitalGlobe


Image size

• The smaller the resolution, the bigger the image size:

Sensor GSD Swath width

NOAA / AVHRR 1 Km 3,000 Km

Spot Vegetation 1 Km 2,250 Km

Landsat TM 30 m 180 Km

Spot HR 10-20 m 120 Km

QuickBird 0.6 m 16.5 Km


Image size


Spectral Resolution

• Every optical sensor is composed by a certain number of spectral bands or channels, each one tailored to a specific interval of the electromagnetic spectrum


Spectral Resolution

• In order to increase the resolution, but not the complexity of the instrument and the volume of the raw data, some satellites have:

– 4 or more Multispectral bands

– 1 Panchromatic band at a higher resolution

• WorldView-2 has 8 MS bands @ 2 m GSD


Data fusionMultispectral @ 2.4 m Panchromatic 0.6 m

© DigitalGlobe© DigitalGlobe


Data fusionPansharpened @ 0.6 m

© DigitalGlobe


Radiometric Resolution

• More bits more information…

Sensor Bit depth

NOAA /AVHRR 10 bit

Spot Vegetation 10 bit

Landsat TM 8 bit

Spot HR 8 bit

QuickBird 11 bit


Radiometric Resolution

• More bits more information…

Yong Byong, North Korea,

2 March 2002 © DigitalGlobe


Satellite programming and data reception

• 2 possible acquisition modes:

– Fixed

– Targeted

• Direct downlink or use of on-board memory

• Receiving Stations

• Revisit

• Viewing Angle

• Clouds


Fixed Acquisitions


Targeted Acquisitions


Satellite programming and data reception

• 3 possible downlinks of the images:– Continuos acquisition & downlink when visibility of a Receiving station

• e.g. Meteosat, NOAA/AVHRR, Landsat 1-5

– Use of a Tracking and Data Relay Satellite System (TDRSS)• e.g. Envisat with Artemis

– Use of on-board memory• e.g. Landsat 7, Spot, QuickBird, GeoEye-1

Landsat 5 present

IGS network


Temporal Resolution

• Revisit = how much time does the satellite need to see again the same target

– Fixed view:• METEOSAT 15 - 30 min

• NOAA / AVHRR 2 times / day (@ 45° latitude)

• SPOT VEGETATION 1 - 2 day

• LANDSAT 16 days

– Targeted:• SPOT HR 1 - 2 day (@ 45° latitude, using 3 satellites)

• QUICKBIRD 4 days (@ 45° latitude)


Viewing Angle

• Sensors fixed at nadir have no prospective distortion, except at the edges of some very large swaths

• Targeted sensor may have very significant prospective distortion

© DigitalGlobe


Clouds

• Optical satellites have 1 big problem: clouds!

• Solutions:

– See catalogue before buying

– Use a combination of acquisitions (e.g. decades)

– Task only when you are quite sure about weather (VHR targeted satellites guarantee max 20% cloud cover)


Future ?


Higher Resolutions

• GeoEye-2 (to be launched end of 2012): maybe up to 25 cm


Competition with aerial photography

Google, Mountain View, CA


3D and Visualization


GoogleEarth


Google Street View


Microsoft VirtualEarth (now Bing Maps)


Pictometry oblique views


Google Sketchup 3D


Rome Reborn Project


C3 Technologies

http://www.yell.com/maps


Need of DEM

• DTM = Digital Terrain Model

• DEM = Digital Elevation Model


What is a DEM?

• A file containing elevation values distributed on a uniform grid of an area of interest

• It can be represented as a raster image or as a vector triangular shape

• Important to know:

– Post spacing (i.e. similar to optical resolution)

– X-Y geolocation accuracy

– Z vertical accuracy


• High resolution

• Color

• 3-dimensional

• Applications

– DEM extraction

– 3D feature extraction

– Geomorphic visualization

In-track Stereo


VHR DEM from QuickBird pseudo-stereo acquisition


Lidar DEM (radar from aerial)


Example of SAR applications


Monitoring of flooding near Pisa for Italian Civil Protection

December 29, 2009 December 31, 2009

Adverse weather conditions


COSMO-SkyMed acquisitions

• GeoEye-1: archive reference image • COSMO-SkyMed: 5 image monitoring between Dec 28th - Jan 1st• Data co-registration and semi-automatic classification

e-GEOS

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Headquarters Via Cannizzaro 7100156 Roma - Italy

Massaciuccoli lake

Viareggio

© e-GEOS / GeoEye


Hydrography

Flood area on Optical image (5 m)In dry season, the flood area is bordered by two dams on the east and by reliefs on the north.

Touloum area

© SpotImage


Flood area on radar image (HH SM) (march)In the end of dry season, it remains a little flood surface near dams.

Touloum area

sensor orientation

Flood area

Flood area

Hydrography

© ASI


Flood area on radar image (VV SM) (september)In rainy season, the reservoir has spread beyond the observed limits on Spot image.

Touloum area

Flood area

reservoir

sensor orientation

Hydrography

© ASI


Support to Siberia expedition


Ob winter crossing near Salekhard


Support to Siberia expedition


Perito Moreno Glacier


Perito Moreno glacier - ArgentinaSatellite: Cosmo SkyMed-1Date: 2009/02/02Mode: Spotlight 2Incidence angle: 40°Polarization: VVLooking side: RightOrbit direction: Ascending Product: GTC (level 1d)Corrected with SRTM90

© ASI


Satellite: Cosmo SkyMed-1Date: 2009/02/18Mode: Spotlight 2Incidence angle: 40°Polarization: VVLooking side: RightOrbit direction: Ascending Product: GTC (level 1d)Corrected with SRTM90

Perito Moreno glacier - Argentina

© ASI


PS-IFSAR analysis

• Shanghai

– Stripmap H4-0B acquisition mode

– Ground resolution 3 m x 3 m

– Polarization HH

– Incidence angle 23.96°

– Right looking, descending pass

– Analyzed period: May. 2008 – Dec. 2009

– Number of acquisitions: 36

© ASI


Shanghai: PS heights

Height (m)


Tall buildings: PS heights 3D view

Height (m)


Shanghai: PS mean velocities

Mean velocity(mm/year)


Detection of land movements


Subsidence in the Gulf of Naples

• Measurements from 1992-1999

•Underground Construction work


Optical reference image (Google)


Cosmo multitemporal combination

29/12/09

30/12/09

06/01/10


Village growth

29/12/09

30/12/09

06/01/10


Multitemporal overlayed on CSK DTM

Derived from a tandem interferometric pair; 5 meters posting


Which roads are used?


Incoherence map

IncoherenceJan 1-9

IncoherenceJan 9-10


incoherence map: road colours

IncoherenceJan 1-9

IncoherenceJan 9-10

“black” roads

“white” roads

“red” roads White road:

used Jan 1-10

Red road:

used Jan 1-9

not used Jan 9-10

Black road:

not used Jan 1-10


Road use map

Used Jan, 1-10

Used Jan, 1-9, not used Jan 9-10

Not used Jan, 1-10


Louisiana oil spill


Lousiana – June 1, 2010


Detail


Questions ??Questions ??


Thank you for your attention!

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