Lecture 1 Introduction to Remote Sensing „Rules of the Game“

Sinnhuber & Bracher, Remote Sensing, University of Bremen, Summer 2008

Remote SensingSummer 2008

Björn-Martin Sinnhuber and Astrid BracherRoom NW1 - U3215Tel. 218 [email protected]@uni-bremen.de

www.iup.uni-bremen.de/~bms/remote_sensing


Lecture 1 Introduction to Remote Sensing

• „Rules of the Game“

• Examples of Remote Sensing Applications


General Principles of Remote Sensing


Lecture 2 Electromagnetic Radiation

Lecture 3 Radiative Transfer

Lecture 4 Satellite Remote Sensing

Lecture 5 Retrieval Techniques / Inverse Methods

Remote Sensing of the Atmosphere:

Lecture 6 Microwave Tehniques

Lecture 7 Infra-Red Techniques

Lecture 8 Spectroscopy

Lecture 9 Optical (UV / Visible) Remote Sensing

Lecture 10 Active Techniques and Meteorological Applications

Remote Sensing of the Ocean Surface:

Lecture 11 Sea Ice Remote Sensing

Lecture 12 Remote Sensing of Ocean Currents and SST

Lecture 13 Ocean Colour & Summary

Outline


General Information: „The rules of the game“

Lecture

• 13 lectures, every Monday 13:15-14:45

• ECTS: 4

• One „rapporteur“ gives brief summary (5 min.) of previous lecture. Mandatory for each student. Fix your date in the list (check on website)!

Exercises

• 10 exercises: turned out Mondays, given back next Monday, 10 points total for each exercise

• Exercises are discussed every Thursdays 13:15-14:00 (not 1st and last week, not holidays 1st and 15th May) with Gregor Kiesewetter ([email protected], phone: 2188689)

Exam

• Written exam 14 July 2008; 9:30-11:30

• Prerequisite: >70 points in all exercises and one report


Literature

• Charles ElachiIntroduction to the Physics and Techniques of Remote Sensing

• Graeme L. StephensRemote Sensing of the Lower Atmosphere

• Martin Seelye

An Introduction to Ocean Remote Sensing



• „Rules of the Game“

• Examples of Remote Sensing Applications


Photo taken

by crew of

Apollo 17

7 Dec 1972


from maps.google.com


A Note on Spatial Resolution

The maximum achievable resolution with an optical systemis given by

with α: opening angle, D: diameter of the optical aperture,λ: wavelength.

Because

with x: object size and h: sensor height we get

D

sin

h

xsin

D

hx

α

x

h

(Rayleigh criterion)


Resolution: An example

D

hx

Assume some typical values: h: 800 km, D: 4m (huge!),λ: 500 nm:

cm10m1.0m4

m10500m10800 93


ENVISAT: Launched 1 March 2002


MERIS/ENVISAT


SeaWIFS, 26. Feb. 2000

Sinnhuber & Bracher, Remote Sensing, University of Bremen, Summer 2008MERIS/ENVISAT, Cloud Top Pressure


Ocean colour: MERIS/ENVISAT, 443 nm


Ocean colour: MERIS/ENVISAT, 560 nm


Ocean colour: MERIS/ENVISAT, Chlorophyll


Absorption windows of atmospheric constituents


Observing the Ozone Layer

http://ww

w.iu

p.physik.uni-b

reme

n.de/g

ome

nrt/

Global measurements of total ozone columns

Measurement type: Satellite-based passive remote sensing

Instrument: Global Ozone Monitoring Experiment (GOME) / ERS-2

Measured quantity: Total ozone columns(from backscattered solar radiation)

Antarctic Ozone Hole


The Arctic Ozone Layer

Ten years of GOME observtions


The Electromagnetic Spectrum

100 m 10-4 cm-1

10 MHz

10 m 10-3 cm-1 Radio

100 MHz

1 m 10-2 cm-1

1 GHz

10 cm 0.1 cm-1

10 GHz Microwave 1 cm 1 cm-1

100 GHz

1 mm 10 cm-1

1 THz sub-mm – Far IR 0.1 mm 100 cm-1

10 THz

10 μm 1000 cm-1 Thermal IR

al IR 100 THz

Near IR 1 μm 104 cm-1

1000 THz Ultraviolet

100 nm 105 cm-1

Wavelength Frequency Wave number

Visible 400-700 nm


Solar Spectrum and Terrestrial Spectrum

Sun Earth

Short Wave Long Wave


MODIS / Terra, Gulfstream Temperature


AMSU-B Data (183 ±1 GHz)

Dry areas in the UT

(NOAA 16, Channel 18,

15.6.2004.

Figure: Oliver Lemke)

Microwave Remote Sensing


Satellite Limb Sounding

(Figure: Oliver Lemke)


Microwave Limb Sonder (MLS) onboard UARS


Airborne Microwave Remote Sensing


ASUR frequency range and primary species


A picture from the SOLVE campaignin Kiruna, Sweden, January 2000


Validation of satellite data is important ...


Ground-based Radiometer for Atmospheric Measurements (RAM)


Measured Microwave Spectrum by the RAM


Pressure Broadening of Spectral Lines

50km / 0.5 hPa

20km / 50 hPa

10km / 200 hPa


A Note on Profile Retrieval

Often we can describe the relation between the (unknown)atmospheric profile x and the measured spectrum y by alinear equation: Axy

The matrix A is also called as the weighting function matrix.Finding x from measured y would require inversion of A:

yAx 1

yAx g

However, this is generally not possible (inverse of A does not exist).Therefore one has to find some „generallized“ inverse of A:


Lidar In-space Technology Experiment (LITE)

on Discovery in September 1994 as part of the STS-64 mission

http://www-lite.larc.nasa.gov/index.html


Radar Image

ENVISAT ASAR

15 April 2005


Sea ice concentration fromAMSR-E 89 GHz

15 April 2007

www.seaice.de

courtesy of Lars Kaleschke



15 April 2007

www.seaice.de

False colour image




06 April 2008

www.seaice.de

False colour image



Example: SCIAMACHY Tropospheric NO2

biomass burningpollution

Courtesy of Andreas Richter


• NO2 reductions in Europe and parts of the US

• strong increase over China

• consistent with significant NOx emission changes

• 7 years of GOME data

• DOAS retrieval + CTM-stratospheric correction

• seasonal and local AMF based on 1997 MOART-2 run

• cloud screening

1996 - 2002

GOME annual changes in tropospheric NO2

GOME NO2: Temporal Evolution

A. Richter et al., Increase in tropospheric nitrogen dioxide over China observed from space, Nature, 437 2005

Lecture 1 Introduction to Remote Sensing „Rules of the Game“

Documents

Transcript of Lecture 1 Introduction to Remote Sensing „Rules of the Game“