Optical Remote Sensing

GIMA: Geographical Information Management and Applications

False colour photograph (NIR – 1.0 µm)

Thermal infrared image (TIR – 10 µm)

Remote Sensing (Earth Observation)

Earth

Sensor at a distance

EM energy

Scanning systems

Opto-mechanical scanner (whiskbroom scanner): - image construction point by point - 1 line at a time - photon detectors

Linear array scanner (pushbroom scanner): - image construction line by line - CCD detectors

Progression sensor platform

2-dimensional image construction

Principles imaging sensor systems

Pushbroom scanner Whiskbroom scanner

digital recording analogue recording digital recording

scanning mirror shutter

“point” detector

aerial image plane line array detector

imaging optics imaging optics

Camera (aerial photography)

imaging optics

Remote sensing instrumentation

General concept

Terrain objects

Sens

or

Recorder Detector

angular aperture

IFOV

Instanteneous field of view - ground resolution element

β

IFOV= β*H (in Nadir!)

H

Collector

Ground receiving station

Active <-> Passive

RS using radiation emitted by objects: (PASSIVE)

RS using reflected solar radiation: (PASSIVE)

ACTIVE RS:

Lelystad Airport: Dornier (Foreground) Piper (Back)

Dornier (inside) with camera mount (foreground) and MSS-scanner (middle)

Multispectral scanner

Resolution concepts

Spectral resolution ● Band width in nm or Hz ● Mid-value ● Sensitivity curve

Spectral range

● Number and position of bands

λ 0

½

1

“50% - width”

sensitivity

0.3 µm 70 cm

IKONOS Multispectral bands

Resolution -2-

Spatial resolution ● Size IFOV or ● Pixel size in terms of terrain size

D = β·H at nadir ≥ β·H at oblique viewing angles

H

β

sens

or

radiometer

D ground resolution element (resolution cell)

β = angular aperture (mrad)

Example of resolution simulation

Resolution -3-

Radiometric resolution ● Smallest measurable step ∆Q ● Noise level Qmin

● Saturation level Qmax

● Dynamic range =10·log(Qmax/ Qmin) in dB

S

Q B Qmax

A Qmin

∆Q

Smax B’

Smin A’

∆S

AD conversion

• 6 bits: 64 digitization levels • 8 bits: 256 digitization levels • 10 bits: 1024 digitization levels • 12 bits: 4096 digitization levels

NOISE may be caused by: • sensor/imaging system • atmosphere • variability terrain object

76543210 Number 79: 01001111 How many bit levels are significant?

The position of the spectral bands of some Remote Sensing sensor systems in the optical window

wavelength (µm)

red middle-

infrared near- infrared bl

ue

gree

n

dry soil

water wet soil vegetation re

flect

ance

(%)

SPOT HRG Panchromatic

Pan: IKONOS, Quickbird, GeoEye, WorldView

Meteosat NOAA AVHRR

Landsat TM

40

20

0 0.8

60

0.4 1.2 1.6 2.0 2.4

SPOT HRG multispectral

Multispectral: IKONOS, Quickbird, GeoEye, WorldView

Some sensor specifications

Altitude (km) FOV (km) Radiometric resolution

(bits)

Spatial resolution (m)

nadir

Meteosat 36,000 hemisphere 8 2500/5000

NOAA-AVHRR 835 3,000 10 1100

Landsat-TM 705 185 8 30/120

SPOT (P/XS)

822 120 8 10/20

SPOT-Vegetation 822 2250 8 1165

IKONOS (P/MS)

681 11 11 1/4

QuickBird (P/MS) 450 14 11 0.6/2.4