principals of remote sensing a user’s perspective jarlath o’neil-dunne source: nasa

Principals of Remote Principals of Remote SensingSensing

A User’s PerspectiveA User’s Perspective

Jarlath O’Neil-DunneJarlath O’Neil-Dunne

Source: NASA

Principals of Remote SensingPrincipals of Remote Sensing 04 Nov 200204 Nov 2002NR 143NR 143

OutlineOutline

• What is remote sensing

• Applications• Electromagnetic

spectrum• Data collection• Image display Source: NASA

http://snr.uvm.edu/sal/index.html


Remote sensingRemote sensing

Remote Sensing is a technology for sampling electromagnetic radiation to acquire and interpret non-immediate geospatial data from which to extract information about features, objects, and classes on the Earth's land surface, oceans, and atmosphere (and, where applicable, on the exteriors of other bodies in the solar system, or, in the broadest framework, celestial bodies such as stars and galaxies).

- Dr. Nicholas Short

Source: NASA



Remotely Sensed DataRemotely Sensed Data

Aerial Camera Radar SatelliteMultispectral Satellite Hyperspectral Sensor



ApplicationsApplications

Transportation– Updating road maps– Asphalt conditions– Wetland delineation

Source: Halcon




• Agriculture– Crop health analysis– Precision agriculture– Compliance mapping– Yield estimation

Clubroot disease

Source: NGIC




Natural Resource Management– Habitat analysis– Environmental

assessment– Pest/disease outbreaks– Impervious surface

mapping– Lake monitoring

Source: TRIC




National Security– Targeting– Damage assessment– Weapons monitoring– Homeland security– Navigation– Border disputes

Source: SPOT




Global Transparency– Weapons

proliferation– Environmental

degradation– Humanitarian

crisis– Independent

verification

© Space Imaging



Electromagnetic RadiationElectromagnetic Radiation

• Energy from the sun travels to Earth through space as electric and magnetic waves, or electromagnetic radiation.

• The range of electromagnetic radiation of various wavelengths and frequencies, extending from cosmic waves to radio waves, is known as the electromagnetic spectrum.

Radiation Source

Irradiance



Electromagnetic SpectrumElectromagnetic Spectrum

1 101 10 10 10 10 10 10 1010101010101010

Cosmic Rays VisibleNear IR

Thermal IR

Microwave

TV & RadioUV

X Rays

Blue - 0.4 - 0.5 umGreen - 0.5 - 0.6 umRed - 0.6 - 0.7 um

2 3 4 5 6 7 8-1-2-3-4-5-6-7

wavelength, m



Spectral Imagery RegionsSpectral Imagery Regions

Wavelength(Micrometers)

Ultra-Violet

Visible Near IR Shortwave IR Midwave IR

Longwave IR

Pan

chrom

aticB

lack &

Wh

ite F

ilm

Color Film

.01 .04 .07 1.0 3.0 5.0 14.00 um

Color IR Film

Spectral Imagery

Visile

Comprises 2%of EM Spectrum



ReflectanceReflectance

High

Low

Blue Green Red

Ref

lect

ance

0.4m 0.5m 0.6m 0.7m

White LightGreenGreen

BlueBlue

RedRed



Spectral Response CurvesSpectral Response Curves

50

40

30

20

10

0

0.4 0.6 0.7 0.8 1.3

Artificial turfAsphalt

Fallow field

Sandy loamy Soil

Concrete

REFLECTANCE

(%) Clear water

Wavelength (micrometers)

Grass

Visible0.5

GREENBLUE GREEN RED

Near IR



Spectral ResponseSpectral Response

© Space Imaging © Space Imaging

Green Reflectance NIR Reflectance



Passive DetectionPassive Detection

Camera or sensor

irradiancereflectance

emittance

scattering

transmittanceabsorptance



SensingSensing

Sensor array

Lens

225214

199198202

176

• Each “cell” recorded as a “digital number” (DN) or “brightness value”

• Measures amount of EM radiation

• The brighter the signal, the higher the value.



PixelsPixels

• Each cell is called a “picture element”, or pixel• Each pixel represents a single brightness value for a

specific geographical area

225 204 188 146

214 198 169 152

202 200 178 162

i columns

j row

s

i x j = 4 x 4 = 16 pixels

114 109 101 97



BandsBands50

40

30

20

10

0

0.4 0.6 0.7 0.8 1.3

Concrete

REFLECTANCE

(%)


Grass

Visible0.5

GREENBLUE GREEN RED

Near IR



Atmospheric WindowsAtmospheric Windows

Ultra Violet Visible Near -Mid Infrared Thermal IR

Wavelength, m

Landsat TM1 2 3 4 5 7 6



Band PlacementBand Placement

Wavelength, m

Landsat TM

RGB

100

50

0

25

75

Per

cent

Re

flect

ance

Near IR Mid IR

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

Silty-clay soilTurbid river water

Vegetation Clear river waterMuck soil

1 2 3 4 5 7

visible

1 2 3 4MSI

IKONOS & HI RESPAN

LANDSAT 7 PAN



Band DisplayBand Display

Band 1 Band 2 Band 3

Band 4 Band 5 Band 7

BLUE GREEN RED

NEAR IRSHORT

WAVE IRMID-

WAVE IR

NEAR IR



Color TheoryColor Theory

• All colors created from additive primary colors:

– Red– Green – Blue

• Complementary colors:– Magenta– YellowYellow– Cyan

Red Green

Blue

M C

YW

Black



Multispectral DisplayMultispectral Display

BLUEBLUE

GREENGREEN

REDRED NEAR IR SHORT

WAVE IRMID-

WAVE IRLONGWAVE IR

1Landsat TM Band 2 3 4 5 7 6

Band Combination = 7 4 2 (LANDSAT)

Color Guns =

Band Composite Output =


Band 3Visible Red

Band 2Visible Green

Band 1Visible Blue

Individual Landsat Bands

Applied to Color Guns

Resulting Image

Band 4Near Infrared

Band 3Visible Red

Band 2Visible Green

Individual Landsat Bands

Applied to Color Guns

Resulting Image


Sensor PropertiesSensor Properties

• Spatial resolution• Spectral resolution/#

bands• Radiometric resolution• Temporal resolution

Source: NASA



Spectral Resolution/# Spectral Resolution/# BandsBands

100s of BandsHyper-spectral

NIR SWIR LW IRSWIR

Band 2

.53-.62

Band 3

.63-.69

Band 1.45-.52

Visible

Band 4

.79-.90

Band 5

1.55-1.75

Band 7

2.08-2.35

Band 6

10.4-12.4

Near IR SWIR LWIR

1000s of BandsUltra-spectral

Multi-spectral



Spectral Resolution/# Spectral Resolution/# BandsBands

50

40

30

20

10

0

0.4 0.6 0.7 0.8 1.3

Concrete

REFLECTANCE

(%)


Grass

Visible0.5

GREENBLUE GREEN RED

Near IR



Radiometric ResolutionRadiometric Resolution

The ability of a sensor to perceive differences in brightness value levels

22 or 4 intensity levels

28 or 256 intensity levels

32

1

120

0

3 2

32

1

120

0

3 2

Sensor “A”

Sensor “B”

225190

72

12413763

0

255 141



Temporal ResolutionTemporal Resolution

1 ms1 ms

1 ms1 ms

1

minute

Sensor Aperture

““Scanner”Scanner” ““Starer”Starer”



Temporal ResolutionTemporal Resolution

2752 Km at the Equator

185 Km

Orbit 1, Day 1Orbit 2, Day 1Orbit 1, Day 8

Orbit 2, Day 8

Landsat



Trade-OffsTrade-OffsAerial Photo IKONOS Landsat

Spatial Resolution ½ m 4m 30m

# Bands 1 4 7

Radiometric Resolution

8 bit 11 bit 8 bit

Temporal Resolution On demand 3-4 days 16 days

© Space Imaging



The EndThe End

Source: Space Imaging


principals of remote sensing a user’s perspective jarlath o’neil-dunne source: nasa

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spot slide

tric slide

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nicholas short source

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