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EGS 2013F > EGS Frank Week 4 Earth Observation > Flashcards

EGS Frank Week 4 Earth Observation Flashcards

1
Q

Overview P1/3

  • (1) There are numerous satellites providing () w. different () & ().
  • (2) These collect data in (), w. different () & ().
  • (3) Satellites can be distinguished by their ().
A
  • (1) There are numerous satellites providing data w. different specifications & capabilities.
  • (2) These collect data in different wavelengths w. different detail & frequency.
  • (3) Satellites can be distinguished by their different capabilities.
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2
Q

Overview P2/3

  • (4) Satellite instruments collect () in many diff. () from the () to the (), which allows the detection of diff. () w. diff ().
  • (5) The number of bands refers to ().
  • (6) Whilst the amount of detail present in the figures refers to ().
A
  • (4) Satellite instruments collect light in many diff. wavebands from the short blue wavelength to the long thermal wavelength, which allows the detection of diff. earth surface features w. diff. characteristics.
  • (5) The number of bands refers to Spectral Resolution.
  • (6) Whilst the amount of detail present in the figures refers to Spatial Resolution.
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3
Q

Overview P3/3

  • (7) Satellites also have diff. orbits, such as a () orbit & a () orbit.
  • (8) The type of orbit has an influence on the () & the (), as well as the ().
  • (9) Satellites can be used to study 1. (), 2. (), & 3. (), as well as 4. (), & 5. ().
A
  • (7) Satellites also have diff. orbits, such as a Polar/Sun-synchronous & a Geostationary orbit.
  • (8) The type of orbit has an influence on the Spatial Resolution & the Temporal Resolution, as well as the Coverage.
  • (9) Satellites can be used to study 1. Vegetation, 2. Land use & 3. Land Cover, as well as 4. Measure temperature & 5. Detect fires
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4
Q

What is the Spatial Resolution of a satellite sensor:

  1. Definition
  2. High Spatial Resolution ():
  3. Low Spatial Resolution ():
A
  1. Defines the abilitity to resolve features depending on their size.
  2. High Spatial Resolution (30m & better):
    Shows great detail, i.e. small no. 1m, e.g. google maps
  3. Low Spatial Resolution (30m & less):
    Shows less detail, i.e. high number 1000m, e.g. weather looking @ big cloud formations
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5
Q

What is the Temporal Resolution of a satellite sensor:

  1. Definition
  2. Example of High Temporal Resolution
  3. Example of Low Temporal Resolution
A
  1. Refers to how often a satellite instrument crosses over the same point
  2. 30 minutes
  3. 1-30 days
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6
Q

What is the spectral resolution of a satellite sensor:

  • Definition:
  • Example:
    (1)
    (2)
    (3)
    (4)
    (5)
A
  • Refers to the no. & location of wavebands
  • Example:

(1) Ultraviolet (0.1-0.4 um)

(2) Visible (0.4-0.7um

(3) Near Infrared (0.7-1.5um)

(4) Thermal Infrared (1.5-11um)

(5) Microwave (1mm-1cm)

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7
Q

Electromagnetic Spectrum (EMS):

  • Remote Sensing uses the () that is () & () from Earth @ () of the EMS
  • Blue band & Green band able to detect ()
  • Red band able to detect ()
  • NIR4:
A
  • Remote Sensing uses the radiant energy that is reflected & emitted from Earth @ various “wavelengths” of the EMS
  • Blue band & Green band able to detect sediment in water
  • Red band able to detect water bodies in more detail
  • Even more contrast, able to detect sediment, water & vegetation better
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8
Q

What are the major orbits used in remote sensing?

A
  1. Polar/Sun-synchronous
  2. Geostationary
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9
Q

Orbits

  1. A
  2. O
  3. I
  4. C
  5. S
  6. T
  7. A
A
  1. Altitude
  2. Orbital period
  3. Iclination
  4. Coverage
  5. Spatial Resolution
  6. Temporal Resolution
  7. Application
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10
Q

Polar/Sun-synchronous Orbit:

  1. Altitude
  2. Orbital period
  3. Inclination
  4. Coverage
  5. Spatial Resolution
  6. Temporal Resolution
  7. Application
A
  1. Low Altitude (200-1500km)
  2. ~90 min
  3. ~90 degrees
  4. Global by successive orbits
  5. High Spatial Resolution: 1m & better
  6. Low Temporal Resolution: 1-30 days
  7. Land Resource Applications
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11
Q

Geostationary Orbit:

  1. Altitude
  2. Orbital period
  3. Inclination
  4. Coverage
  5. Spatial Resolution
  6. Temporal Resolution
  7. Application
A
  1. High Altitude (35,000km)
  2. 24 Hours
  3. 0 degrees
  4. Disk of the Earth
  5. Low Spatial Resolution: 1000m & less
  6. High Temporal Resolution: 30 min
  7. Meterological Applications & can be used as Relay Satellites & to Transmit Data.
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12
Q

Sensor Capabilities P1/5

Terra, Aqua MODIS:

  • Spatial Resolution:
  • Temporal Resolution:
  • Spectral Resolution:
  • Orbit Type:
  • Possible Applications:
A
  • Spatial Resolution: 250m
  • Temporal Resolution: 2x Day AM. PM.
  • Spectral Resolution: VIS, NIR, TIR - 35 Channels
  • Orbit Type: Polar
  • Possible Applications: Global Weather Patterns, Fire, Ice, Dust, Snow, Vegetation (NDVI)
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13
Q

Sensor Capabilities 2/5

Landsat 1, 2, 3 MSS:

  • Spatial Resolution:
  • Temporal Resolution:
  • Spectral Resolution:
  • Orbit Type:
  • Possible Applications:
A
  • Spatial Resolution: 80m
  • Temporal Resolution: 18 days
  • Spectral Resolution: VIS, NIR - 4 Channels
  • Orbit Type: Polar
  • Possible Applications: Land Resource Mapping, Study of long term land coverage change (NDVI)
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14
Q

Sensor Capabilities 3/5

Landsat 4, 5, 6, 7 TM, ETM:

  • Spatial Resolution:
  • Temporal Resolution:
  • Spectral Resolution:
  • Orbit Type:
  • Possible Applications:
A
  • Spatial Resolution: 30m
  • Temporal Resolution: 16 days
  • Spectral Resolution: VIS, NIR, TIR - 8 Channels
  • Orbit Type: Polar
  • Possible Applications: Land Resource Mapping, Study of long term land cover change (NDVI)
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15
Q

Sensor Capabilities 4/5

Landsat 8:

  • Spatial Resolution:
  • Temporal Resolution:
  • Spectral Resolution:
  • Orbit Type:
  • Possible Applications:
A
  • Spatial Resolution: 30m
  • Temporal Resolution: ** 2 x month**
  • Spectral Resolution: VIS, NIR, TIR - 8 Channels
  • Orbit Type: Polar
  • Possible Applications: Land Resource Mapping, Study of long term land cover change (NDVI)
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16
Q

Sensor Capabilities 5/5:

Meteosat:

  • Spatial Resolution:
  • Temporal Resolution:
  • Spectral Resolution:
  • Orbit Type:
  • Possible Applications:
A
  • Spatial Resolution: 1000m
  • Temporal Resolution: 15 min
  • Spectral Resolution: VIS, NIR, TIR - 3 channels
  • Orbit Type: Geostationary
  • Possible Applications: Global Weather Patterns. Europe, US, China, India & Japan produce global coverage.
17
Q

Wien’s Displacement Law

  • States:
  • Used to identify:
  • Formula:
  • Example of Formula:
  • () of () is () proportional to ().
  • Hotter Object:
  • Colder Object:
A
  • States: The radiation peaks are inversely proportional to the temperature.
  • Used to identify: wavelength @ which max. emission of radiation occurs (for objects)
  • Formula: λmax = 2897/T
  • E.g.
    Sun = 2897/6000 = 0.5 um (Visible)
    & Earth = 2897/288 = 10 um (Thermal)
  • Wavelength of max. emission is inversely proportional to temperature.
  • Hotter Object: shorter wavelenghts
  • Colder Object: longer wavelengths
18
Q

What does NDVI stand for?

A

Normalized Difference Vegetation Index

19
Q

NDVI P1/2

  • Veg. is characterized by () in () in terms of () & doesn’t () a lot of () or ().
  • In (), veg. reflects () radiation/light -> therefore more reflection in () -> utilized to study veg.
  • In terms of non-veg = reflect () in ().
  • Veg. reflects () & absorbs () -> NDVI
A
  • Veg. is characterized by peaking in green in terms of visible light & doesn’t reflect a lot of red or blue.
  • In Near Infrared, veg. reflects more radiation/light -> therefore more reflection in NIR -> utilized to study veg.
  • In terms of non-veg. = reflect less in NIR
  • Veg reflects NIR & absorbs red light -> NDVI
20
Q

NDVI P2/2

  • Formula:
  • Health veg. reflectance =
  • Stressed veg. reflectance =
  • NDVI allows for the ()
  • NDVI collected over long time can allow the () & can be used to study ().
A
  • Formula:
    NDVI = NIR - Red/NIR + Red
  • Healthy veg. reflectance =
    1. 50% NIR & 8% Red
    2. 0.5 - 0.08/0.5 + 0.08
    3. NDVI = 0.72
  • Stressed veg. reflectance =
    1. 40% NIR & 30% Red
    2. 0.4 - 0.3/ 0.4 + 0.3
    3. NDVI = 0.14
  • NDVI allows for the quantification of the state of veg.
  • NDVI collected over long time can allow the detection of anomalies & can be used to study precipiation dymanics.
21
Q

How do we study fire?

  • By detecting the () emitted by the ().
  • Sensors like () can detect the () generated by fires & provide information on (), (), & ().
  • () -> shows as smoky clouds
  • () -> Red fire & blue smoke; much more visible
A
  • By detecting the thermal signature emitted by the flames.
  • Sensors like MODIS can detect the heat energy generated by fires & provide information on location, extent & intensity.
  • MODIS Visible Bands -> shows as smoky clouds.
  • MODIS Thermal Bands -> Red fire & blue smoke; much more visible

EGS 2013F (16 decks)

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