EG2211: Earth Observation

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EG2211 Earth Observation

• Interactions - Land
• Dr Mark Cresswell

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Topics

• Land surfaces
• Temperature and radiance
• Proxy air temperature
• Albedo
• NDVI
• Fires and volcanoes

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Land Surfaces

• Remote sensing provides a proxy for the nature of
  land surfaces
• We are interested in land cover rather than land
  use
• Different materials (land cover classes) absorb
  and reflect electromagnetic radiation differently
• We can infer land surface conditions from
  remotely sensed images

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Temperature and Radiance

• Infrared radiation is the key
• A region of the electromagnetic spectrum
  sandwiched between the red visible and microwave
  portions of the spectrum
• IR radiation is invisible
• 3 14µm is TIR (0.7 1.3µm is NIR, 1.3 3µm is
  MIR)
• Quantity of IR is related to radiance
• Radiance intensity is related to temperature

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Temperature and Radiance

• Detection of infrared energy is performed by the
  radiometer
• Measurement is the result of a current effect due
  to the direct interaction of photons with
  electrons present in the detector
• Operation of the detector requires that incident
  photons liberate charge-carrier electron

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Temperature and Radiance

• Different materials in nature absorb and emit
  thermal energy differently
• Differences are due to thermal capacity and
  ability to conduct as well as environmental
  parameters
• Water often has a high thermal capacity compared
  with bare soil so both materials are easily
  distinguished from one another

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TIR image
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Raw Meteosat Radiance image
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Proxy Air Temperature

• LST may be converted to a proxy air temperature
  by means of a solar correction algorithm
• Knowing the position of the Sun at the time an
  image is acquired allows the LST to be
  transformed into a proxy for air temperature
  (approx 1m above the ground)

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Albedo

• Albedo is simply the ratio of incoming radiation
  to reflected outgoing radiation expressed as

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Albedo

• Materials such as clouds and fresh snow have a
  HIGH albedo (they reflect much of the incident
  solar radiation back to space)
• Forests and soil have a low albedo (they absorb
  much of the incident radiation)
• We can classify materials according to their
  albedo

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VISIBLE

• Albedo
• Weather Fcst.

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NDVI

• Normalised Difference Vegetation Index
• NDVI provides a good assessment of
  photosynthesising vegetation but caution must
  be exercised with this type of index as other
  factors can affect the NDVI other than leaf
  reflectance Viewing angle, Soil background,
  Atmospheric degradation and Leaf orientation

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NDVI

• Often derived from NOAA-AVHRR satellite system
  (polar orbiter)
• Uses differential reflectance of visible and IR

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NDVI
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NDVI

• One of the problems associated with remote
  sensing vegetation is mixed pixels a
  combination of both soil and vegetation
• Hutchinson (1982) found that it was difficult to
  separate soil and vegetation reflectance when
  vegetation cover is less than 30.
• Solution is Perpendicular Vegetation Index (PVI)
  (Richardson and Wiegand, 1977)

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PVI (perpendicular vegetation index)
B dark wet soils C dry soils X pure
vegetation pixel Y mixed pixel
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Fires and Volcanoes

• Because of their thermal anomaly, fires and
  active volcanoes can be identified from space
• Acquisition of thermal infrared images allows
  fires to be detected automatically
• Time-series of images can show a trend in
  temperature beneath and surrounding a volcano
  that might allow a prediction of eruption to be
  made

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Volcanoes

• The moderate resolution imaging spectroradiometer
  (MODIS) instrument on board the NASA EOS
  platform, Terra gives global coverage every 1-2
  days at 250, 500 and 1000 metre resolutions
• Spectral data measured at 4µm and 12µm
• System examines scenes for high temperature
  volcanic thermal anomalies

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Volcanoes

• Once identified, details such as location,
  emitted spectral radiance and other parameters
  are transferred via the internet to the Hawaii
  Institute of Geophysics and Planetology
• Algorithms appear to be robust at detecting both
  permanent and sporadically active volcanic
  systems. See Wright et al. 2002

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Forest Fires

• A fire detection and management system should
  have the following aims
• A measure of the geographical limits of the
  fire-front
• An estimate of fire intensity
• Monitoring of burnt area to look for latent fires
• Mapping of burnt areas to aid restoration
• (Barducci et al. 2002)

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Boreneo Fires (Sep 18th 2005) NASA Earth
Observatory, 2005