EG5503: GIS & Earth Observation
Earth Interactions
Dr Mark Cresswell
Topics
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Land surfaces
Temperature and radiance
Albedo
NDVI
Fires and volcanoes
SST and Oceans
Algal blooms and pollution
Land Surfaces
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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
Temperature and Radiance
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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
Temperature and Radiance
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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
Raw Meteosat
Dekad composite
Radiance image
Albedo
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Albedo is simply the ratio of incoming radiation
to reflected outgoing radiation expressed as %
out
A
 100
in
Albedo
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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
Table 1 - Typical Albedo values for natural surfaces
Surface or Object
Fresh snow
Clouds (Thick)
Cloud (Thin)
Ice
Sand
Grassy Field
Water
Forest
Earth/Atmosphere
Moon
Albedo (%)
75 – 95
60 – 90
30 – 50
30 - 40
15 – 45
10 – 30
10
3 – 10
30
7
VISIBLE
•Albedo
•Weather Fcst.
NDVI
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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
Red edge
NDVI
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Often derived from NOAA-AVHRR satellite
system (polar orbiter)
Uses differential reflectance of visible and IR
IR  R CH 2  CH1
NDVI 
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IR  R CH 2  CH1
CHANNEL
1
2
3
4
5
SPECTRAL LIMITS
REGION
0.58 - 0.68µm
visible
0.72 - 1.10µm
near infrared
3.55 - 3.93µm
thermal infrared
10.3 - 11.3µm
thermal infrared
11.5 - 12.5µm
thermal infrared
Fires and Volcanoes
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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
Volcanoes
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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
Volcanoes
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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
Forest Fires
A fire detection and management system should have the
following aims:
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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)
Boreneo Fires (Sep 18th 2005)
NASA Earth Observatory, 2005
Sea Surface Temperature (SST)
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SSTs are carefully monitored on a global basis
SST anomalies (deviation from mean) are
often the sole source of long-range climate
prediction
SST may also indicate either industrial
pollution events, natural climate fluctuations (El
Niño) and geothermal vents
Sea Surface Temperature (SST)
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SST can be measured directly from thermal
infrared (e.g. by NOAA-AVHRR)
Large-scale global sea temperature conditions
are measured by altimetric satellites such as
TOPEX-Poseidon and JASON
SST based on TIR uses radiance which may
be transformed into temperature
TOPEX/Poseidon
Launched in 1992
TOPEX
1336km above ocean
Determined wave height
Resolution of <1 inch
10-day return time
Return time of
microwave pulse used
to ascertain ocean
surface topography
SEA SURFACE
Ocean Monitoring for Disaster
Management
Tsunami
Like coastal flooding, Tsunami events may be modelled
and within a GIS.
Complex computational fluid dynamics (CFD) requires
very detailed bathymetric and topographic data retrieved
from remote sensing missions. Earthquakes and landslides
that contribute to tsunami formation can be assessed by
different remote sensing techniques.
QuickBird used extensively throughout Asian Tsunami Disaster
Of December 2004
QuickBird used extensively throughout Asian Tsunami Disaster
QuickBird used extensively throughout Asian Tsunami Disaster
QuickBird used extensively throughout Asian Tsunami Disaster
QuickBird used extensively throughout Asian Tsunami Disaster
QuickBird used extensively throughout Asian Tsunami Disaster
Algal Blooms
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During summer months certain species of
algae in warm ocean water can grow and
proliferate extremely quickly
Results in available dissolved oxygen being
removed from the water – as well as nutrients
which kills fish and other marine life
Algal ‘mats’ also blocks sunlight from
penetrating surface of water killing marine flora
Algal Blooms
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Species such as Cochlodinium polykrikoides
are often responsible for ‘red tides’ that kill fish
stocks affecting food supply and economy of
people living in Asia
Main satellite system used in monitoring ocean
algal blooms is SeaWIFS
Launched in 1997
Sun-synchronous orbit (705km above Earth)
1 day revisit interval
Algal Blooms
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Product is an ocean colour scene (OCS)
OCS is normally blue
A green OCS suggests high chlorophyll
concentration due to algae
Higher the green reflectance the greater the
algal (chlorophyll) concentration
Washington coast and
Vancouver Island
October 1st 2004
Thriving ocean plants form
clouds of green in the waters a large bloom of Pseudonitzschia, a toxic algae, off the
Strait of Juan de Fuca, the
channel of water that
separates Vancouver Island in
the north from Washington
State in the south
Source: NASA Earth Observatory 2005
Pollution Monitoring
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Satellites can clearly distinguish toxic algae as
well as thermal pollution
Oil slicks, chemical spills and dumping of
waste can also be identified
Differential spectral response of seawater
compared to chemical species (such as fuel, oil
or chemicals)
A fuel spill plume on the
surface of the water
identified from nearultraviolet imagery
Aerial sensor.