Remote Sensing from Space

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Chapter 18

• Remote Sensing from Space

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Remote Sensing
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Remote Sensing requires the following 1.
Electromagnetic Energy Source 2. Interaction with
a Target 3. Sensor to Record Energy 4.
Transmission, Reception and Processing 5.
Interpretation 6. Application
Electromagnetic Energy Source Illuminates or
provides electromagnetic radiation to the target
of interest
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A - Source of Electromagnetic Radiation
B - Radiation comes into Contact with
Atmosphere
C - Radiation Interacts with Target
D - Sensor Collects and Records
Electromagnetic Radiation
F - Processed Image Interpreted to Extract
Target Info
G - Application
E - Recorded Energy Transmitted to Processing
Station (for copy)
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Radiation Interacts with Atmosphere Radiation
interacts with the atmosphere on the way to the
target and as the energy travels from the target
to the sensor
Interaction with a Target Radiation interacts
with target. The nature of this interaction is
dependent on the wavelength of the radiation and
the nature of the target
Sensor A sensor (mounted on satellite/plane/helico
pter) collects/records the electromagnetic
radiation scattered or emitted by the target
Transmission and Processing Recorded energy is
transmitted to a processing station to produce an
image saved in digital format (or hardcopy)
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Interpretation Visual interpretation or digital
(GIS) interpretation to extract further
information about the target
Application Information applied to solve a problem
Remote sensing is especially important
for extracting information from harsh
environments or difficult terrain
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Passive Sensors Measure naturally-available
energy (eg. thermal infrared radiation emitted
from the Earth 24 hours per day, but solar
reflected radiation only during solar day)
Active Sensors Sensor emits radiation toward
target Reflected radiation in emitted bands are
detected and measured (eg. microwaves emitted)
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Characteristic spectral responses of different
surface types. Bands are those of the SPOT
remote sensing satellite.
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Images and Photographs
Representation in digital format by subdividing
image into equally- shaped areas called pixels
The brightness of each area can be attributed
a numeric value or digital number
Information from narrow wavelength ranges can be
stored in channels, also called bands
Often, data from multiple channels can
be represented as one of three primary
colours which combine according to brightness. We
are, thus, no longer blind to these ?s.
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Orbits and Swaths
Geostationary orbits Very high altitude
satellites (approximately 36 000 km) Focus on the
same area of the Earth at all times Continual
data collection over a specific area Eg. Weather
and communications satellites
Near-polar orbits Satellite travels northward on
one side of the Earth and then southwards during
the second half of its orbit In sun-synchronous
orbits, ascending path can be on a shadowed side
with the descending path on the sunlit side.
Passive sensors would only record data during the
descent.
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Swath The area imaged on the surface. Swaths vary
from very small areas (helicopters and planes) to
hundreds of kilometres (spaceborne
satellites) Earth rotates Satellite swath may
cover new area with each pass Complete coverage
of Earth after one cycle of orbits Areas at high
latitude generally covered more frequently
Spatial Resolution Size of the smallest possible
feature that can be detected Instantaneous Field
of View (IFOV) is the angular cone of visibility
of the sensor (See A at right) This, along with
altitude (C), determines the area visible on the
ground (B)
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Spatial Resolution
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Examples of Remote Sensing Satellites Each has
multiple channels for specific purposes 1. Weathe
r GOES (Geostationary Operational Environmental
Satellite) NOAA AVHRR (Advanced Very High
Resolution Radiometer) 2. Land Surface
Observation Landsat (NOAA) SPOT (Système Pour
lObservation de la Terre) IRS (Indian Remote
Sensing) MEIS-II and CASI (Airborne
Sensors) 3. Marine Observation CZCS (Coastal
Zone Colour Scanner) MOS (Marine Observation
Satellite) SeaWiFS (Sea-viewing Wide Field of
View Sensor)
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Applications of Remote Sensing There are many
applications of remote sensing, most of which
are related to Geography as a discipline
Agriculture Crop type, condition and yield,
soil characteristics Forestry Type, health,
biomass, burning, species, deforestation Hydrology
Sea ice, navigation, oil spills, sea surface
temperature Land Use Resource management,
habitat protection, urban sprawl, damage
assessment, legal boundaries Oceans Currents,
winds, waves, phytoplankton concentration, tempe
rature monitoring, navigation routing,
traffic density, bathymetry, land-water
interface delineation, coastal
vegetation Mapping Digital Elevation Models
(DEMs), thematic mapping
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AVHRR
Visible, NIR, Thermal 1.1 km Resolution -
local area coverage (LAC) 4 km Resolution -
global area coverage (GAC) Used for
meteorological studies Vegetation pattern
analysis Global modeling Broad spectral bands
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LANDSAT Thematic Mapper Sun-synchronous,
near-polar orbit, imaging the same 185 km x 0.474
km ground swath every 16 days Global coverage
between 81 degrees north latitude and 81 degrees
south latitude Particularly useful in
determining land use classes Blue/Green, Green,
Red, NIR, MIR, Thermal 30 meter resolution 256
brightness values7 spectral bands
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Normalized Difference Vegetative Index (NDVI)
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RADAR - Radio Detection and Ranging
Passive Microwave Sensors Applications include
meteorology (atmosphere profiles, water and ozone
content), hydrology (soil moisture) and
oceanography (sea ice, currents, oil slicks)
Active Microwave Sensors RADAR - Sensor
transmits a microwave (or radio) signal toward
a target and detects the backscattered portion of
the signal Strength of backscattered signal
discriminates between targets Time delay between
transmitted and reflected signals determines the
distance to the target Non-Imaging (e.g.
altimeters) or Imaging Sensors Imaging Microwave
Sensors include RADARSAT (Canada, 1995) RADARSAT,
developed by the Canadian Space Agency, is the
worlds first, operationally-oriented radar
satellite system capable of rapid delivery of
large quantities of data
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Image Processing 1. Preprocessing Radiometric
and geometric corrections 2. Image
Enhancement Improving contrast, and spatial
filtering to enhance specific spatial patterns
of interest 3. Image Transformations Combined
processing of multiple spectral bands for
image enhancement 4. Image Classification and
Analysis Digital identification and
classification of pixels. Classification
Assigns each pixel to a particular class or
theme based on desired statistical
characteristics (supervised or unsupervised)
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Before GIS Popularity of stack maps
Limitation Restricted to consistent scale,
projection and coverage area
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Advantage of Digital Overlay 1. Faster 2. Scale
, projection and coverage area less problematic
(Most applications consist of sources collected
by different methods and at different
scales) 3. Time and error associated with manual
integration and redrafting eliminated
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Raster Implementation of Overlay