Intel 304
bwood89
rs_fundamentals.pptOutline
1. Definition
2. History of remote sensing
3. Principles of radiation
4. Radiation-target interaction
5. Spectral signatures
6. Resolution
7. Satellite orbits
8. Applications
Remote Sensing
Definition
Science and art of obtaining information about an object, area or
phenomenon through an analysis of data acquired by a device
that is not in direct contact with the area, object or phenomenon
under investigation.
Lillesand, Thomas M. and Ralph W. Kiefer, “Remote Sensing and Image Interpretation” John Wiley and Sons, Inc, 1979, p. 1
What are some common examples of remote sensors?
History of Remote Sensing
1609 - Invention of the telescope
Galileo
History of Remote Sensing
1859 - First aerial photographer
Gaspard Felix Tournachon, also known as Nadar
1862 - US Army balloon corp
History of Remote Sensing
1909 - Dresden International
Photographic Exhibition
1903 - The Bavarian Pigeon Corps
History of Remote Sensing
1914-1918 - World War I
1908 - First photos from an airplane
First flight, Wright Bros., Dec. 1903
Electromagnetic energy is emitted in waves
Amount of radiation emitted from
an object depends on its temperature
Planck Curve
Radiation
Electromagnetic Spectrum
Remote Sensing Systems
Human eye
Camera
Radiometer
Radar
Sonar
Laser
- Passive
- Active
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Remote Sensing Platforms
- Ground based
- Aircraft
- Space shuttle
- Satellite
Components of a Remote Sensing System
Remote Sensing
Four Fundamental Properties For Design
• Image depends on the wavelength response of the sensing instrument (radiometric and spectral resolution) and the emission or reflection spectra of the target (the signal).
- Radiometric resolution
- Spectral resolution
• Image depends on the size of objects (spatial resolution) that can be discerned
- Spatial resolution
• Knowledge of the changes in the target depends on how often (temporal resolution) the target is observed
- Temporal resolution
Radiation - Target Interactions
• Spectral response depends on target
• Leaves reflect green and near IR
• Water reflects at lower end of visible
range
Radiometric Resolution
• Number of Shades or brightness levels at a given wavelength
• Smallest change in
intensity level that can
be detected by the
sensing system
Spectral Response Differences
TM Band 3 (Red)
TM Band 4 (NIR)
Pixels
80 x 80
Spatial Resolution
320 x 320
40 x 40
Application of Temporal Data: Urban Sprawl
Atlanta, GA
1973
1987
Spectral Resolution
• Example: Black and
white image
- Single sensing device
- Intensity is sum of
intensity of all
visible wavelengths
Can you tell the color of the
platform top?
How about her sash?
Spectral Resolution (Con’t)
- Example: Color image
- Color images need
least three sensing
devices, e.g., red, green,
and blue; RGB
Using increased spectral
resolution (three sensing
wavelengths) adds
information
In this case by “sensing”
RGB can combine to
get full color rendition
Spectral Resolution (Con’t)
• Example
- What do you believe the
image would look like if you
used a blue only sensitive film?
- What do you believe the
image would look like if you
used a green only sensitive film?
- What do you believe the
image would look like if you
used a red only sensitive film?
Spectral Resolution (Con’t)
• Example
- Blue only sensitive film
- Green only sensitive film
- Red only sensitive film
Spectral Resolution (Con’t)
• Example
- What do you believe the
image would look like if you
used near and middle
infrared sensitive film?
Spectral Resolution (Con’t)
• Example
- What do you believe the
image would look like if you
used a thermal infrared
sensitive film?
Blinded in the darkness, he extended his arms, felt around for obstacles, both to avoid and to hide behind. The men wearing infrared monocular night-vision units, the lenses strapped against their eyes by means of a head harness and helmet mount, were doubtless also carrying handguns. The others had rifles fitted with advanced infrared weapon sights. Both allowed the user to see in total darkness by detecting the differentials in thermal patterns given off by animate and inanimate objects.
Ludlum, Robert, 2000: The Prometheus Deception, p. 96.
Spectral Resolution (Con’t)
• Example (Con’t)
- What do you believe the
image would look like if you
used a thermal infrared
sensitive film?
Heat - Energy Transfer
• Example - Thermal infrared view
Note warmer objects are brighter
Spectral Resolution (Con’t)
Example of sampling wavelengths
Data Acquisition - Satellite Orbits
Satellites:
- Sun-synchronous (Landsat, SPOT)
- Geostationary (TIROS)
Satellite Orbit Determines...
- …what part of the globe can be viewed.
- …the size of the field of view.
- …how often the satellite can revisit the
same place.
- …the length of time the satellite is on the
sunny side of the planet.
Types of Orbits
• Lower Earth Orbit (LEO)
- Orbit at 500 - 3,000 km above the Earth (definition varies)
- Used for reconnaissance, localized weather and imaging
of natural resources.
- Space shuttle can launch and retrieve satellites in this orbit
- Now coming into use for personal voice and data
communications
- Weather satellites
> Polar orbit - Note, as the satellite orbits, the Earth is turning underneath. Current NOAA satellites orbit about 700 - 850 km above Earth’s surface
> Orbital period about every 98 - 102 min
Satellite Observations
Satellite Observations
Types of Orbits (Con’t)
• Medium Earth Orbit (MEO)
- Orbit at 3,000 - 30,000 km (definition varies)
- Typically in polar or inclined orbit
- Used for navigation, remote sensing,
weather monitoring, and sometimes
communications
> GPS (Global Position System) satellites
‡ 24-27 GPS satellites (21+ active, 3+
spare) are in orbit at 20,000 km
(about 10,600 miles) above the Earth;
placed into six different orbital planes,
with four satellites in each plane
‡ One pass about every 12 h
Satellite Observations
Types of Orbits (Con’t)
• Highly Elliptical Orbits (HEO)
- Typically pass low (1,000 km) over the southern regions, then loop high
over the northern regions
- One pass every 4 to 12 h
- Used in communications to provide coverage of the higher latitudes and the polar regions
Satellite Observations
Types of Orbits (Con’t)
• Geosynchronous
- Orbital period of 1 day, i.e., satellite stays over the same spot on the
Earth
- Orbital radius is 42,164 km or 35,786 km above the Earth’s surface
at the Equator where the Earth’s radius is 6.378 * 106 m
- Used for many communication satellites;
> Cover a country like Australia
> Don’t require complex tracking dishes to receive the signals;
Note: satellite stay stationary relative to Earth
Satellite Observations
Types of Orbits (Con’t)
• Geosynchronous (Con’t)
- Weather satellites
> GOES (Geosynchronous Operational Environmental Satellites)
Satellite
Applications of Remote Sensing
- Images serve as base maps
- Observe or measure properties or conditions
of the land, oceans, and atmosphere
- Map spatial distribution of “features”
- Record spatial changes
Classification - Supervised Training
Maximum Likelihood
Classification
Change Detection - Flooding
Landsat imagery of the 1993 Mississippi flood
Quantifying Urban Sprawl
San Francisco Bay
Change Detection - Urban Sprawl
Monitoring Weather
GOES-8 Water Vapor
Detecting and Monitoring Wildland Fires
Arizona, June 2002
Borneo
Monitoring Sea Surface Temperature
GOES and MODIS Spatial and
Temporal Resolution
• GOES sounder – temporal resolution every hour; spatial resolution
(10 km)
• MODIS instrument on the polar orbiting platforms - up to four passes a day, two daytime and two nighttime; spatial resolution
(1 km)
AQUA MODIS 24 JAN 2004
GOES LST 2 AM CST
GOES and MODIS Spectral Resolution
MODIS observes 36 separate frequencies of radiation, ranging from visible to infrared. GOES detects only five frequencies.
http://science.nasa.gov/headlines/y2004/09jan_sport.htm
Land Surface Temperature (LST) Comparison
Dry Period
- June 25-July 3, 2004
- July 25-August 3, 2004
Wet Period
- June 26-July 3, 2005
- July 23-31, 2005
LST Products
MODIS/Terra Land Surface Temperature/Emissivity
Daily L3 Global 1 km SIN Grid (MOD11A1)
Data Set Characteristics
• Area = ~ 1100 x 1100 km Image Dimensions = 2 (1200 x 1200 row/column)
• Average File Size = 24 MB
• Resolution = 1 kilometer (actual 0.93 km)
• Projection = Sinusoidal
• Land Surface Temperature (LST) Data Type =16-bit Unsigned Integer
• Emissivity Data Type = 8-bit Unsigned Integer
• Data Format = HDF-EOS
• Science Data Sets (SDS) = 12
The MODIS/Terra Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid product, MOD11A1, is a gridded version of the level-2 daily LST product. It is generated by projecting MOD11_L2 pixels to Earth locations on a sinusoidal mapping grid.
MODIS/Terra Land Surface Temperature/
Emissivity Daily L3 Global 1 km SIN Grid
| SDS | Units | Data Type-bit | Fill Value | Valid Range | Multiply By Scale Factor | Add Additional Offset |
| Daily daytime 1 km grid Land-Surface Temperature | Kelvin | 16-bit unsigned integer | 0 | 7500-65535 | 0.0200 | na |
| Daily nighttime 1 km grid Land-Surface Temperature | Kelvin | 16-bit unsigned integer | 0 | 7500-65535 | 0.0200 |
Land Cover Products
MODIS/Terra Land Cover Type Yearly L3 Global 1 km
SIN Grid
Version VOO4
- The MOD12 classification schemes are multitemporal classes describing land cover properties as observed during the year (12 months of input data).
- These classes are distinguished with a supervised decision tree classification method
LEGEND MOD12Q1 Land Cover Type 5
| Land Cover | Class |
| Fill Value | 255 |
| Water | 0 |
| Evergreen needleleaf trees | 1 |
| Evergreen broadleaf trees | 2 |
| Deciduous needleleaf trees | 3 |
| Deciduous broadleaf trees | 4 |
| Shrub | 5 |
| Grass | 6 |
| Cereal crop | 7 |
| Broadleaf crop | 8 |
| Urban and built up | 9 |
| Snow and ice | 10 |
| Barren or sparse vegetation | 11 |
Incident
Radiation
Reflected
Absorbed
Transmitted
