This document provides an overview of remote sensing including:
1. The history of remote sensing from early aerial photography to modern satellite systems.
2. The principles of electromagnetic radiation and how different sensors capture radiation in various parts of the spectrum to analyze objects.
3. The various types of remote sensing platforms, sensors, and data products including satellites, spectral resolution, spatial resolution, temporal resolution, and applications like land cover mapping.
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Rs fundamentals
1. Outline
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
2. 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?
12. 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
13. Radiation - Target Interactions
Spectral response depends on target
Leaves reflect green and near IR
Water reflects at lower end of visible
range
Incide nt
R a dia tio n
R e fle cte d
A bs o rbe d
T ra ns m itte d
14. 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
19. 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
0.4 袖m 0.7 袖m
Black &
White
Images
Blue + Green +
Red
20. Spectral Resolution (Cont)
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
0.4 袖m 0.7 袖m
Color
Images
Blue Green
Red
21. Spectral Resolution (Cont)
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?
22. Spectral Resolution (Cont)
Example
- Blue only sensitive film
- Green only sensitive film
- Red only sensitive film
23. Spectral Resolution (Cont)
Example
- What do you believe the
image would look like if you
used near and middle
infrared sensitive film?
24. Spectral Resolution (Cont)
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.
25. Spectral Resolution (Cont)
Example (Cont)
- What do you believe the
image would look like if you
used a thermal infrared
sensitive film?
26. Heat - Energy Transfer
Example - Thermal infrared view
Note warmer objects are brighter
29. 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.
30. 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 Earths surface
> Orbital period about every 98 - 102 min
Satellite Observations
31. Types of Orbits (Cont)
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
32. Types of Orbits (Cont)
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
33. Types of Orbits (Cont)
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 Earths surface
at the Equator where the Earths radius is 6.378 * 106
m
- Used for many communication satellites;
> Cover a country like Australia
> Dont require complex tracking dishes to receive the signals;
Note: satellite stay stationary relative to Earth
Satellite Observations
35. 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
45. 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
46. 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
47. 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
48. 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.
49. 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
50. 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
51. 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