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Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction to GIS

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Page 1: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Lecture 11:Data input 2: GPS and Remote

Sensing

By Austin TroyUniversity of Vermont

------Using GIS--Introduction to GIS

Page 2: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Part 1:Global Positioning System

------Using GIS--Introduction to GIS

Many materials for this part of the lecture adapted from Trimble Navigation Ltd’s GPS Web tutorial at http://trimble.com/gps/index.html

Page 3: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

GPS•Stands for Global Positioning System

•GPS is used to get an exact location on the surface of the earth, in three dimensions.

•GPS is a very important data input source, used for surveying, military operations, engineering, vehicle tracking, flight navigation, car navigation, ship navigation, unmanned vehicle guidance, agriculture, and of course, mapping

•For mapping, a GPS tells us “where” and allows us to input “what”

Introduction to GIS

Page 4: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

GPS•GPS is a worldwide radio-navigation system formed from 24 satellites and their ground stations.

•Uses satellites in space as reference points for locations here on earth

•Ground stations help satellites determine their exact location in space. There are five monitor stations: Hawaii, Ascension Island, Diego Garcia, Kwajalein, and Colorado Springs.

Introduction to GIS

Page 5: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•GPS derives position relative to satellite “reference points,” using triangulation

• The GPS unit on the ground figures its out distance to each of several satellites using the time it takes for a radio signal to travel to the satellite

•To do this, the exact position of the satellites at a given time, must be known; otherwise they can’t serve as reference points

Introduction to GIS

Page 6: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?

Introduction to GIS

11,500 km

12,500 km

11,200 km

Page 7: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•We need at least 3 satellites as reference points to “triangulate” our position.

•Based on the principle that where we know our exact distance from a satellite in space, we know we are somewhere on the surface of an imaginary sphere with radius equal to the distance to the satellite.

•With two satellites we know we are in the plane where the two intersect. With three or more, we can get two possible points, and one of those is usually impossible from a practical standpoint and can be discarded

Introduction to GIS

Page 8: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•Here’s how the sphere concept works

• A fourth satellite narrows it from 2 possible points to 1 point

Introduction to GIS

Source: Trimble Navigation Ltd.

Page 9: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•This method assumes we can find exact distance from our GPS receiver to a satellite. How does that work?

•Simple answer: see how long it takes for a radio signal to get from the satellite to the receiver.

•Since we know speed of light, we can answer this

•This gets complicated when you think about the need to perfectly synchronize satellite and receiver.

•A tiny error in synchronization can result in hundreds of meters of positional error

Introduction to GIS

Page 10: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•The difficult part is measuring travel time, because the amount of time elapsed is tiny (about .06 seconds for an overhead satellite), and we require a way to know precisely WHEN the signal left the satellite

•To do this requires comparing lag in exactly similar patterns, one from satellite and one from receiver.

•Analogy, going to a stadium, sitting 1000 feet from the speaker and pressing “play” on your handheld tape player containing REO Speedwagon at exactly the same time as the guy in the sound booth presses play for that same song.

Introduction to GIS

Page 11: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?

•Only, instead of using cheesy eighties rock power ballads, GPS uses something called “pseudo-random code.”

•This code has to be extremely complex (hence almost random), so that patterns are not linked up at the wrong place on the code—that would generate the wrong time delay and hence the wrong distance

Introduction to GIS

Local: “I can’t fight this feeling any more,”

delayed:“I can’t fight this feeling any more,”

Source: Trimble Navigation Ltd.

Page 12: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•So how do we know that the two Speedwagon fans are pressing “play” at exactly the same time? Do Speedwagon fans all think alike? Hardly.

•We must assume that satellite and receiver generate signal at exactly the same time; if they’re off by 1/1000th of a second, that means 200 m of error

•The satellites have expensive atomic clocks that keep perfect time—that takes care of their end.

•But what about the ground receiver?

Introduction to GIS

Page 13: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•Here is where the fourth satellite signal comes in.

•While 3 perfect satellite signals can give a perfect location, 3 imperfect signals can’t, but 4 can

•Imagine time to receiver as distance, with each distance from each satellite defining a circle around each satellite of that radius

•If receiver clock is correct, 4 circles should meet at one point. If they don’t meet, the computer knows there is an error in the clock: “ They don’t add up”

Introduction to GIS

Page 14: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•Dotted lines represent real distance, and solid lines represent erroneous distance, based on clock error—they don’t meet. Notice here we used three circles, because we’re looking in 2D, but in reality (3D) this represents four satellites, or four circles

Introduction to GIS

Source: Trimble Navigation Ltd.

•Assuming the clock error affects all measurements equally, the computer can then simply apply a correction factor that makes circles meet in one place

Page 15: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•The receiver then knows the difference between its clock’s time and universal time and can apply that to future measurements.

•Of course, the receiver clock will have to be resynchronized often , because it will lose or gain time

•This is one reason why a GPS receiver needs at least four channels to get four signals

Introduction to GIS

Page 16: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•So now we know how far we are from the satellites, but how do we know where the satellites are?? We can’t use them as a reference otherwise.

•Because the satellites are 11,000 ft up, they operate according to the well understood laws of physics, and are subject to few random, unknown forces.

•This allows us to know where a satellite should be at any given moment.

Introduction to GIS

Page 17: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•There is a digital “almanac” on each GPS receiver that tells it where a given satellite is supposed to be at any given moment.

•While the positions can be predicted very accurately based on simple mathematics, the DOD does monitor them using precise radar, just to make sure.

•These errors are called “ephemeris” and are caused by gravitational pull of other celestial bodies

•That info is relayed to the satellite, which transmits the info when it sends its pseudo random code.

Introduction to GIS

Page 18: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•Even after all this, there are still many factors that can generate errors and reduce positional accuracy

•One of the biggest error sources is the fact that the radio signal does not travel at the exact speed of light in different parts if the atmosphere as it does in the vacuum of space.

•This can be partly dealt with using predictive models of known atmospheric behavior

Introduction to GIS

Source: Trimble Navigation Ltd.

Page 19: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•Signals also can bounce off features, like tall buildings, cliffs and mountains, resulting in “multipath error,” where a direct signal hits, followed by a bunch of “bounced” signals which can confuse the receiver.

•Good receivers have algorithms that can deal with this by determining what counts as a multi-path signal and choosing the first one as the signal to use

•There are other errors as well, resulting from things like ionospheric distortions and satellite inaccuracies

Introduction to GIS

Page 20: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•Until May of 2000, the DoD intentionally introduced a small amount of error into the signal for all civilian users, calling it “selective availability,” so non- US military users would not have the same positional accuracy as the US military.

•SA resulted in about 100 m error most of the time

•Turning off SA reduced error to about 30 m radius

•Here is Clinton’s letter: http://www.ngs.noaa.gov/FGCS/info/sans_SA/docs/statement.html

Introduction to GIS

Page 21: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Differential GPS•This is a way to dramatically increase the accuracy of GPS positioning to a matter of a few meters, using basic concepts of geometry

•This was used in the past to overcome SA, but with that gone, is now used for reducing the 30m error

•DGPS uses one stationary and one moving receiver to help overcome the various errors in the signal

•By using two receivers that are nearby each other, within a few dozen km, they are getting essentially the same errors (except receiver errors)

Introduction to GIS

Page 22: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Differential GPS•DGPS improves accuracy much more than disabling of SA does

•This table shows typical error—these may vary

Introduction to GIS

Source: http://www.furuno.com/news/saoff.html

Page 23: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does DGPS work?•The stationary receiver must be located on a control point whose position has been accurately surveyed: eg. USGS benchmarks

•The stationary unit works backwards—instead of using timing to calculate position, it uses its position to calculate timing

•It determines what the GPS signal travel time should be and compares it with what it actually is

•Can do this because, precise location of stationary receiver is known, and hence, so is location of satellite

Introduction to GIS

Page 24: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does DGPS work?•Can do this because, precise location of stationary receiver is known, and hence, so is location of satellite

•Once it knows error, it determines a correction factor and sends it to the other receiver.

Introduction to GIS

Page 25: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does DGPS work?•Since the reference receiver does not know which satellites the mobile receiver is using, it sends a message to it telling the correction factor for all

•It used to be that only big companies and governments could use DGPS because they had to set up their own reference receiver station

•Now there are many public agencies that maintain them, especially the Coast guard; these stations broadcast on a radio frequency, which GPS receivers with a radio receiver can pick up

Introduction to GIS

Page 26: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

How does GPS work?•DGPS: now or later?

•If you don’t need the exact DGPS measurement at the moment you take a GPS measurement in the field, you can correct your data later.

•All you need to know is the roving receiver’s measured positions and the exact times they were taken

•At a later time, the reference receiver’s corrections can then be integrated with the roving GPS data based on the time and location; no radio link needed for this

Introduction to GIS

Page 27: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Surveyor DGPS•There are even more accurate types of DGPS that surveyors use

•These are accurate to a matter of millimeters

•This uses a very involved method that won’t be discussed here

•One of the techniques they use though, carrier-phase GPS” is beginning to make its way into consumer GPS

•Use carrier-phase signal, which is much smaller cycle widths than the standard code phase signal

Introduction to GIS

Page 28: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Aviation DGPS•FAA is implementing DGPS for the continent, so all planes can get extremely accurate GPS navigation, called Wide Area Augmentation System (WAAS)

•They have installed 25 ground reference stations as well as a master ground station that almost instantaneously processes and sends out satellite errors

•Improves error to 7 m and, when finished, will allow GPS to be used as primary navigational tool for Category I landings, where there is some visibility.

•Soon, it will allow zero-visibility landing navigation

Introduction to GIS

Page 29: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

GPS Uses•Trimble Navigation Ltd., breaks GPS uses into five categories:

•Location – positioning things in space

•Navigation – getting from point a to point b

•Tracking - monitoring movements

•Mapping – creating maps based on those positions

•Timing – precision global timing

•You can learn about all these applications at these web links, but we mainly care about mapping

Introduction to GIS

Page 30: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

GPS Uses•The uses for GPS mapping are enormous. Here are just a few examples:

•Centerlines of roads

•Hydrologic features (over time)

•Bird nest/colony locations (over time)

•Fire perimeters

•Trail maps

•Geologic/mining maps

•Vegetation and habitat

Introduction to GIS

Page 31: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Part 2:Introduction to Remote Sensing

------Using GIS--Introduction to GIS

Thanks are due to Jarlath O’Neil Dunne, upon whose lecture much of this material is based, and whose graphics were used in many slides for this part of the lecture

Page 32: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

What is remote sensing•Remote sensing is “the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area or phenomenon under investigation.” (Lillesand and Kiefer 2000)

•In the case of geography, this refers to sensing of electromagnetic energy operated from airborne or spaceborne platforms.

•These sensors collect data on how earth surface features emit and reflect electromagnetic energy

Introduction to GIS

Page 33: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Why is remote important•Remotely sensed imagery is the original source for most of the GIS data we use

•RS data can be used to assess ground conditions over a very large area

•RS data allows us to look at changes in the environment

Introduction to GIS

Page 34: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Some Applications•Planning and transportation

•Road updates

•Infrastructure monitoring

•Growth monitoring

Introduction to GIS

Source: Halcon

Page 35: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Some Applications•Natural resource mapping

•Tree cover

•Tree conditions

•Crop conditions

•Yield estimation

Introduction to GIS

Clubroot disease

Source: NGIC

Page 36: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Some Applications•Natural resource mapping

•Land use change analysis

•Habitat and natural communities mapping

Introduction to GIS

Source: TRIC

Page 37: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS•Remote sensing data are collected in the electro-magnetic radiation spectrum, principally the visible, infra-red and radio regions

•Passive RS systems collect data on energy that is reflected or emitted from the earth

•Most systems are passive, except for microwave and radar, which are active sensing mechanisms.

•Most RS platforms record reflectance in multiple wavelengths spectrums

Introduction to GIS

Page 38: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Physics of RS•EM radiation exists across a range of wavelengths, referring to distance between two peaks

Introduction to GIS

Source: http://rst.gsfc.nasa.gov/Intro/Part2_2.html

Page 39: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Physics of RS•The visible spectrum constitutes a small portion, bounded by ultraviolet spectrum below and the infrared spectrum above

Introduction to GIS

Source: http://www.sci-ctr.edu.sg/ssc/publication/remotesense/em.htm

Page 40: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Physics of RS

Introduction to GIS

Ultra-Violet

Visible Near IR Shortwave IR Midwave IR

Longwave IR

Pan

chrom

aticB

lack &

Wh

ite F

ilm

Color Film

.01 .04 .07 1.0 3.0 5.0 14.00 um

Color IR Film

Spectral Imagery

Visile

Comprises 2%of EM Spectrum

Wavelength(Micrometers)

Source: Jarlath O’Neil-Dunne

Page 41: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS•Light can either be reflected, absorbed or transmitted on a surface, and the proportion of those three will vary at each wavelength for a given object.

•Reflection is emission of photons caused by excitation of the surface, due to incident radiation

•Reflected E = incident E - absorbed and transmitted E

•This relationship varies in each wavelength

•This is why two features may appear similar in the same wavelength band, but distinguishable in different wavelength band

Introduction to GIS

Page 42: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS

•The wavelengths in which it is reflected determine the color of the object

Introduction to GIS

High

Low

Blue Green Red

Ref

lect

ance

0.4m 0.5m 0.6m 0.7m

White LightGreenGreen

BlueBlue

RedRed

Source: Jarlath O’Neil-Dunne

Page 43: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS•Spectral reflectance = E(r)E(i)

Or the proportion of reflected to incident radiation

•The power of emitted photons in each wavelength depends on the surface.

•An RS sensor can detect spectral responses from objects in various wavelength ranges.

•Each class of objects has a different spectral responses across wavelength

•Spectral reflectance values of an object can be plotted on a graph as a function of wavelength, known as a spectral reflectance curve.

Introduction to GIS

Page 44: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS•Each object feature class on the earth has a spectral reflectance curve that helps us to identify it remotely. This is why we can use RS to tell the difference between types of objects

•A spectral response pattern delivers much more information than a single pixel value

•Spectral response usually plotted as an “envelope” of values rather than a line, because the relationship varies within a range for a given class of object

•RS sensors only look at small portion of the x axis

Introduction to GIS

Page 45: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS•A spectral reflectance curve for several very different classes of object; note how different the responses are

Introduction to GIS

Source :Lillesand and Kiefer 2000. Remote Sensing and Image Interpretation Wiley and Sons

Page 46: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS

Introduction to GIS

50

40

30

20

10

0

0.4 0.6 0.7 0.8 1.3

Artificial turfAsphalt

Fallow field

Sandy loamy Soil

Concrete

REFLECTANCE

(%) Clear water

Wavelength (micrometers)

Grass

Visible0.5

GREENBLUE GREEN RED

Near IR

Source: Jarlath O’Neil-Dunne

Page 47: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS

Introduction to GIS

•A Spectral reflectance curve for two classes of similar object: conifers and deciduous trees

•Note how visible band is similar, but near IR band is very different: means eye could not pick this up

•The shape of an objects curves will determine what bands we use to ID it

Source :Lillesand and Kiefer 2000

Page 48: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS

Introduction to GIS

•Panchromatic B&W: can’t tell deciduous from conifer

Source :Lillesand and Kiefer 2000

•Infrared B&W: can clearly see deciduous because higher reflectance in those wavelengths

Page 49: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS

Introduction to GIS

© Space Imaging © Space Imaging

Green Reflectance NIR Reflectance

Page 50: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS

Introduction to GIS

•RS hardware’s ability to sense in these non-visible wavelengths allow us to visualize things we normally could not perceive with the human eye, like water temperature

Source :Lillesand and Kiefer 2000

Page 51: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS

Introduction to GIS

•Here’s one showing suspended sediment in San Francisco Bay

Source :USGS

Page 52: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS•Atmosphere has a big impact on RS imagery

•Scattering of light degrades the image in shorter wavelengths, particularly the ultraviolet and blue

•The scattering causes “noise” which reduces contrast in these wavelengths

Introduction to GIS

Page 53: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

The Physics of RS•Many wavelengths are also absorbed by gases in the atmosphere, including CO2 and O3

Introduction to GIS

Source :Lillesand and Kiefer 2000

Page 54: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

So, what are RS data?•RS imagery is raster data

•Each pixel has a geographic coordinate and reflectance/intensity value, or digital number (DN).

•The dimensions of the area represented by a single pixel defines the resolution

•High resolution images have small pixel size, like 1 meter square, while coarse images have large pixel size, like a square kilometer

Introduction to GIS

Page 55: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Introduction to GIS

Source: http://www.sci-ctr.edu.sg/ssc/publication/remotesense/em.htm

Page 56: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

RS Data•RS data also have “radiometric” resolution, which is the smallest change in reflectance value, or intensity level that can be detected by the system

•This, like with any raster image, is determined by the data bits

•The fewer pixel values, the less realistic, and the more abrupt the changes look

Introduction to GIS

Page 57: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Panchromatic imaging•With panchromatic imaging, the sensor is a single channel detector sensitive to radiation in a broad wavelength range. Where the wavelength range coincides with the visible range, the resulting image resembles a "black-and-white" photograph. The physical quantity being measured is the apparent brightness of the targets. The spectral information or "colour" of the targets is lost.

Introduction to GIS

Page 58: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging•With multispectral, or multiband data, there are several layers, or values for each pixel, each representing a different “channel” or reflectance in a wavelength spectrum

•Each “band” or “channel” is sensitive to radiation within a different band of wavelength, through use of different filters

•The sensor takes an average value for the spectral window in which it is sensing; that is, it averages the curve within that region

Introduction to GIS

Page 59: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging

Introduction to GIS

40

30

20

10

0

0.4 0.6 0.7 0.8 1.3

Concrete

REFLECTANCE

(%)

Wavelength (micrometers)

Grass

Visible0.5

GREENBLUE GREEN RED

Near IR

Source: Jarlath O’Neil-Dunne

Page 60: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging• These bands can be combined to make “composite” images, can be looked at separately, or can be analyzed using overlay analysis methods

•One band from a multispectral image would be displayed as a grayscale image, with each pixel represented by a grayscale value

•When three layers are combined, they can be assigned to the three color channels (red, green, blue) to make a display that appears to us in humanly visible colors, although they may represent colors outside the visible spectrum and may not coincide with the real colors

Introduction to GIS

Page 61: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging•Here is an example of three bands, green, red and near infra-red displayed separately as grayscale

Introduction to GIS

green

red

Near-infra red

Source: http://www.sci-ctr.edu.sg/ssc/publication/remotesense/opt_int.htm#multispectral

Page 62: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging•The “best” combination of bands will depend on what the object is that’s being sensed, and what it’s spectral response curve looks like.

•For instance, if we go back to the conifer-deciduous example from before, we know that near IR is the key band for differentiating the two, but this won’t be so for all object types

•The key is to get the band that best shows contrast between two feature classes that may be indistinguishable to the human eye

Introduction to GIS

Page 63: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging•True color composite: where bands are assigned to color channels in such a way that colors in the image roughly correspond with the colors in the real world. Often assigned red to red, green to green and blue to blue can result in this

• Another is a false color composite, which shows colors that don’t really exist in that location. An example is color infrared composite, where green band is assigned to blue display channel, red is assigned to green and Near IR is assigned to red

Introduction to GIS

Page 64: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging•Composite images are usually displayed by assigning three of the bands to the red, green and blue channels and displaying them additively. This can be done in image processing software.

•For instance, here in AV we can assign bands to channels in the legend editor

Introduction to GIS

Page 65: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging

Introduction to GIS

BLUEBLUE

GREENGREEN

REDRED NEAR IR SHORT

WAVE IRMID-

WAVE IRLONGWAVE IR

1Landsat TM Band 2 3 4 5 7 6

Band Combination = 7 4 2 (LANDSAT)

Color Guns =

Band Composite Output =

Source: Jarlath O’Neil-Dunne

Page 66: Lecture Materials by Austin Troy © 2003 Lecture 11: Data input 2: GPS and Remote Sensing By Austin Troy University of Vermont ------Using GIS-- Introduction

Lecture Materials by Austin Troy © 2003

Multispectral Imaging•Here are examples of simulated normal color composite (top) and simulated IR color (bottom)

•Other bands can be used for composites as well

Introduction to GIS

Source :Lillesand and Kiefer 2000