Gis and remote sensings

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University College of Science, OU
Remote Sensing and GIS
2014
Haroon Hairan

UNIT-I
What is Remote Sensing?
We perceive the surrounding world through our five senses. Some senses (touch and
taste) require contact of our sensing organs with the objects. However, we acquire much
information about our surrounding through the senses of sight and hearing which do not
require close contact between the sensing organs and the external objects. In another
word, we are performing Remote Sensing all the time.
Generally, Remote sensing refers to the activities of recording/observing/perceiving
(sensing) objects or events at far away (remote) places. In remote sensing, the
sensors are not in direct contact with the objects or events being observed. The
information needs a physical carrier to travel from the objects/events to the sensors
through an intervening medium. The electromagnetic radiation is normally used as an
information carrier in remote sensing. The output of a remote sensing system is usually
an image representing the scene being observed. A further step of image analysis and
interpretation is required in order to extract useful information from the image. The
human visual system is an example of a remote sensing system in this general sense.
In a more restricted sense, remote sensing usually refers to the technology of acquiring
information about the earth's surface (land and ocean) and atmosphere using sensors
onboard airborne (aircraft, balloons) or space borne (satellites, space shuttles)
platforms.
Satellite Remote Sensing
In this CD, you will see many remote sensing images around Asia acquired by earth
observation satellites. These remote sensing satellites are equipped with sensors
looking down to the earth. They are the "eyes in the sky" constantly observing the earth as
they go round in predictable orbits.
Effects of Atmosphere
In satellite remote sensing of the earth, the sensors are looking through a layer
of atmosphere separating the sensors from the Earth's surface being observed. Hence, it
is essential to understand the effects of atmosphere on the electromagnetic radiation
travelling from the Earth to the sensor through the atmosphere. The atmospheric
constituents cause wavelength dependent absorption and scattering of radiation.
These effects degrade the quality of images. Some of the atmospheric effects can be
corrected before the images are subjected to further analysis and interpretation.
A consequence of atmospheric absorption is that certain wavelength bands in the
electromagnetic spectrum are strongly absorbed and effectively blocked by the
atmosphere. The wavelength regions in the electromagnetic spectrum usable for remote
sensing are determined by their ability to penetrate atmosphere. These regions are known
as the atmospheric transmission windows. Remote sensing systems are often designed
to operate within one or more of the atmospheric windows. These windows exist in the
microwave region, some wavelength bands in the infrared, the entire visible region and
part of the near ultraviolet regions. Although the atmosphere is practically transparent to
x-rays and gamma rays, these radiations are not normally used in remote sensing of the
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earth.
Optical and Infrared Remote Sensing
In Optical Remote Sensing, optical sensors detect solar radiation reflected or scattered
from the earth, forming images resembling photographs taken by a camera high up in
space. The wavelength region usually extends from the visible and near
infrared (commonly abbreviated as VNIR) to the short-wave infrared (SWIR).
Different materials such as water, soil, vegetation, buildings and roads reflect visible and
infrared light in different ways. They have different colours and brightness when seen
under the sun. The inter pretation of optical images require the knowledge of
the spectral reflectance signatures of the various materials (natural or man-made)
covering the surface of the earth.
There are also infrared sensors measuring the thermal infrared radiation emitted from
the earth, from which the land or sea surface temperature can be derived.
Microwave Remote Sensing
There are some remote sensing satellites which carry passive or active microwave
sensors. The active sensors emit pulses of microwave radiation to illuminate the areas
to be imaged. Images of the earth surface are formed by measuring the microwave energy
scattered by the ground or sea back to the sensors. These satellites carry their own
"flashlight" emitting microwaves to illuminate their targets. The images can thus be
acquired day and night. Microwaves have an additional advantage as they can penetrate
clouds. Images can be acquired even when there are clouds covering the earth surface.
A microwave imaging system which can produce high resolution image of the Earth is
the synthetic aperture radar (SAR). The intensity in a SAR image depends on the
amount of microwave backscattered by the target and received by the SAR antenna. Since
the physical mechanisms responsible for this backscatter is different for microwave,
compared to visible/infrared radiation, the interpretation of SAR images requires the
knowledge of how microwaves interact with the targets.
Remote Sensing Images
Remote sensing images are normally in the form of digital images. In order to extract
useful information from the images, image processing techniques may be employed to
enhance the image to help visual interpretation, and to correct or restore the image if
the image has been subjected to geometric distortion, blurring or degradation by other
factors. There are many image analysis techniques available and the methods used depend
on the requirements of the specific problem concerned. In many cases,
image segmentation and classification algorithms are used to delineate different areas
in an image into thematic classes. The resulting product is a thematic map of the study
area. This thematic map can be combined with other databases of the test area for further
analysis and utilization.
Aerial photography
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Aerial photography is the taking of photographs of the ground from an elevated position.
The term usually refers to images in which the camera is not supported by a ground-based
structure. Platforms for aerial photography include fixed-wing aircraft, helicopters, multi
rotor Unmanned Aircraft Systems (UAS), balloons, blimps and dirigibles, rockets, kites,
parachutes, stand-alone telescoping and vehicle mounted poles. Mounted cameras may be
triggered remotely or automatically; hand-held photographs may be taken by a
photographer.
Aerial photography should not be confused with Air-to-Air Photography, where one-or-more
aircraft are used as Chase planes that "chase" and photograph other aircraft in flight.
History
Early History
Aerial photography was first practiced by the French photographer
and balloonist Gaspard-Félix Tournachon, known as "Nadar", in 1858 over Paris,
France. However, the photographs he produced no longer exist and therefore the earliest
surviving aerial photograph is titled 'Boston, as the Eagle and the Wild Goose See It.' Taken
by James Wallace Black and Samuel Archer King on October 13, 1860, it depicts Boston
from a height of 630m.
Kite aerial photography was pioneered by British meteorologist E.D. Archibald in 1882. He
used an explosive charge on a timer to take photographs from the air. Frenchman Arthur
Batut began using kites for photography in 1888, and wrote a book on his methods in 1890.
Samuel Franklin Cody developed his advanced 'Man-lifter War Kite' and succeeded in
interesting the British War Office with its capabilities.
The first use of a motion picture camera mounted to a heavier-than-air aircraft took place
on April 24, 1909 over Rome in the 3:28 silent film short, Wilbur Wright und seine
Flugmaschine.
World War I
The use of aerial photography rapidly matured during the war, as reconnaissance
aircraft were equipped with cameras to record enemy movements and defences. At the
start of the conflict, the usefulness of aerial photography was not fully appreciated, with
reconnaissance being accomplished with map sketching from the air.
Germany adopted the first aerial camera, a Görz, in 1913. The French began the war with
several squadrons of Blériot observation aircraft equipped with cameras for
reconnaissance. The French Army developed procedures for getting prints into the hands
of field commanders in record time.
Frederick Charles Victor Laws started aerial photography experiments in 1912 with the No.
1 Squadron RAF, taking photographs from the British dirigible Beta. He discovered that
vertical photos taken with 60% overlap could be used to create a stereoscopic effect when
viewed in a stereoscope, thus creating a perception of depth that could aid in cartography
and in intelligence derived from aerial images. The Royal Flying Corps recon pilots began to
use cameras for recording their observations in 1914 and by the Battle of Neuve
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Chapelle in 1915, the entire system of German trenches was being photographed. In 1916
the Austro-Hungarian Monarchy made vertical camera axis aerial photos above Italy for
map-making.
The first purpose-built and practical aerial camera was invented by Captain John Moore-
Brabazon in 1915 with the help of the Thornton-Pickard company, greatly enhancing the
efficiency of aerial photography. The camera was inserted into the floor of the aircraft and
could be triggered by the pilot at intervals. Moore-Brabazon also pioneered the
incorporation of stereoscopic techniques into aerial photography, allowing the height of
objects on the landscape to be discerned by comparing photographs taken at different
angles.
By the end of the war aerial cameras had dramatically increased in size and focal
power and were used increasingly frequently as they proved their pivotal military worth;
by 1918 both sides were photographing the entire front twice a day, and had taken over
half a million photos since the beginning of the conflict. In January 1918, General
Allenby used five Australian pilots from No. 1 Squadron AFC to photograph a 624 square
miles (1,620 km2) area in Palestine as an aid to correcting and improving maps of the
Turkish front. This was a pioneering use of aerial photography as an aid for cartography.
Lieutenants Leonard Taplin, Allan Runciman Brown, H. L. Fraser, Edward Patrick Kenny,
and L. W. Rogers photographed a block of land stretching from the Turkish front lines 32
miles (51 km) deep into their rear areas. Beginning 5 January, they flew with a fighter
escort to ward off enemy fighters. Using Royal Aircraft Factory BE.12 and Martin syde
airplanes, they not only overcame enemy air attacks, but also had to contend with 65 mph
(105 km/h) winds, antiaircraft fire, and malfunctioning equipment to complete their task.
Commercial Aerial Photography
The first commercial aerial photography company in the UK was Aerofilms Ltd, founded by
World War I veterans Francis Wills and Claude Graham White in 1919. The company soon
expanded into a business with major contracts in Africa and Asia as well as in the UK.
Operations began from the Stag Lane Aerodrome at Edgware, using the aircraft of the
London Flying School. Subsequently the Aircraft Manufacturing Company(later the De
Havilland Aircraft Company), hired an Airco DH.9 along with pilot entrepreneur Alan
Cobham.
From 1921, Aerofilms carried out vertical photography for survey and mapping purposes.
During the 1930s, the company pioneered the science of photo grammetry (mapping from
aerial photographs), with the Ordnance Survey amongst the company's clients.
Another successful pioneer of the commercial use of aerial photography was the
American Sherman Fairchild who started his own aircraft firm Fairchild Aircraft to develop
and build specialized aircraft for high altitude aerial survey missions. One Fairchild aerial
survey aircraft in 1935 carried unit that combined two synchronized cameras, and each
camera having five six inch lenses with a ten inch lenses and took photos from 23,000 feet.
Each photo covered two hundred and twenty five square miles. One of its first government
contracts was an aerial survey of New Mexico to study soil erosion. A year later, Fairchild
introduced a better high altitude camera with nine-lens in one unit that could take a photo
of 600 square miles with each exposure from 30,000 feet.
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World War II
In 1939 Sidney Cotton and Flying Officer Maurice Long bottom of the RAF were among the
first to suggest that airborne reconnaissance may be a task better suited to fast, small
aircraft which would use their speed and high service ceiling to avoid detection and
interception. Although this seems obvious now, with modern reconnaissance tasks
performed by fast, high flying aircraft, at the time it was radical thinking.
They proposed the use of Spitfires with their armament and radios removed and replaced
with extra fuel and cameras. This led to the development of the Spitfire PR variants.
Spitfires proved to be extremely successful in their reconnaissance role and there were
many variants built specifically for that purpose. They served initially with what later
became No. 1 Photographic Reconnaissance Unit (PRU). In 1928, the RAF developed an
electric heating system for the aerial camera. This allowed reconnaissance aircraft to take
pictures from very high altitudes without the camera parts freezing. Based at RAF
Medmenham, the collection and interpretation of such photographs became a considerable
enterprise.
Cotton's aerial photographs were far ahead of their time. Together with other members of
the 1 PRU, he pioneered the techniques of high-altitude, high-speed stereoscopic
photography that were instrumental in revealing the locations of many crucial military and
intelligence targets. According to R.V. Jones, photographs were used to establish the size
and the characteristic launching mechanisms for both the V-1 flying bomb and the V-2
rocket. Cotton also worked on ideas such as a prototype specialist reconnaissance aircraft
and further refinements of photographic equipment. At the peak, the British flew over 100
reconnaissance flights a day, yielding 50,000 images per day to interpret. Similar efforts
were taken by other countries.
Uses
Aerial photography is used in cartography (particularly in photogrammetric surveys, which
are often the basis for topographic maps), land-use planning, archaeology, movie
production, environmental studies, surveillance, commercial advertising, conveyancing,
and artistic projects. An example of how aerial photography is used in the field of
Archaeology is the mapping project done at the site Angkor Borei in Cambodia from 1995-
1996. Using aerial photography, archaeologists were able to identify archaeological
features, including 112 water features (reservoirs, artificially constructed pools and natural
ponds) within the walled site of Angkor Borei. In the United States, aerial photographs are
used in many Phase I Environmental Site Assessments for property analysis.
Platforms
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Radio-controlled model aircraft
Advances in radio controlled models have made it possible for model aircraft to conduct
low-altitude aerial photography. This has benefited real-estate advertising, where
commercial and residential properties are the photographic subject. Full-size, manned
aircraft are prohibited from low flights above populated locations. Small scale model
aircraft offer increased photographic access to these previously restricted areas. Miniature
vehicles do not replace full size aircraft, as full size aircraft are capable of longer flight
times, higher altitudes, and greater equipment payloads. They are, however, useful in any
situation in which a full-scale aircraft would be dangerous to operate. Examples would
include the inspection of transformers atop power transmission lines and slow, low-level
flight over agricultural fields, both of which can be accomplished by a large-scale radio
controlled helicopter. Professional-grade, gyroscopically stabilized camera platforms are
available for use under such a model; a large model helicopter with a 26cc gasoline engine
can hoist a payload of approximately seven kilograms (15 lbs).
Recent (2006) FAA regulations grounding all commercial RC model flights have been
upgraded to require formal FAA certification before permission to fly at any altitude in
USA.
In Australia Civil Aviation Safety Regulation 101 (CASR 101) allows for commercial use of
radio control aircraft. Under these regulations radio controlled unmanned aircraft for
commercial are referred to as Unmanned Aircraft Systems (UAS), where as radio controlled
aircraft for recreational purposes are referred to as model aircraft. Under CASR 101,
businesses/persons operating radio controlled aircraft commercially are required to hold
an Operator Certificate, just like manned aircraft operators. Pilots of radio controlled
aircraft operating commercially are also required to be licensed by the Civil Aviation Safety
Authority (CASA). Whilst a small UAS and model aircraft may actually be identical, unlike
model aircraft, a UAS may enter controlled airspace with approval, and operate within
close proximity to an aerodrome.
Due to a number of illegal operators in Australia making false claims of being approved,
CASA maintains and publishes a list of approved UAS operators because anything capable
of being viewed from a public space is considered outside the realm of privacy in the
United States, aerial photography may legally document features and occurrences on
private property.
Types
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Oblique
Photographs taken at an angle are called oblique photographs. If they are taken from a low
angle earth surface–aircraft, they are called low oblique and photographs taken from a high
angle are called high or steep oblique.
Vertical
Vertical photographs are taken straight down. They are mainly used in photogrammetry
and image interpretation. Pictures that will be used in photogrammetry are traditionally
taken with special large format cameras with calibrated and documented geometric
properties.
Combinations
Aerial photographs are often combined. Depending on their purpose it can be done in
several ways, of which a few are listed below.
· Panoramas can be made by stitching several photographs taken with one hand held
camera.
· In pictometry five rigidly mounted cameras provide one vertical and four low
oblique pictures that can be used together.
· In some digital cameras for aerial photogrammetry images from several imaging
elements, sometimes with separate lenses, are geometrically corrected and combined
to one image in the camera.
Orthophotos
Vertical photographs are often used to create orthophotos, alternatively known
as orthophotomaps, photographs which have been geometrically "corrected" so as to be
usable as a map. In other words, an orthophoto is a simulation of a photograph taken from
an infinite distance, looking straight down to nadir. Perspective must obviously be
removed, but variations in terrain should also be corrected for. Multiple geometric
transformations are applied to the image, depending on the perspective and terrain
corrections required on a particular part of the image.
Orthophotos are commonly used in geographic information systems, such as are used by
mapping agencies (e.g. Ordnance Survey) to create maps. Once the images have been
aligned, or "registered", with known real-world coordinates, they can be widely deployed.
Large sets of orthophotos, typically derived from multiple sources and divided into "tiles"
(each typically 256 x 256 pixels in size), are widely used in online map systems such
as Google Maps. Open Street Map offers the use of similar orthophotos for deriving new
map data. Google Earth overlays orthophotos or satellite imagery onto a digital elevation
model to simulate 3D landscapes.
Aerial Video
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With advancements in video technology, aerial video is becoming more popular.
Orthogonal video is shot from aircraft mapping pipelines, crop fields, and other points of
interest. Using GPS, video may be embedded with meta data and later synced with a video
mapping program.
This "Spatial Multimedia" is the timely union of digital media including still photography,
motion video, stereo, panoramic imagery sets, immersive media constructs, audio, and
other data with location and date-time information from the GPS and other location
designs.
Aerial videos are emerging Spatial Multimedia which can be used for scene understanding
and object tracking. The input video is captured by low flying aerial platforms and typically
consists of strong parallax from non-ground-plane structures. The integration of digital
video, global positioning systems (GPS) and automated image processing will improve the
accuracy and cost-effectiveness of data collection and reduction. Several different aerial
platforms are under investigation for the data collection.
Satellite
In the context of spaceflight, a satellite is an artificial object which has been intentionally
placed into orbit. Such objects are sometimes called artificial satellites to distinguish
them from natural satellites such as the Moon.
The world's first artificial satellite, the Sputnik 1, was launched by the Soviet Union in
1957. Since then, thousands of satellites have been launched into orbit around the Earth.
Some satellites, notably space stations, have been launched in parts and assembled in orbit.
Artificial satellites originate from more than 50 countries and have used the satellite
launching capabilities of ten nations. A few hundred satellites are currently operational,
whereas thousands of unused satellites and satellite fragments orbit the Earth as space
debris. A few space probes have been placed into orbit around other bodies and become
artificial satellites to the Moon, Mercury, Venus, Mars, Jupiter, Saturn, Vesta, Eros, and
the Sun.
Satellites are used for a large number of purposes. Common types include military and
civilian Earth observation satellites, communications satellites, navigation satellites,
weather satellites, and research satellites. Space stations and human spacecraft in orbit are
also satellites. Satellite orbits vary greatly, depending on the purpose of the satellite, and
are classified in a number of ways. Well-known (overlapping) classes include low Earth
orbit, polar orbit, and geostationary orbit.
About 6,600 satellites have been launched. The latest estimates are that 3,600 remain in
orbit. Of those, about 1,000 are operational;[2][3] the rest have lived out their useful lives and
are part of the space debris. Approximately 500 operational satellites are in low-Earth
orbit, 50 are in medium-Earth orbit (at 20,000 km), the rest are in geostationary orbit (at
36,000 km).
Satellites are propelled by rockets to their orbits. Usually the launch vehicle itself is a
rocket lifting off from a launch pad on land. In a minority of cases satellites are launched at
sea (from a submarine or a mobile maritime platform) or aboard a plane.
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Satellites are usually semi-independent computer-controlled systems. Satellite subsystems
attend many tasks, such as power generation, thermal control, telemetry, attitude
control and orbit control.
Space Surveillance Network
The United States Space Surveillance Network (SSN), a division of The United States
Strategic Command, has been tracking objects in Earth's orbit since 1957 when the Soviets
opened the space age with the launch of Sputnik I. Since then, the SSN has tracked more
than 26,000 objects. The SSN currently tracks more than 8,000 man-made orbiting objects.
The rest have re-entered Earth's atmosphere and disintegrated, or survived re-entry and
impacted the Earth. The SSN tracks objects that are 10 centimeters in diameter or larger;
those now orbiting Earth range from satellites weighing several tons to pieces of spent
rocket bodies weighing only 10 pounds. About seven percent are operational satellites (i.e.
~560 satellites), the rest are space debris. The United States Strategic Command is
primarily interested in the active satellites, but also tracks space debris which upon reentry
might otherwise be mistaken for incoming missiles.
A search of the NSSDC Master Catalog at the end of October 2010 listed 6,578 satellites
launched into orbit since 1957, the latest being Chang'e 2, on 1 October 2010.
Non-Military Satellite Services
There are three basic categories of non-military satellite services:
Fixed satellite services
Fixed satellite services handle hundreds of billions of voice, data, and video transmission
tasks across all countries and continents between certain points on the Earth's surface.
Mobile satellite systems
Mobile satellite systems help connect remote regions, vehicles, ships, people and aircraft to
other parts of the world and/or other mobile or stationary communications units, in
addition to serving as navigation systems.
Scientific research satellites (commercial and noncommercial)
Scientific research satellites provide meteorological information, land survey data (e.g.
remote sensing), Amateur (HAM) Radio, and other different scientific research applications
such as earth science, marine science, and atmospheric research.
Types
· Anti-Satellite weapons/"Killer Satellites" are satellites that are designed to
destroy enemy warheads, satellites, and other space assets.
· Astronomical satellites are satellites used for observation of distant planets,
galaxies, and other outer space objects.
· Biosatellites are satellites designed to carry living organisms, generally for
scientific experimentation.
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· Communications satellites are satellites stationed in space for the purpose
of telecommunications. Modern communications satellites typically use
geosynchronous orbits, Molniya orbits or Low Earth orbits.
· Miniaturized satellites are satellites of unusually low masses and small sizes. New
classifications are used to categorize these satellites: mini satellite (500–
100 kg), microsatellite (below 100 kg), nanosatellite (below 10 kg).
· Navigational satellites are satellites which use radio time signals transmitted to
enable mobile receivers on the ground to determine their exact location. The relatively
clear line of sight between the satellites and receivers on the ground, combined with
ever-improving electronics, allows satellite navigation systems to measure location to
accuracies on the order of a few meters in real time.
· Reconnaissance satellites are Earth observation satellite or communications
satellite deployed for military or intelligence applications. Very little is known about
the full power of these satellites, as governments who operate them usually keep
information pertaining to their reconnaissance satellites classified.
· Earth observation satellites are satellites intended for non-military uses such
as environmental monitoring, meteorology, map making etc. (See especially Earth
Observing System.)
· Tether satellites are satellites which are connected to another satellite by a thin
cable called a tether.
· Weather satellites are primarily used to monitor Earth's weather and climate.
· Recovery satellites are satellites that provide a recovery of reconnaissance,
biological, space-production and other payloads from orbit to Earth.
· Manned spacecraft (spaceships) are large satellites able to put humans into (and
beyond) an orbit, and return them to Earth. Spacecraft including space
planes of reusable systems have major propulsion or landing facilities. They can be
used as transport to and from the orbital stations.
· Space stations are man-made orbital structures that are designed for human
beings to live on in outer space. A space station is distinguished from other manned
spacecraft by its lack of major propulsion or landing facilities. Space stations are
designed for medium-term living in orbit, for periods of weeks, months, or even years.
· A Skyhook is a proposed type of tethered satellite/ion powered space station that
serves as a terminal for suborbital launch vehicles flying between the Earth and the
lower end of the Skyhook, as well as a terminal for spacecraft going to, or arriving from,
higher orbit, the Moon, or Mars, at the upper end of the Skyhook
Orbit Types
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The first satellite, Sputnik 1, was put into orbit around Earth and was therefore
in geocentric orbit. By far this is the most common type of orbit with approximately 2,456
artificial satellites orbiting the Earth. Geocentric orbits may be further classified by their
altitude, inclination and eccentricity.
The commonly used altitude classifications of geocentric orbit are Low Earth
orbit (LEO), Medium Earth orbit (MEO) and High Earth orbit (HEO). Low Earth orbit is any
orbit below 2,000 km. Medium Earth orbit is any orbit between 2,000km-35,786 km. High
Earth orbit is any orbit higher than 35,786 km.
Centric classifications
· Geocentric orbit: An orbit around the planet Earth, such as the Moon or artificial
satellites. Currently there are approximately 2,465 artificial satellites orbiting the
Earth.
· Heliocentric orbit: An orbit around the Sun. In our Solar System, all
planets, comets, and asteroids are in such orbits, as are many artificial satellites and
pieces of space debris. Moons by contrast are not in a heliocentric orbit but rather orbit
their parent planet.
· Areocentric orbit: An orbit around the planet Mars, such as by moons or artificial
satellites.
The general structure of a satellite is that it is connected to the earth stations that are
present on the ground and connected through terrestrial links.
Altitude classifications
· Low Earth orbit (LEO): Geocentric orbits ranging in altitude from 0–2000 km (0–
1240 miles)
· Medium Earth orbit (MEO): Geocentric orbits ranging in altitude from 2,000 km
(1,200 mi)-35,786 km (22,236 mi). Also known as an intermediate circular orbit.
· Geosynchronous Orbit (GEO): Geocentric circular orbit with an altitude of 35,786
kilometres (22,236 mi). The period of the orbit equals one sidereal day, coinciding with
the rotation period of the Earth. The speed is approximately 3,000 metres per second
(9,800 ft/s).
· High Earth orbit (HEO): Geocentric orbits above the altitude of geosynchronous
orbit 35,786 km (22,236 mi).
Inclination classifications
· Inclined orbit: An orbit whose inclination in reference to the equatorial plane is not
zero degrees.
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· Polar orbit: An orbit that passes above or nearly above both poles of the
planet on each revolution. Therefore it has an inclination of (or very close to)
90 degrees.
· Polar sun synchronous orbit: A nearly polar orbit that passes
the equator at the same local time on every pass. Useful for image taking satellites
because shadows will be nearly the same on every pass.
Eccentricity classifications
· Circular orbit: An orbit that has an eccentricity of 0 and whose path traces a circle.
· Hohmann transfer orbit: An orbit that moves a spacecraft from one
approximately circular orbit, usually the orbit of a planet, to another, using two
engine impulses. The perihelion of the transfer orbit is at the same distance from
the Sun as the radius of one planet's orbit, and the aphelion is at the other. The two
rocket burns change the spacecraft's path from one circular orbit to the transfer
orbit, and later to the other circular orbit. This maneuver was named after Walter
Hohmann.
· Elliptic orbit: An orbit with an eccentricity greater than 0 and less than 1 whose
orbit traces the path of an ellipse.
· Geosynchronous transfer orbit: An elliptic orbit where the perigee is at the
altitude of a Low Earth orbit (LEO) and the apogee at the altitude of a
geosynchronous orbit.
· Geostationary transfer orbit: An elliptic orbit where the perigee is at the
altitude of a Low Earth orbit (LEO) and the apogee at the altitude of a geostationary
orbit.
· Molniya orbit: A highly elliptic orbit with inclination of 63.4° and orbital
period of half of a sidereal day (roughly 12 hours). Such a satellite spends most of
its time over two designated areas of the planet(specifically Russia and the United
States).
· Tundra orbit: A highly elliptic orbit with inclination of 63.4° and orbital
period of one sidereal day (roughly 24 hours). Such a satellite spends most of its
time over a single designated area of the planet.
Synchronous classifications
· Synchronous orbit: An orbit where the satellite has an orbital period equal to the
average rotational period (earth's is: 23 hours, 56 minutes, 4.091 seconds) of the body
being orbited and in the same direction of rotation as that body. To a ground observer
such a satellite would trace an analemma (figure 8) in the sky.
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· Semi-synchronous orbit (SSO): An orbit with an altitude of approximately
20,200 km (12,600 mi) and an orbital period equal to one-half of the average rotational
period (earth's is approximately 12 hours) of the body being orbited
· Geosynchronous orbit (GSO): Orbits with an altitude of approximately 35,786 km
(22,236 mi). Such a satellite would trace an analemma (figure 8) in the sky.
· Geostationary orbit (GEO): A geosynchronous orbit with an inclination of
zero. To an observer on the ground this satellite would appear as a fixed point in
the sky.
· Clarke orbit: Another name for a geostationary orbit. Named after
scientist and writer Arthur C. Clarke.
· Super synchronous orbit: A disposal / storage orbit above GSO/GEO.
Satellites will drift west. Also a synonym for Disposal orbit.
· Sub synchronous orbit: A drift orbit close to but below GSO/GEO. Satellites
will drift east.
· Graveyard orbit: An orbit a few hundred kilometers
above geosynchronous that satellites are moved into at the end of their operation.
· Disposal orbit: A synonym for graveyard orbit.
· Junk orbit: A synonym for graveyard orbit.
· Aero synchronous orbit: A synchronous orbit around the planet Mars with an
orbital period equal in length to Mars' sidereal day, 24.6229 hours.
· Aero stationary orbit (ASO): A circular aero synchronous orbit on the equatorial
plane and about 17000 km (10557 miles) above the surface. To an observer on the
ground this satellite would appear as a fixed point in the sky.
· Helio synchronous orbit: A heliocentric orbit about the Sun where the satellite's
orbital period matches the Sun's period of rotation. These orbits occur at a radius of
24,360 Gm (0.1628 AU) around the Sun, a little less than half of the orbital
radius of Mercury.
Special classifications
· Sun-synchronous orbit: An orbit which combines altitude and inclination in such a
way that the satellite passes over any given point of the planets' surface at the same
local solar time. Such an orbit can place a satellite in constant sunlight and is useful
for imaging, spy, and weather satellites.
· Moon orbit: The orbital characteristics of Earth's Moon. Average altitude of
384,403 kilometers (238,857 mi), elliptical–inclined orbit.
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Pseudo-orbit classifications
· Horseshoe orbit: An orbit that appears to a ground observer to be orbiting a
certain planet but is actually in co-orbit with the planet. See asteroids 3753 (Cruithne)
and 2002 AA29.
· Exo-orbit: A maneuver where a spacecraft approaches the height of orbit but lacks
the velocity to sustain it.
· Suborbital spaceflight: A synonym for exo-orbit.
· Lunar transfer orbit (LTO)
· Prograde orbit: An orbit with an inclination of less than 90°. Or rather, an orbit that
is in the same direction as the rotation of the primary.
· Retrograde orbit: An orbit with an inclination of more than 90°. Or rather, an orbit
counter to the direction of rotation of the planet. Apart from those in sun-synchronous
orbit, few satellites are launched into retrograde orbit because the quantity of fuel
required to launch them is much greater than for a prograde orbit. This is because
when the rocket starts out on the ground, it already has an eastward component of
velocity equal to the rotational velocity of the planet at its launch latitude.
· Halo orbit and Lissajous orbit: Orbits "around" Lagrangian points.
Satellite Subsystems
The satellite's functional versatility is imbedded within its technical components and its
operations characteristics. Looking at the "anatomy" of a typical satellite, one discovers two
modules. Note that some novel architectural concepts such as Fractionated
Spacecraft somewhat upset this taxonomy.
Spacecraft bus or service module
This bus module consist of the following subsystems:
· The Structural Subsystem
The structural subsystem provides the mechanical base structure with adequate stiffness
to withstand stress and vibrations experienced during launch, maintain structural integrity
and stability while on station in orbit, and shields the satellite from extreme temperature
changes and micro-meteorite damage.
· The Telemetry Subsystem (aka Command and Data Handling, C&DH)
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The telemetry subsystem monitors the on-board equipment operations, transmits
equipment operation data to the earth control station, and receives the earth control
station's commands to perform equipment operation adjustments.
· The Power Subsystem
The power subsystem consists of solar panels to convert solar energy into electrical power,
regulation and distribution functions, and batteries that store power and supply the
satellite when it passes into the Earth's shadow. Nuclear power sources (Radioisotope
thermoelectric generator have also been used in several successful satellite programs
including the Nimbus program (1964–1978).
· The Thermal Control Subsystem
The thermal control subsystem helps protect electronic equipment from extreme
temperatures due to intense sunlight or the lack of sun exposure on different sides of the
satellite's body (e.g. Optical Solar Reflector)
· The Attitude and Orbit Control Subsystem
The attitude and orbit control subsystem consists of sensors to measure vehicle
orientation; control laws embedded in the flight software; and actuators (reaction wheels,
thrusters) to apply the torques and forces needed to re-orient the vehicle to a desired
attitude, keep the satellite in the correct orbital position and keep antennas positioning in
the right directions.
Communication payload
The second major module is the communication payload, which is made up of
transponders. A transponder is capable of :
· Receiving uplinked radio signals from earth satellite transmission stations
(antennas).
· Amplifying received radio signals
· Sorting the input signals and directing the output signals through input/output
signal multiplexers to the proper downlink antennas for retransmission to earth
satellite receiving stations (antennas).
End of Life
When satellites reach the end of their mission, satellite operators have the option of de-orbiting
the satellite, leaving the satellite in its current orbit or moving the satellite to
a graveyard orbit. Historically, due to budgetary constraints at the beginning of satellite
missions, satellites were rarely designed to be de-orbited. One example of this practice is
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the satellite Vanguard 1. Launched in 1958, Vanguard 1, the 4th manmade satellite put in
Geocentric orbit, was still in orbit as of August 2009.
Instead of being de-orbited, most satellites are either left in their current orbit or moved to
a graveyard orbit. As of 2002, the FCC requires all geostationary satellites to commit to
moving to a graveyard orbit at the end of their operational life prior to launch. In cases of
uncontrolled de-orbiting, the major variable is the solar flux, and the minor variables the
components and form factors of the satellite itself, and the gravitational perturbations
generated by the Sun and the Moon (as well as those exercised by large mountain ranges,
whether above or below sea level). The nominal breakup altitude due to aerodynamic
forces and temperatures is 78 km, with a range between 72 and 84 km. Solar panels,
however, are destroyed before any other component at altitudes between 90 and 95 km.
UNIT-II
Image Interpretation
To derive useful spatial information from images is the task of image interpretation. It
includes
ï detection: such as search for hot spots in mechanical and electrical facilities and white
spot in x-ray images. This procedure is often used as the first step of image interpretation.
ï identification: recognition of certain target. A simple example is to identify vegetation
types, soil types, rock types and water bodies. The higher the spatial/spectral resolution of
an image, the more detail we can derive from the image.
ï delineation: to outline the recognized target for mapping purposes. Identification and
delineation combined together are used to map certain subjects. If the whole image is to be
processed by these two procedures, we call it image classification.
ï enumeration: to count certain phenomena from the image. This is done based on
detection and identification. For example, in order to estimate household income of the
population, we can count the number of various residential units.
ï mensuration: to measure the area, the volume, the amount,and the length of certain
target from an image. This often involves all the procedures mentioned above. Simple
examples include measuring the length of a river and the acreage of a specific land-cover
class. More complicated examples include an estimation of timber volume, river discharge,
crop productivity, river basin radiation and evapotranspiration.
In order to do a good job in the image interpretation, and in later digital image analysis, one
has to be familiar with the subject under investigation, the study area and the remote
sensing system available to him. Usually, a combined team consisting of the subject
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specialists and the remote sensing image analysis specialists is required for a relatively
large image interpretation task.
Depending on the facilities that an image interpreter has, he might interpret images in raw
form, corrected form or enhanced form. Correction and enhancement are usually done
digitally.
Elements on which image interpretation are based
ï Image tone, grey level, or multispectral grey-level vector
Human eyes can differentiate over 1000 colors but only about 16 grey levels. Therefore,
colour images are preferred in image interpretation. One difficulty involved is use of
multispectral image with a dimensionality of over 3. In order to make use of all the
information available in each band of image, one has to somehow reduce the image
dimensionality.
ï Image texture
Spatial variation of image tones. Texture is used as an important clue in image
interpretation. It is very easy for human interpreters to include it in their mental process.
Most texture patterns appear irregular on an image.
ï Pattern
Regular arrangement of ground objects. Examples are residential area on an aerial
photograph and mountains in regular arrangement on a satellite imagery.
ï Association
A specific object co-occurring with another object. Some examples of association are an
outdoor swimming pool associated with a recreation center and a playground associated
with a school.
ï Shadow
Object shadow is very useful when the phenomena under study have vertical variation.
Examples include trees, high buildings, mountains, etc.
ï Shape
Agricultural fields and human-built structures have regular shapes. These can be used to
identify various target.
ï Size
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Relative size of buildings can tell us about the type of land uses while relative sizes of tree
crowns can tell us about the approximate age of trees.
ï Site
Broad leaf trees are distributed at lower and warmer valleys while coniferous trees tend to
be distributed on a higher elevation, such as tundra. Location is used in image
interpretation.
Image interpretation strategies
Direct recognition: Identification of targets.
Land-cover classification
(Land cover is the physical evidence of the earth's surface.)
- indirect interpretation
to map something that is not directly observable in the image. This is used to classify land
use types (Gong and Howarth, 1992b). Land-use is the human activities on a piece of land.
It is closely related to land-cover types. For example, a residential land-use type is
composed of roof cover, lawn, trees and paved surfaces.
- from known to unknown
To interpret an area where the interpreter is familiar with first, then interpret the areas
where the interpreter is not familiar with (Chen et al, 1989). This can be assisted by field
observation
- from direct to indirect
In order to obtain forest volume, one might have to determine what is observable from the
image, such as tree canopies, shadows etc. Then the volume can be derived. We can also
estimate the depth of permafrost using the surface cover information (Peddle, 1991).
- Use of collateral information
Census data,and topographical maps and other thematic maps may all be useful during
image interpretation.
Principles of Image Interpretation
Strategy for Image Interpretation and Differential Diagnosis
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This section is included to aid the beginning surgeon or oncologist in developing a basic
strategy for image interpretation. Normally, the radiologist chooses and supervises the
appropriate imaging study, evaluates and interprets the images, and communicates its
significance to the referring physician. However, frequent dialogue between the referring
physician and the radiologist will significantly improve interpretation of the imaging study.
Accurately interpreting an imaging study of the head and neck requires a systematic
method of observation, knowledge of the complex anatomy and pathophysiology, and an
understanding of imaging principles. The differential diagnosis of lesions of the head and
neck requires a systematic approach as well. One such diagnostic imaging process is
summarized here:
1. Obtain clinical data: age, sex, history, physical findings.
2. Survey the films for all …
4. Visual Image Interpretation
Virtually all people live with the visual perception of his/her environment. This
experience is also used to interpret images (in 2D) and 3-dimensional structures and
specimens.
The visual interpretation of satelllite images is a complex process. It includes the meaning
of the image content but also goes beyond what can be seen on the image in order to
recognise spatial and landscape patterns. This process can be roughly divided into 2 levels:
1. The recognition of objects such as streets, fields, rivers, etc. The quality of
recognition depends on the expertise in image interpretation and visual perception.
2. A true interpretation can be ascertained through conclusions (from previously
recognized objects) of situations, recovery, etc. Subject specific knowledge and
expertise are crucial.
Interpretation Factors↓
The first step recognition of objects and structures, relates to the followong saying: "I can
recognize in an image only what I already know." Hence, previous knowledge and
experience play a very large role in the interpretation process as only through subject
specific knowledge connections can be made between the key underlying processes.
Both steps, recognition and interpretation, do not "mechanically" follow one another, but
rather run through a repetitive process, where both steps heavily rely on one another
(Albertz 2007).
The Practice of Image Interpretation
· Acquisition of documents: Satellite images, maps, etc.
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· Pre-interpretation: gross distribution, apportionment of the area, etc.
· Partial land pre-investigation: Recognition of regional particularities
· Detail interpretation: Core of the work: areas will be individually considered,
objects will be recognised and compared to maps. Objects that are easily identifiable
are addressed first.
· Land Examination / Field Comparison: a method to double check uncertain
interpretation results
· Depiction of the results: through maps, map-like sketches, thematic mapping, etc.
5. Image Processing
Corrections
Image processing is a process which makes an image interpretable for a specific use. There
are many methods, but only the most common will be presented here.
Geometric Correction
The geometric correction of image data is an important prerequisitewhich must be
performed prior to using images in geographic information systems (GIS) and other image
processing programs. To process the data with other data or maps in a GIS, all of the data
must have the same reference system. A geometrical correction, also called geo-referencing,
is a procedure where the content of a map will be assigned a spatial
coordinate system (for example, geographical latitude and longitude).
In geo-referencing, image points and pass points need to be searched, which then can be
recognized in the coordinates. Pass points are usually determined with a GPS receiver on
the terrain or with maps. Visual street crossings, bridges over water, etc. can be identified,
and their coordinates will be noted. These points will then be coordinated with identical
image points of the not yet geo-referenced satellite image. These correlations can ensure
projections with the help of various additional procedures.
Radiometric Correction
System corrections are important, when technical defects and deficiencies of the sensor
and data transfer systems lead to mistakes in the image data construction. Causes can
be detector failure and/or power failure from detectors operating simultaneously.
In scanners such as Land sat TM and MSS with 6 respectively 15 scan rows which are used
for the same spectral area, a failure of scan rows occurs. These errors always appear at the
same intervals and create a characteristic striping (banding) in the image.
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Image enhancement
Why do we enhance satellite images? Different methods of image enhancement are used
to prepare the "raw data" so that the actual analysis of images will be easier, faster and
more reliable. The choice of method is dependent on the objective of the analysis. Two
processes are presented below:
Histogram Stretches
In digital image processing the statistics of images are portrayed in agreyscale
histogram (frequency distribution of grey values)
The form of a histogram describes the contrast range of a satellite image and permits
comments about its homogeneity. For example, a grey scale distribution with an extreme
maximum indicates small contrast. A simply stretched maximum indicates homogeneity in
the image, but also a larger contrast range.
A histogram stretch is a method to process individual values in the image. The stretch is
used as a contrasting presentation of the data. The contrast stretch can be used in many
different processes. The entry data will always be stretched over the entire area of 0-255.
Filter
So called filter operations change image structures by calculating greyscale value
relations of the neighbouring pixels. The filters use coefficient matrixes which cut a
small area or matrix out of the original image centered on an individual image point. The
filter/matrix then has to "run" over the entire image.
UNIT-IV
Geographic information system
A geographic information system (GIS) is a computer system designed to capture, store,
manipulate, analyze, manage, and present all types of geographical data. The acronym GIS
is sometimes used for geographical information science or geospatial information
studies to refer to the academic discipline or career of working with
geographic information systems and is a large domain within the broader academic
discipline of Geo informatics.
GIS can be thought of as a system that provides spatial data entry, management, retrieval,
analysis, and visualization functions. The implementation of a GIS is often driven by
jurisdictional (such as a city), purpose, or application requirements. Generally, a GIS
implementation may be custom-designed for an organization. Hence, a GIS deployment
developed for an application, jurisdiction, enterprise, or purpose may not be necessarily
interoperable or compatible with a GIS that has been developed for some other application,
jurisdiction, enterprise, or purpose. What goes beyond a GIS is a spatial data infrastructure,
a concept that has no such restrictive boundaries.
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In a general sense, the term describes any information system that integrates stores, edits,
analyzes, shares, and displays geographic information for informing decision making. GIS
applications are tools that allow users to create interactive queries (user-created searches),
analyze spatial information, edit data in maps, and present the results of all these
operations. Geographic information science is the science underlying geographic concepts,
applications, and systems.
The first known use of the term "Geographic Information System" was by Roger
Tomlinson in the year 1968 in his paper "A Geographic Information System for Regional
Planning". Tomlinson is also acknowledged as the "father of GIS"
Application
GIS is a relatively broad term that can refer to a number of different technologies,
processes, and methods. It is attached to many operations and has many applications
related to engineering, planning, management, transport/logistics, insurance,
telecommunications, and business. For that reason, GIS and location intelligence
applications can be the foundation for many location-enabled services that rely on analysis,
visualization and dissemination of results for collaborative decision making.
History and Development
One of the first applications of spatial analysis in epidemiology is the 1832 "Rapport sur la
marche et les effets du choléra dans Paris et le département de la Seine". The French
geographer Charles Picquet represented the 48 districts of the city of Paris by halftone
color gradient according to the percentage of deaths by cholera per 1,000 inhabitants.
In 1854 John Snow depicted a cholera outbreak in London using points to represent the
locations of some individual cases, possibly the earliest use of a geographic methodology in
epidemiology. His study of the distribution of cholera led to the source of the disease, a
contaminated water pump (the Broad Street Pump, whose handle he disconnected, thus
terminating the outbreak).
While the basic elements of topography and theme existed previously in cartography, the
John Snow map was unique, using cartographic methods not only to depict but also to
analyze clusters of geographically dependent phenomena.
The early 20th century saw the development of photozincography, which allowed maps to
be split into layers, for example one layer for vegetation and another for water. This was
particularly used for printing contours – drawing these was a labour-intensive task but
having them on a separate layer meant they could be worked on without the other layers to
confuse the draughtsman. This work was originally drawn on glass plates but later plastic
film was introduced, with the advantages of being lighter, using less storage space and
being less brittle, among others. When all the layers were finished, they were combined
into one image using a large process camera. Once color printing came in, the layers idea
was also used for creating separate printing plates for each colour. While the use of layers
much later became one of the main typical features of a contemporary GIS, the
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photographic process just described is not considered to be a GIS in itself – as the maps
were just images with no database to link them to.
Computer hardware development spurred by nuclear weapon research led to general-purpose
computer "mapping" applications by the early 1960s.
The year 1960 saw the development of the world's first true operational GIS in Ottawa,
Ontario, Canada by the federal Department of Forestry and Rural Development. Developed
by Dr. Roger Tomlinson, it was called the Canada Geographic Information System (CGIS)
and was used to store, analyze, and manipulate data collected for the Canada Land
Inventory – an effort to determine the land capability for rural Canada by mapping
information about soils, agriculture, recreation, wildlife, waterfowl, forestry and land use at
a scale of 1:50,000. A rating classification factor was also added to permit analysis.
CGIS was an improvement over "computer mapping" applications as it provided
capabilities for overlay, measurement, and digitizing/scanning. It supported a national
coordinate system that spanned the continent, coded lines as arcs having a true
embedded topology and it stored the attribute and locational information in separate files.
As a result of this, Tomlinson has become known as the "father of GIS", particularly for his
use of overlays in promoting the spatial analysis of convergent geographic data.
CGIS lasted into the 1990s and built a large digital land resource database in Canada. It was
developed as a mainframe-based system in support of federal and provincial resource
planning and management. Its strength was continent-wide analysis of complex datasets.
The CGIS was never available commercially.
In 1964 Howard T. Fisher formed the Laboratory for Computer Graphics and Spatial
Analysis at the Harvard Graduate School of Design (LCGSA 1965–1991), where a number of
important theoretical concepts in spatial data handling were developed, and which by the
1970s had distributed seminal software code and systems, such as SYMAP, GRID, and
ODYSSEY – that served as sources for subsequent commercial development—to
universities, research centers and corporations worldwide.
By the early 1980s, M&S Computing (later Intergraph) along with Bentley Systems
Incorporated for the CAD platform, Environmental Systems Research Institute (ESRI),
CARIS (Computer Aided Resource Information System), MapInfo Corporation and
ERDAS (Earth Resource Data Analysis System) emerged as commercial vendors of
GIS software, successfully incorporating many of the CGIS features, combining the first
generation approach to separation of spatial and attribute information with a second
generation approach to organizing attribute data into database structures. In parallel, the
development of two public domain systems (MOSS and GRASS GIS) began in the late 1970s
and early 1980s.
In 1986, Mapping Display and Analysis System (MIDAS), the first desktop GIS product
emerged for the DOS operating system. This was renamed in 1990 to MapInfo for Windows
when it was ported to the Microsoft Windows platform. This began the process of moving
GIS from the research department into the business environment.
By the end of the 20th century, the rapid growth in various systems had been consolidated
and standardized on relatively few platforms and users were beginning to explore viewing
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GIS data over the Internet, requiring data format and transfer standards. More recently, a
growing number of free, open-source GIS packages run on a range of operating systems and
can be customized to perform specific tasks. Increasingly geospatial data and mapping
applications are being made available via the world wide web.
GIS Techniques and Technology
Modern GIS technologies use digital information, for which various digitized data creation
methods are used. The most common method of data creation is digitization, where a hard
copy map or survey plan is transferred into a digital medium through the use of a CAD
program, and geo-referencing capabilities. With the wide availability of ortho-rectified
imagery (both from satellite and aerial sources), heads-up digitizing is becoming the main
avenue through which geographic data is extracted. Heads-up digitizing involves the
tracing of geographic data directly on top of the aerial imagery instead of by the traditional
method of tracing the geographic form on a separate digitizing tablet (heads-down
digitizing).
Relating information from different sources
GIS uses spatio-temporal (space-time) location as the key index variable for all other
information. Just as a relational database containing text or numbers can relate many
different tables using common key index variables, GIS can relate unrelated information by
using location as the key index variable. The key is the location and/or extent in space-time.
Any variable that can be located spatially, and increasingly also temporally, can be
referenced using a GIS. Locations or extents in Earth space–time may be recorded as
dates/times of occurrence, and x, y, and z coordinates representing, longitude, latitude,
and elevation, respectively. These GIS coordinates may represent other quantified systems
of temporo-spatial reference (for example, film frame number, stream gage station,
highway mile-marker, surveyor benchmark, building address, street intersection, entrance
gate, water depth sounding, POS or CAD drawing origin/units). Units applied to recorded
temporal-spatial data can vary widely (even when using exactly the same data, see map
projections), but all Earth-based spatial–temporal location and extent references should,
ideally, be relatable to one another and ultimately to a "real" physical location or extent in
space–time.
Related by accurate spatial information, an incredible variety of real-world and projected
past or future data can be analyzed, interpreted and represented to facilitate education
and decision making. This key characteristic of GIS has begun to open new avenues of
scientific inquiry into behaviors and patterns of previously considered unrelated real-world
information.
GIS uncertainties
GIS accuracy depends upon source data, and how it is encoded to be data referenced. Land
surveyors have been able to provide a high level of positional accuracy utilizing the GPS-
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derived positions. High-resolution digital terrain and aerial imagery, powerful computers
and Web technology are changing the quality, utility, and expectations of GIS to serve
society on a grand scale, but nevertheless there are other source data that have an impact
on overall GIS accuracy like paper maps, though these may be of limited use in achieving
the desired accuracy since the aging of maps affects their dimensional stability.
In developing a digital topographic data base for a GIS, topographical maps are the main
source, and aerial photography and satellite images are extra sources for collecting data
and identifying attributes which can be mapped in layers over a location facsimile of scale.
The scale of a map and geographical rendering area representation type are very important
aspects since the information content depends mainly on the scale set and resulting
locatability of the map's representations. In order to digitize a map, the map has to be
checked within theoretical dimensions, and then scanned into a raster format, and
resulting raster data has to be given a theoretical dimension by a rubber sheeting/warping
technology process.
A quantitative analysis of maps brings accuracy issues into focus. The electronic and other
equipment used to make measurements for GIS is far more precise than the machines of
conventional map analysis. All geographical data are inherently inaccurate, and these
inaccuracies will propagate through GIS operations in ways that are difficult to predict.
Data representation
GIS data represents real objects (such as roads, land use, elevation, trees, waterways, etc.)
with digital data determining the mix. Real objects can be divided into two abstractions:
discrete objects (e.g., a house) and continuous fields (such as rainfall amount, or
elevations). Traditionally, there are two broad methods used to store data in a GIS for both
kinds of abstractions mapping references: raster images and vector. Points, lines, and
polygons are the stuff of mapped location attribute references. A new hybrid method of
storing data is that of identifying point clouds, which combine three-dimensional points
with RGB information at each point, returning a "3D color image". GIS thematic maps then
are becoming more and more realistically visually descriptive of what they set out to show
or determine.
Data capture
Data capture—entering information into the system—consumes much of the time of
GIS practitioners. There are a variety of methods used to enter data into a GIS where it is
stored in a digital format.
Existing data printed on paper or PET film maps can be digitized or scanned to produce
digital data. A digitizer produces vector data as an operator traces points, lines, and
polygon boundaries from a map. Scanning a map results in raster data that could be further
processed to produce vector data.
Survey data can be directly entered into a GIS from digital data collection systems on
survey instruments using a technique called coordinate geometry (COGO). Positions from a
global navigation satellite system (GNSS) like Global Positioning System can also be
collected and then imported into a GIS. A current trend in data collection gives users the
ability to utilize field computers with the ability to edit live data using wireless connections
26

or disconnected editing sessions. This has been enhanced by the availability of low-cost
mapping-grade GPS units with decimeter accuracy in real time. This eliminates the need to
post process, import, and update the data in the office after fieldwork has been collected.
This includes the ability to incorporate positions collected using a laser rangefinder. New
technologies also allow users to create maps as well as analysis directly in the field, making
projects more efficient and mapping more accurate.
Remotely sensed data also plays an important role in data collection and consist of sensors
attached to a platform. Sensors include cameras, digital scanners and LIDAR, while
platforms usually consist of aircraft and satellites. Recently with the development
of miniature UAVs, aerial data collection is becoming possible at much lower costs, and on a
more frequent basis. For example, the Aeryon Scout was used to map a 50-acre area with
a Ground sample distance of 1 inch (2.54 cm) in only 12 minutes.
The majority of digital data currently comes from photo interpretation of aerial
photographs. Soft-copy workstations are used to digitize features directly from stereo
pairs of digital photographs. These systems allow data to be captured in two and three
dimensions, with elevations measured directly from a stereo pair using principles of
photogrammetry. Analog aerial photos must be scanned before being entered into a soft-copy
system, for high-quality digital cameras this step is skipped.
Satellite remote sensing provides another important source of spatial data. Here satellites
use different sensor packages to passively measure the reflectance from parts of the
electromagnetic spectrum or radio waves that were sent out from an active sensor such as
radar. Remote sensing collects raster data that can be further processed using different
bands to identify objects and classes of interest, such as land cover.
When data is captured, the user should consider if the data should be captured with either
a relative accuracy or absolute accuracy, since this could not only influence how
information will be interpreted but also the cost of data capture.
After entering data into a GIS, the data usually requires editing, to remove errors, or further
processing. For vector data it must be made "topologically correct" before it can be used for
some advanced analysis. For example, in a road network, lines must connect with nodes at
an intersection. Errors such as undershoots and overshoots must also be removed. For
scanned maps, blemishes on the source map may need to be removed from the
resulting raster. For example, a fleck of dirt might connect two lines that should not be
connected.
Raster-to-vector translation
Data restructuring can be performed by a GIS to convert data into different formats. For
example, a GIS may be used to convert a satellite image map to a vector structure by
generating lines around all cells with the same classification, while determining the cell
spatial relationships, such as adjacency or inclusion.
More advanced data processing can occur with image processing, a technique developed in
the late 1960s by NASA and the private sector to provide contrast enhancement, false
colour rendering and a variety of other techniques including use of two
dimensional Fourier transforms. Since digital data is collected and stored in various ways,
27

the two data sources may not be entirely compatible. So a GIS must be able to convert
geographic data from one structure to another.
Projections, coordinate systems, and registration
The earth can be represented by various models, each of which may provide a different set
of coordinates (e.g., latitude, longitude, elevation) for any given point on the Earth's
surface. The simplest model is to assume the earth is a perfect sphere. As more
measurements of the earth have accumulated, the models of the earth have become more
sophisticated and more accurate. In fact, there are models called datums that apply to
different areas of the earth to provide increased accuracy, like NAD83 for U.S.
measurements, and the World Geodetic System for worldwide measurements.
Spatial analysis with GIS
GIS spatial analysis is a rapidly changing field, and GIS packages are increasingly including
analytical tools as standard built-in facilities, as optional toolsets, as add-ins or 'analysts'. In
many instances these are provided by the original software suppliers (commercial vendors
or collaborative non commercial development teams), whilst in other cases facilities have
been developed and are provided by third parties. Furthermore, many products offer
software development kits (SDKs), programming languages and language support,
scripting facilities and/or special interfaces for developing one's own analytical tools or
variants. The website "Geospatial Analysis" and associated book/ebook attempt to provide
a reasonably comprehensive guide to the subject. The increased availability has created a
new dimension to business intelligence termed "spatial intelligence" which, when openly
delivered via intranet, democratizes access to geographic and social network
data. Geospatial intelligence, based on GIS spatial analysis, has also become a key element
for security. GIS as a whole can be described as conversion to a vectorial representation or
to any other digitisation process.
Slope and aspect
Slope can be defined as the steepness or gradient of a unit of terrain, usually measured as
an angle in degrees or as a percentage. Aspect can be defined as the direction in which a
unit of terrain faces. Aspect is usually expressed in degrees from north. Slope, aspect, and
surface curvature in terrain analysis are all derived from neighborhood operations using
elevation values of a cell's adjacent neighbours. Slope is a function of resolution, and the
spatial resolution used to calculate slope and aspect should always be specified. Authors
such as Skidmore, Jones and Zhou and Liu have compared techniques for calculating slope
and aspect.
The following method can be used to derive slope and aspect:
The elevation at a point or unit of terrain will have perpendicular tangents (slope) passing
through the point, in an east-west and north-south direction. These two tangents give two
components, ∂z/∂x and ∂z/∂y, which then be used to determine the overall direction of
slope, and the aspect of the slope. The gradient is defined as a vector quantity with
components equal to the partial derivatives of the surface in the x and y directions.[27]
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The calculation of the overall 3x3 grid slope S and aspect A for methods that determine
east-west and north-south component use the following formulas respectively:
Zhou and Liu describe another algorithm for calculating aspect, as follows:
Data analysis
It is difficult to relate wetlands maps to rainfall amounts recorded at different points such
as airports, television stations, and schools. A GIS, however, can be used to depict two- and
three-dimensional characteristics of the Earth's surface, subsurface, and atmosphere from
information points. For example, a GIS can quickly generate a map with isopleth or contour
lines that indicate differing amounts of rainfall. Such a map can be thought of as a rainfall
contour map. Many sophisticated methods can estimate the characteristics of surfaces from
a limited number of point measurements. A two-dimensional contour map created from the
surface modeling of rainfall point measurements may be overlaid and analyzed with any
other map in a GIS covering the same area. This GIS derived map can then provide
additional information - such as the viability of water power potential as a renewable
energy source. Similarly, GIS can be used compare other renewable energy resources to
find the best geographic potential for a region.
Additionally, from a series of three-dimensional points, or digital elevation model, isopleths
lines representing elevation contours can be generated, along with slope analysis, shaded
relief, and other elevation products. Watersheds can be easily defined for any given reach,
by computing all of the areas contiguous and uphill from any given point of interest.
Similarly, an expected thal weg of where surface water would want to travel in intermittent
and permanent streams can be computed from elevation data in the GIS.
Topological modeling
A GIS can recognize and analyze the spatial relationships that exist within digitally stored
spatial data. These topological relationships allow complex spatial modeling and analysis to
be performed. Topological relationships between geometric entities traditionally include
adjacency (what adjoins what), containment (what encloses what), and proximity (how
close something is to something else).
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Geometric Networks
Geometric networks are linear networks of objects that can be used to represent
interconnected features, and to perform special spatial analysis on them. A geometric
network is composed of edges, which are connected at junction points, similar to graphs in
mathematics and computer science. Just like graphs, networks can have weight and flow
assigned to its edges, which can be used to represent various interconnected features more
accurately. Geometric networks are often used to model road networks and public
utility networks, such as electric, gas, and water networks. Network modeling is also
commonly employed in transportation planning, hydrology modeling,
and infrastructure modeling.
Hydrological modeling
GIS hydrological models can provide a spatial element that other hydrological models lack,
with the analysis of variables such as slope, aspect and watershed or catchment
area. Terrain analysis is fundamental to hydrology, since water always flows down a slope.
As basic terrain analysis of a digital elevation model (DEM) involves calculation of slope
and aspect, DEMs are very useful for hydrological analysis. Slope and aspect can then be
used to determine direction of surface runoff, and hence flow accumulation for the
formation of streams, rivers and lakes. Areas of divergent flow can also give a clear
indication of the boundaries of a catchment. Once a flow direction and accumulation matrix
has been created, queries can be performed that show contributing or dispersal areas at a
certain point. More detail can be added to the model, such as terrain roughness, vegetation
types and soil types, which can influence infiltration and evapotranspiration rates, and
hence influencing surface flow. One of the main uses of hydrological modeling is in
environmental contamination research.
Cartographic modeling
The term "cartographic modeling" was probably coined by Dana Tomlin in his PhD
dissertation and later in his book which has the term in the title. Cartographic modeling
refers to a process where several thematic layers of the same area are produced, processed,
and analyzed. Tomlin used raster layers, but the overlay method (see below) can be used
more generally. Operations on map layers can be combined into algorithms, and eventually
into simulation or optimization models.
Map overlay
The combination of several spatial datasets (points, lines, or polygons) creates a new
output vector dataset, visually similar to stacking several maps of the same region. These
overlays are similar to mathematical Venn diagram overlays. A union overlay combines the
geographic features and attribute tables of both inputs into a single new output.
An intersect overlay defines the area where both inputs overlap and retains a set of
attribute fields for each. A symmetric difference overlay defines an output area that
includes the total area of both inputs except for the overlapping area.
Data extraction is a GIS process similar to vector overlay, though it can be used in either
vector or raster data analysis. Rather than combining the properties and features of both
30

datasets, data extraction involves using a "clip" or "mask" to extract the features of one
data set that fall within the spatial extent of another dataset.
In raster data analysis, the overlay of datasets is accomplished through a process known as
"local operation on multiple rasters" or "map algebra," through a function that combines
the values of each raster's matrix. This function may weigh some inputs more than others
through use of an "index model" that reflects the influence of various factors upon a
geographic phenomenon.
Geostatistics
Geostatistics is a branch of statistics that deals with field data, spatial data with a
continuous index. It provides methods to model spatial correlation, and predict values at
arbitrary locations (interpolation).
When phenomena are measured, the observation methods dictate the accuracy of any
subsequent analysis. Due to the nature of the data (e.g. traffic patterns in an urban
environment; weather patterns over the Pacific Ocean), a constant or dynamic degree of
precision is always lost in the measurement. This loss of precision is determined from the
scale and distribution of the data collection.
To determine the statistical relevance of the analysis, an average is determined so that
points (gradients) outside of any immediate measurement can be included to determine
their predicted behavior. This is due to the limitations of the applied statistic and data
collection methods, and interpolation is required to predict the behavior of particles,
points, and locations that are not directly measurable.
Interpolation is the process by which a surface is created, usually a raster dataset, through
the input of data collected at a number of sample points. There are several forms of
interpolation, each which treats the data differently, depending on the properties of the
data set. In comparing interpolation methods, the first consideration should be whether or
not the source data will change (exact or approximate). Next is whether the method is
subjective, a human interpretation, or objective. Then there is the nature of transitions
between points: are they abrupt or gradual. Finally, there is whether a method is global (it
uses the entire data set to form the model), or local where an algorithm is repeated for a
small section of terrain.
Interpolation is a justified measurement because of a spatial autocorrelation principle that
recognizes that data collected at any position will have a great similarity to, or influence of
those locations within its immediate vicinity.
Digital elevation models, triangulated irregular networks, edge-finding
algorithms, Thiessen polygons, Fourier analysis, (weighted) moving averages, inverse
distance weighting, kriging, spline, and trend surface analysis are all mathematical methods
to produce interpolative data.
Address geocoding
Geocoding is interpolating spatial locations (X,Y coordinates) from street addresses or any
other spatially referenced data such as ZIP Codes , parcel lots and address locations. A
reference theme is required to geocode individual addresses, such as a road centerline file
31

with address ranges. The individual address locations have historically been interpolated,
or estimated, by examining address ranges along a road segment. These are usually
provided in the form of a table or database. The software will then place a dot
approximately where that address belongs along the segment of centerline. For example,
an address point of 500 will be at the midpoint of a line segment that starts with address 1
and ends with address 1,000. Geocoding can also be applied against actual parcel data,
typically from municipal tax maps. In this case, the result of the geocoding will be an
actually positioned space as opposed to an interpolated point. This approach is being
increasingly used to provide more precise location information.
Reverse geocoding
Reverse geocoding is the process of returning an estimated street address number as it
relates to a given coordinate. For example, a user can click on a road centerline theme (thus
providing a coordinate) and have information returned that reflects the estimated house
number. This house number is interpolated from a range assigned to that road segment. If
the user clicks at the midpoint of a segment that starts with address 1 and ends with 100,
the returned value will be somewhere near 50. Note that reverse geocoding does not return
actual addresses, only estimates of what should be there based on the predetermined
range.
Multi-criteria decision analysis
Coupled with GIS, multi-criteria decision analysis methods support decision-makers in
analysing a set of alternative spatial solutions, such as the most likely ecological habitat for
restoration, against multiple criteria, such as vegetation cover or roads. MCDA uses
decision rules to aggregate the criteria, which allows the alternative solutions to be ranked
or prioritized. GIS MCDA may reduce costs and time involved in identifying potential
restoration sites.
Data output and cartography
Cartography is the design and production of maps, or visual representations of spatial data.
The vast majority of modern cartography is done with the help of computers, usually using
GIS but production of quality cartography is also achieved by importing layers into a design
program to refine it. Most GIS software gives the user substantial control over the
appearance of the data.
Cartographic work serves two major functions:
First, it produces graphics on the screen or on paper that convey the results of analysis to
the people who make decisions about resources. Wall maps and other graphics can be
generated, allowing the viewer to visualize and thereby understand the results of analyses
or simulations of potential events. Web Map Servers facilitate distribution of generated
maps through web browsers using various implementations of web-based application
programming interfaces (AJAX, Java, Flash, etc.).
Second, other database information can be generated for further analysis or use. An
example would be a list of all addresses within one mile (1.6 km) of a toxic spill.
32

Graphic display techniques
Traditional maps are abstractions of the real world, a sampling of important elements
portrayed on a sheet of paper with symbols to represent physical objects. People who use
maps must interpret these symbols. Topographic maps show the shape of land surface
with contour lines or with shaded relief.
Today, graphic display techniques such as shading based on altitude in a GIS can make
relationships among map elements visible, heightening one's ability to extract and analyze
information. For example, two types of data were combined in a GIS to produce a
perspective view of a portion of San Mateo County , California.
· The digital elevation model, consisting of surface elevations recorded on a 30-meter
horizontal grid, shows high elevations as white and low elevation as black.
· The accompanying Landsat Thematic Mapper image shows a false-color infrared
image looking down at the same area in 30-meter pixels, or picture elements, for the
same coordinate points, pixel by pixel, as the elevation information.
A GIS was used to register and combine the two images to render the three-dimensional
perspective view looking down the San Andreas Fault, using the Thematic
Mapper image pixels, but shaded using the elevation of the landforms. The GIS display
depends on the viewing point of the observer and time of day of the display, to properly
render the shadows created by the sun's rays at that latitude, longitude, and time of day.
An archeochrome is a new way of displaying spatial data. It is a thematic on a 3D map that
is applied to a specific building or a part of a building. It is suited to the visual display of
heat-loss data.
Spatial ETL
Spatial ETL tools provide the data processing functionality of traditional Extract,
Transform, Load (ETL) software, but with a primary focus on the ability to manage spatial
data. They provide GIS users with the ability to translate data between different standards
and proprietary formats, whilst geometrically transforming the data en route. These tools
can come in the form of add-ins to existing wider-purpose software such asMicrosoft Excel.
GIS data mining
GIS or spatial data mining is the application of data mining methods to spatial data. Data
mining, which is the partially automated search for hidden patterns in large databases,
offers great potential benefits for applied GIS-based decision making. Typical applications
including environmental monitoring. A characteristic of such applications is that spatial
correlation between data measurements require the use of specialized algorithms for more
efficient data analysis.
GIS Developments
Many disciplines can benefit from GIS technology. An active GIS market has resulted in
lower costs and continual improvements in the hardware and software components of GIS.
These developments will, in turn, result in a much wider use of the technology throughout
33

science, government, business, and industry, with applications including real estate, public
health, crime mapping, national defense, sustainable development, natural
resources, landscape architecture, archaeology, regional and community planning,
transportation and logistics. GIS is also diverging into location-based services, which allows
GPS-enabled mobile devices to display their location in relation to fixed assets (nearest
restaurant, gas station, fire hydrant), mobile assets (friends, children, police car) or to relay
their position back to a central server for display or other processing. These services
continue to develop with the increased integration of GPS functionality with increasingly
powerful mobile electronics (cell phones, PDAs, laptops).
Open Geospatial Consortium standards
The Open Geospatial Consortium (OGC) is an international industry consortium of
384 companies, government agencies, universities, and individuals participating in a
consensus process to develop publicly available geoprocessing specifications. Open
interfaces and protocols defined by Open GIS Specifications support interoperable
solutions that "geo-enable" the Web, wireless and location-based services, and
mainstream IT, and empower technology developers to make complex spatial information
and services accessible and useful with all kinds of applications. Open Geospatial
Consortium protocols include Web Map Service, and Web Feature Service.
GIS products are broken down by the OGC into two categories, based on how completely
and accurately the software follows the OGC specifications.
Compliant Products are software products that comply to OGC's Open GIS Specifications.
When a product has been tested and certified as compliant through the OGC Testing
Program, the product is automatically registered as "compliant" on this site.
Implementing Products are software products that implement OpenGIS Specifications but
have not yet passed a compliance test. Compliance tests are not available for all
specifications. Developers can register their products as implementing draft or approved
specifications, though OGC reserves the right to review and verify each entry.
Web mapping
In recent years there has been an explosion of mapping applications on the web such
as Google Maps and Bing Maps. These websites give the public access to huge amounts of
geographic data.
Some of them, like Google Maps and OpenLayers, expose an API that enable users to create
custom applications. These toolkits commonly offer street maps, aerial/satellite imagery,
geo coding, searches, and routing functionality. Web mapping has also uncovered the
potential of crowd sourcing geo data in projects like Open Street Map, which is a
collaborative project to create a free editable map of the world.
Global climate change, climate history program and prediction of its impact
Maps have traditionally been used to explore the Earth and to exploit its resources.
GIS technology, as an expansion of cartographic science, has enhanced the efficiency and
analytic power of traditional mapping. Now, as the scientific community recognizes the
environmental consequences of anthropogenic activities influencing climate change,
34

GIS technology is becoming an essential tool to understand the impacts of this change over
time. GIS enables the combination of various sources of data with existing maps and up-to-date
information from earth observation satellites along with the outputs of climate change
models. This can help in understanding the effects of climate change on complex natural
systems. One of the classic examples of this is the study of Arctic ice melting.
Adding the dimension of time
The condition of the Earth's surface, atmosphere, and subsurface can be examined by
feeding satellite data into a GIS. GIS technology gives researchers the ability to examine the
variations in Earth processes over days, months, and years. As an example, the changes in
vegetation vigor through a growing season can be animated to determine when drought
was most extensive in a particular region. The resulting graphic, known as a normalized
vegetation index, represents a rough measure of plant health. Working with two variables
over time would then allow researchers to detect regional differences in the lag between a
decline in rainfall and its effect on vegetation.
GIS technology and the availability of digital data on regional and global scales enable such
analyses. The satellite sensor output used to generate a vegetation graphic is produced for
example by the Advanced Very High Resolution Radiometer (AVHRR). This sensor system
detects the amounts of energy reflected from the Earth's surface across various bands of
the spectrum for surface areas of about 1 square kilometer. The satellite sensor produces
images of a particular location on the Earth twice a day. AVHRR and more recently
the Moderate-Resolution Imaging Spectroradiometer (MODIS) are only two of many sensor
systems used for Earth surface analysis. More sensors will follow, generating ever greater
amounts of data.
In addition to the integration of time in environmental studies, GIS is also being explored
for its ability to track and model the progress of humans throughout their daily routines. A
concrete example of progress in this area is the recent release of time-specific population
data by the U.S. Census. In this data set, the populations of cities are shown for daytime and
evening hours highlighting the pattern of concentration and dispersion generated by North
American commuting patterns. The manipulation and generation of data required to
produce this data would not have been possible without GIS.
Using models to project the data held by a GIS forward in time have enabled planners to
test policy decisions using spatial decision support systems.
CONCEPTS
MAPS AS A MODEL OF REALITY
The real world is too complex and unmanageable for direct analysis and understanding
because of its countless variability and diversity. It would be an impossible task to describe
and locate each city, building, tree, blade of grass, and grain of sand. How do we reduce the
complexity of the Earth and its inhabitants, so we can portray them in a GIS database and
on a map? We do it by selecting the most relevant features (ignoring those we do not think
are necessary for our specific research or project) and then generalizing the features we
35

have selected. Chapter 6, as well as later portions of this chapter, covers the selection and
generalization process in more detail. For now, let’s focus on features.
FEATURES
As described in Definition #2 (and Figure 1.2), conceptually, there are two parts of a GIS: a
spatial or map component and an attribute or database component. Features have these
two components as well. They are represented spatially on the map and their attributes,
describing the features, are found in a data file. These two parts are linked. In other words,
each map feature is linked to a record in a data file that describes the feature. If you delete
the feature’s attributes in the data file, the feature disappears on the map. Conversely, if
you delete the feature from the map, its attributes will disappear too.
Features are individual objects and events that are located (present, past or future) in
space. In Figure 1.2, a single parcel is an example of a feature. Within the GIS industry,
features have many synonyms including objects, events, activities, forms, observations,
entities, and facilities. Combined with other features of the same type (like all of the
parcels in Figure 1.2), they are arranged in data files often called layers, coverages, or
themes. In this text, we use the terms feature and layer.
In Figure 1.4 below, three features—parcels, buildings, and street centerlines—of a typical
city block are visible. Every feature has a spatial location and a set of attributes. Its spatial
location describes not only its location but its extent. While “location” may be simple to
grasp, it is difficult to locate features accurately and precisely. Accuracy and precision are
examined in Chapter 2, but, in brief, precision deals with the exactness of the
measurement. For example, some input devices, like GPS, have a certain error. They may
be precise within a certain accuracy range if used correctly. Accuracy is the degree of
correspondence between the data and the real world.
Besides location, each feature usually has a set of descriptive attributes, which characterize
the individual feature. Each attribute takes the form of numbers or text (characters), and
these values can be qualitative (i.e. low, medium, or high income) or quantitative (actual
measurements). Sometimes, features may also have a temporal dimension; a period in
which the feature’s spatial or attribute data may change.
As an example of a feature, think of a streetlight. Now imagine a map with the locations of
all the streetlights in your neighborhood. In Figure 1.5, streetlights most are depicted as
small circles. Now think of all of the different characteristics that you could collect relating
to each streetlight. It could be a long list. Streetlight attributes could include height,
material, basement material, presence of a light globe, globe material, color of pole, style,
wattage and lumens of bulb, bulb type, bulb color, date of installation, maintenance report,
and many others. The necessary streetlight attributes depends on how you intend to use
them. For example, if you are solely interested in knowing the location of streetlights for
personal safety reasons, you need to know location, pole heights, and bulb strength. On the
36

other hand, if you are interested in historic preservation, you are concerned with the
streetlight’s location, style, and color.
Now continue thinking about feature attributes, by imagining the trees planted around
your campus or office. What attributes would a gardener want versus a botanist? There
would be differences because they have different needs. You determine your study’s
features and the attributes that define the features.
POINTS, LINES AND POLYGONS
Now think of the feature’s shape on a map. Single or multiple paired coordinates (x, y)
locate individual features in space and define their unique shape. The x and y values of
each coordinate pair are associated with real world coordinate systems, which are
discussed in Chapter 3. For now, let’s focus on the shape of features, which take the
generalized form of points, lines, and polygons
Points
Points are zero dimensional features (meaning that they possess only one x, y coordinate
set) whose location is depicted by a small symbol. What you represent as a point depends
on your study. Examples include streetlights, individual trees, wells, car accidents, crimes,
telephone polls, earthquake epicenters, and even, depending on scale, buildings and cities.
Lines
Lines are formed from a sequence of at least two paired coordinates. The first pair starts
the line and the last ends it. Two coordinate pairs form a straight line. Additional paired
coordinates can form vertices between the starting and ending points that allow the line to
bend and curve. Having length (which can be measured) but no width, a line feature is one-dimensional.
Again, what is represented as a line depends on your study, but street
centerlines, utility lines, canals, railroad tracks, rivers, flight paths, and elevation contour
lines usually form lines.
Polygons
Polygons are features that have boundaries. Formed by a sequence of paired coordinates,
polygons differ from lines in that the starting point is also its ending point. This provides
polygons with both length and width, so these two-dimensional features can calculate the
area contained within the feature. What is represented as a polygon differs from study to
study, but examples include lakes, forest stands, buildings, counties, countries, states, and
census districts.
TOPOLOGY
One of the most important concepts associated with GIS and other geotechnologies is
topology. As features are added to a GIS, they form spatial relationships—called topology
—with each other (both with features within the same layer and with features in different
layers). You might find topology a confusing term partly because it has both spatial and
37

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