Geography has always
been important to humans. Stone-age hunters anticipated the location of their
quarry, early explorers lived or died by their knowledge of geography and
current societies live and work based on their understanding of who belongs
where. Applied geography, in the form of maps and spatial information, has
served discovery, planning, cooperation, and conflict for at least the past
3000 years and maps are among the most beautiful documents of our civilization. Most often our geographic knowledge is
applied to routine tasks, such as when we puzzle over a route through a maze of
city streets or search for the nearest gas station. Spatial information has a
much greater impact on our lives, often to an extent we don’t realize, to help
us produce the food we eat, the energy we burn, the clothes we wear, and the
diversions we enjoy.
Because
spatial information is so important, we have developed tools called geographic
information systems (GIS) to help us with our geographic knowledge. A GIS helps
us gather and use spatial data Some GIS components are purely technological;
they include space-age data collectors, advanced communications networks, and
sophisticated computing. Other GIS methods are very simple; for example, when a
pencil and paper are used to field verify a map.
As
with many aspects of life in the last five decades, how we gather and use
spatial data has been profoundly altered by modern electronics, and GIS
software and hardware are a primary result of these technological developments.
The capture and treatment of spatial data has quickened over the past three
decades, and continues to evolve.
Key
to all definitions of a GIS are “what” and “where”. GIS and spatial analyses
are concerned with the absolute and relative location of features, as well as
the properties and attributes of those features. The locations of important
spatial objects such as rivers and streams may be recorded, and also their
size, flow rate, water quality, or the kind of fish found in them. Indeed,
these attributes often depend on the spatial arrangement of “important”
features. A GIS aids in the analysis and display of these spatial relationships
Relation with information technology
Geoinformatics sometimes related to as
geographic information system/s. basically is the combination of two sciences
the geography “ Geography (from Greek γεωγραφία – geographia,
lit. “earth describe-write”) is the science that studies the lands,
features, inhabitants, and phenomena of Earth A literal translation would be
“to describe or write about the Earth”. The first person to use the
word “geography” was Eratosthenes (276-194 BC). Four historical
traditions in geographical research are the spatial analysis of natural and
human phenomena (geography as a study of distribution), area studies (places
and regions), study of man-land relationship, and research in earth sciences.
Nonetheless, modern geography is an all-encompassing discipline that foremost
seeks to understand the Earth and all of its human and natural complexities—not
merely where objects are, but how they have changed and come to be. Geography
has been called “the world discipline” and “the bridge between
the human and the physical science”. Geography is divided into two main
branches: human geography and physical geography”, and information technology
“Information technology (IT) is the acquisition, processing, storage and
dissemination of vocal, pictorial, textual and numerical information by a
microelectronics-based combination of computing and telecommunications. The
term in its modern sense first appeared in a 1958 article published in the
Harvard Business Review, in which authors Leavitt and Whisler commented that
“the new technology does not yet have a single established name. We shall
call it information technology (IT). Some of the modern and emerging fields of
Information technology are next generation web technologies, bioinformatics,
Geoinformatics, cloud computing, global information systems,
large scale knowledgebase, etc.”
IT
is the area of managing technology and spans wide variety of areas that include
but are not limited to things such as processes, computer software, information
systems, computer hardware, programming languages, and data constructs. In
short, anything that renders data, information or perceived knowledge in any
visual format whatsoever, via any multimedia distribution mechanism, is
considered part of the IT domain. IT provides businesses with four sets of core
services to help execute the business strategy: business process automation, providing
information, connecting with customers, and productivity tools. Based on a global inventory of the world’s IT capacity,
Hilbert and Lopez identify the exponential pace of technological change (a kind
of Moore’s law): machines’ application-specific capacity to compute information
per capita has roughly doubled every 14 months between 1986-2007; the per
capita capacity of the world’s general-purpose computers has doubled every 18
months during the same two decades; the global telecommunication capacity per
capita doubled every 34 months; the world’s storage capacity per capita
required roughly 40 months to double (every 3 years); and per capita broadcast
information has doubled roughly every 12.3 years.
Trends
in increasing Geoinformatics
Actually
Geography is an Information technology now a day and is growing enormously
around the world geographic information technology is a trillion dollar company
these days and is growing at the rate of 15% per year. Recent trend in the
growth of hardware and continuous decline in their cost has helped a lot both
in the growth of technology and Geoinformatics. Geoinformatics is wholly
dependent on Computers without the technological features available these days
one cannot think of Geoinformatics. The Development of Geoinformatics has been
driven at least in part by technology, particularly the specific technology to
support spatial and graphic data applications in computing. the use of advanced
DBMS have revolutionized the applications of Geoinformatics and the available
analysis are growing widely relation DBMS object oriented data basses high
level DBMS systems MS access SQL etc. are very useful in handling the
geographic as well as non-spatial data . Technology is evolving as from the
simple analytical engine to modern real time systems the technology in both
data storage and retrieval is increasing day by now we have terra best of Hard
discs some 60 Gb of Rams some 8-10 Gb of display adapters and recent Led display
devices are best displaying of geographic data. From the 8-bit computers we
have 64-bit + computers and having the speed in gaga hertz. Internet technology
also helped the GIS largely almost all the information is available on the
internet all the maps and other research projects are available on internet
also Open source software are supporting a lot in the spread of Geoinformatics
. Modern computers based on integrated circuits are millions
to billions of times more capable than the early machines, and occupy a
fraction of the space.Simple computers are small enough to fit into mobile
devices, and mobile computers can be powered by small batteries. Personal
computers in their various forms are icons of the Information Age and are what
most people think of as “computers”. However, the embedded computers
found in many devices from mp3 players to fighter aircraft and from toys to
industrial robots are the most numerous. Now we have the Graphic User Interface
Operating systems. The high standard peripheral devices and large storage
devices and also the advanced software Decision support systems also the WEBGIS
is emerging very rapidly. With the IT we have multitasking, Multiprocessing
Multi-User Computers which are the back bone of GIS. Strictly speaking if there
is no information Technology there would have been no GIS .
Geoinformatics
is a late bloomer among applications of computing technology in parts because
it is so demanding, and simply could not be supported in any useful fashion by
the resources available in the typical computer system of, say 1960. In
addition, the spatial nature of geographic data is not easily accommodated
within the essentially linear structure of conventional computers, and early
input and output devices lacked the spatial resolution to deal these kinds of
data. Indeed, it is often noted that the human eye and mind are still superior
to the best digital technology in such spatial tasks as pattern recognition.
The Geoinformatics development can be directly linked to the general advances
in hardware and software although other factors like education and awareness
and the action of key individuals have also been important.
The main power of Geoinformatics is the
linkage between geographic data and the information about it. GIS not only show
the feature but what exactly the feature is. This is only possible with the
help of data base management system which actually are the software and the
advancement in these systems has led to the easy collection and relation and
also supports the linkage between locational data and the attribute data. DBMs were
used for computing in late 1970 and were implemented in GIS in 1980s.
SENSOR technology and Geoinformatics
Without sensors most electronic applications would not exist
they perform a vital function, namely providing an interface to the real world.
The importance of sensors, however, contrasts with the limited information
available on them. Today’s smart sensors, wireless sensors, and
microtechnologies are revolutionizing sensor design and applications
A sensor is a device that measures a
physical quantity and converts it into a signal which can be read by an
observer or by an instrument. For example, a mercury-in-glass thermometer
converts the measured temperature into expansion and contraction of a liquid
which can be read on a calibrated glass tube. A thermocouple converts
temperature to an output voltage which can be read by a voltmeter. For
accuracy, most sensors are calibrated against known standards. Sensors are used
in everyday objects such as touch-sensitive elevator buttons (tactile sensor)
and lamps which dim or brighten by touching the base. There are also
innumerable applications for sensors of which most people are never aware.
Applications include cars, machines, aerospace, medicine, manufacturing and
robotics. A sensor is a device which receives and responds to a signal. A
sensor’s sensitivity indicates how much the sensor’s output changes when the
measured quantity changes. For instance, if the mercury in a thermometer moves
1 cm when the temperature changes by 1 °C, the sensitivity is 1 cm/°C (it is
basically the slope Dy/Dx assuming a linear characteristic). Sensors that
measure very small changes must have very high sensitivities. Sensors also have
an impact on what they measure; for instance, a room temperature thermometer
inserted into a hot cup of liquid cools the liquid while the liquid heats the
thermometer. Sensors need to be designed to have a small effect on what is
measured; making the sensor smaller often improves this and may introduce other
advantages. Technological progress allows more and more sensors to be
manufactured on a microscopic scale as microsensors using MEMS technology. In
most cases, a microsensor reaches a significantly higher speed and sensitivity
compared with macroscopic approaches.
Ideal sensors are designed to be linear or
linear to some simple mathematical function of the measurement, typically
logarithmic. The output signal of such a sensor is linearly proportional to the
value or simple function of the measured property. The sensitivity is then
defined as the ratio between output signal and measured property. For example,
if a sensor measures temperature and has a voltage output, the sensitivity is a
constant with the unit [V/K]; this sensor is linear because the ratio is
constant at all points of measurement. Actually the GIS uses the sensor to
Acquire the information and on this information the whole system is dependent
Sensor deviations
If the sensor is not ideal, several
types of deviations can be observed:
- Ø The sensitivity may in practice differ from the value
specified. This is called a sensitivity error, but the sensor is still linear. - Ø Since the range of the output signal is always limited, the
output signal will eventually reach a minimum or maximum when the measured
property exceeds the limits. The full scale range defines the maximum and
minimum values of the measured property. - Ø If the output signal is not zero when the measured property
is zero, the sensor has an offset or bias. This is defined as the output of the
sensor at zero input. - Ø If the sensitivity is not constant over the range of the
sensor, this is called nonlinearity. Usually this is defined by the amount the
output differs from ideal behavior over the full range of the sensor, often
noted as a percentage of the full range. - Ø If the deviation is caused by a rapid change of the measured
property over time, there is a dynamic error. Often, this behaviour is
described with a bode plot showing sensitivity error and phase shift as
function of the frequency of a periodic input signal. - Ø If the output signal slowly changes independent of the
measured property, this is defined as drift (telecommunication). - Ø Long term drift usually indicates a slow degradation of
sensor properties over a long period of time. Noise is a random deviation of
the signal that varies in time. - Hysteresis is an
error caused by when the measured property reverses direction, but there is
some finite lag in time for the sensor to respond, creating a different offset
error in one direction than in the other. - Ø If the sensor has a digital output, the output is
essentially an approximation of the measured property. The approximation error
is also called digitization error. - Ø If the signal is monitored digitally, limitation of the
sampling frequency also can cause a dynamic error, or if the variable or added
noise noise changes periodically at a frequency near a multiple of the sampling
rate may induce aliasing errors.
The sensor may to some extent be sensitive to
properties other than the property being measured. For example, most sensors
are influenced by the temperature of their environment.
All these deviations can be classified
as systematic errors or random errors. Systematic errors can sometimes be
compensated for by means of some kind of calibration strategy. Noise is a
random error that can be reduced by signal processing, such as filtering,
usually at the expense of the dynamic behavior of the sensor. The more the
sensor is error free the more information will be accurate and the more
analysis will be really developed. Actually the GIS displays the real world in
a model recorded by the sensors of various types the range on EMR to which the
sensor is sensitive depends upon the technology used in that sensor. Recent
sensors are sensitive to hundreds of wavelengths Hyper spectral sensors
Resolution
The resolution of a sensor is the smallest change it can
detect in the quantity that it is measuring. Often in a digital display, the
least significant digit will fluctuate, indicating that changes of that
magnitude are only just resolved. The resolution is related to the precision
with which the measurement is made. For example, a scanning tunneling probe (a
fine tip near a surface collects an electron tunneling current) can resolve
atoms and molecules. The more the sensor resolution the more accurate the data
will be and the technology has grown when we have the spatial resolution of .5
m which helps to detect a small change/feature
Types
All living organisms contain biological
sensors with functions similar to those of the mechanical devices described.
Most of these are specialized cells that are sensitive to:
Light, motion, temperature, magnetic fields,
gravity, humidity, vibration, pressure, electrical fields, sound, and other
physical aspects of the external environment
Physical aspects of the internal environment,
such as stretch, motion of the organism, and position of appendages
(proprioception)
Environmental molecules, including toxins,
nutrients, and pheromones
Estimation of biomolecules interaction and
some kinetics parameters
Internal metabolic milieu, such as glucose
level, oxygen level, or osmolality
Internal signal molecules, such as hormones,
neurotransmitters, and cytokines
Differences between proteins of the organism
itself and of the environment or alien creatures.
Most remote sensing instruments (sensors) are designed to
measure photons. The fundamental principle underlying sensor operation centers
on what happens in a critical component – the detector. This is the concept of
the photoelectric effect (for which Albert Einstein, who first explained
it in detail, won his Nobel Prize [not for Relativity which was a much
greater achievement]; his discovery was, however, a key step in the
development of quantum physics). This, simply stated, says that there will be
an emission of negative particles (electrons) when a negatively charged plate
of some appropriate light-sensitive material is subjected to a beam of photons.
The electrons can then be made to flow as a current from the plate, are
collected, and then counted as a signal. A key point: The magnitude of the
electric current produced (number of photoelectrons per unit time) is directly
proportional to the light intensity. Thus, changes in the electric current can
be used to measure changes in the photons (numbers; intensity) that strike the
plate (detector) during a given time interval. The kinetic energy of the
released photoelectrons varies with frequency (or wavelength) of the impinging
radiation. But, different materials undergo photoelectric effect release of
electrons over different wavelength intervals; each has a threshold wavelength
at which the phenomenon begins and a longer wavelength at which it ceases. The
first is a functional treatment of several classes of sensors, plotted as a
triangle diagram, in which the corner members are determined by the principal
parameter measured: Spectral; Spatial; Intensity.
The growth in technology has been started for early human
age and is increasing day by day .In early days the images which were available
for GIS were only panchromatic (black/white) and the analysis were not so good
enough now we have the sensor sensitive to almost every band in EMR and the
data is available in lots of colours and shades by thermal sensor the image s
are taken day and night also the active sensors are employed now a days we have
the real time access to the features changing on the earth. The Hyper spectral
images give large information about the feature and the microwave sensor can sense
through the clouds even in rain and is sensitive to the geometric features as
well. As in the advancement in sensor
technology the applications of Geoinformatics are increased.
Summary
From the technological perspective, the
development of GIS is heavily dependent on the general trends of the hardware
and software evolution in the computer industry. In recent years, growing
awareness of the importance of Geoinformatics in cooperate information resource
management has attracted many main stream companies to GIS arena. There is a
particularly strong interest among database software vendors to include spatial
data-handling capabilities within the conventional database environments. Big
information technology companies such as Oracle, Hewlett Packard .IBM and
Microsoft have now all had a presence in the GIS marketplace. This has led to
several breakthroughs in database technology that make the integration of
spatial and descriptive data a reality. However,
it has also created a substantial amount of hype and confusion among the
ordinary users. For example, the entry of large technology companies into the
GIS marketplace has engendered many take overs, mergers , partnerships and
joint development pacys among them and conventional GIS vendors. It has also given to rise to
intense marketing efforts with claims and counter claims about the capabilities
of products and the future directions of technology. Users are sometimes
overwhelmed with excessive information when trying to configure their system
for implementation projects.
References
- Ø Geographic Information System By
Michael F. Goodchild University of California Santa Barbara - Ø Concept and Techniques of GIS by C. P.
Lo Albert K. W. Yeung - Ø Fundamentals of GIS by Michael N.
DeMers. - Ø GIS Tools Prakash T.N
- Ø Sensor Technology Hand Book by John S.
Wilson - Ø WEB
- Wikipedia
- Nasa Website
- Usgs
- Nmsu.edu
