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Introduction to and Scope of Remote Sensing

 Remote sensing

Remote sensing

Remote Sensing

The science of remote sensing has emerged as one of the most fascinating subjects over the past three decades. Earth observation from space through various remote sensing instruments has provided a vantage means of monitoring land surface dynamics, natural resources management, and the overall state of the environment itself (Joseph, 2005).

Remote sensing is defined, for our purposes, as the measurement of object properties on the earth’s surface using data acquired from aircraft and satellites. It is, therefore, an attempt to measure something at a distance rather than in situ. While remote-sensing data can consist of discrete point measurement, or a profile along a flight path, we are most interested here in measurements over a two-dimensional spatial grid, i.e., images. Remote sensing systems, particularly those deployed on satellites, provide a repetitive and consistent view of the earth that is invaluable to monitoring the earth system and the effect of human activities on the earth (Schowengerdt, 2006).

Definition of Remote Sensing

Remote means away from or at a distance, while sensing means detecting a property or characteristics. Thus, the term remote sensing refers to the examination, measurement, and analysis of an object without being in contact with it.

Remote sensing is the science and art of acquiring information about the earth's surface without actually being in contact with it. This is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information.

There are many possible definitions of what remote sensing actually is. One of the most accepted definitions of remote sensing is that it is the process of collecting and interpreting information about a target without being in physical contact with the object. Aircraft and satellites are the common platforms for remote sensing observation.

According to the United Nations, "The term remote sensing means the sensing of the Earth's surface from space by making use of the properties of the electromagnetic wave emitted, reflected or diffracted by the sensed objects, for the purpose of improving natural resource management, land use and the protection of the environment."

Components of Remote Sensing

In much of remote sensing, the process involves an interaction between incident radiation and the targets of interest. This is exemplified by the use of imaging systems where the following seven elements are involved:

  1. Energy Source or Illumination (A): The first requirement for remote sensing is to have an energy source which illuminates or provides electromagnetic energy to the target of interest.
  2. Radiation and the Atmosphere (B): As the energy travels from its source to the Target, it will come in contact with and interact with the atmosphere it passes through. This interaction may take place a second time as the energy travels from the target to the sensor.
  3. Interaction With the Target (C): Once the energy makes its way to the target through the atmosphere, it interacts with the target depending on the properties of both the target and the radiation
  4. Recording of Energy by the Sensor (D): After the energy has been scattered by or emitted from the target, we require a sensor (remote, not in contact with the target) to collect and record the electromagnetic radiation.
  5. Transmission, Reception, and Processing (E): The energy recorded by the sensor has to be transmitted, often in electronic form, to a receiving and processing station where the data are processed into an image (hardcopy and/or digital).
  6. Interpretation and Analysis (F): The processed image is interpreted, visually and/or digitally or electronically, to extract information about the target which was illuminated.
  7. Application (G): The final element of the remote sensing process is achieved when we apply the information we have been able to extract from the imagery about the target in order to better understand it, reveal some new information, or assist in solving a particular problem.

Principles of Remote Sensing

Remote sensing has been defined in many ways. It can be thought of as including traditional aerial photography, geophysical measurements such as surveys of the earth’s gravity and magnetic fields and even seismic sonar surveys. However, in a modern context, the term remote sensing usually implies digital measurements of electromagnetic energy, often for wavelengths that are not visible to the human eye.

The basic principles of remote sensing are listed below:

  1. Electromagnetic energy has been classified by wavelength and arranged to form the electromagnetic spectrum.
  2. As electromagnetic energy interacts with the atmosphere and the surface of the Earth, the most important concept to remember is the conservation of energy (i.e., the total energy is constant).
  3. As electromagnetic waves travel, they encounter objects (discontinuities in velocity) that reflect some energy like a mirror and transmit some energy after changing the travel path.
  4. The distance (d) an electromagnetic wave travels in a certain time (t) depends on the velocity of the material (v) through which the wave is traveling; d = vt.
  5. The velocity (c), frequency (f), and wavelength (l) of an electromagnetic wave are related by the equation: c = fl.
  6. The analogy of a rock dropped into a pond can be drawn as an example to define wavefront.
  7. It is quite appropriate to look at the amplitude of an electromagnetic wave and think of it as a measure of the energy in that wave.
  8. Electromagnetic waves lose energy (amplitude) as they travel because of several phenomena.

Remote Sensing System

With the general background treatise on remote sensing we have made so far, it would now be easier to analyze the different stages in remote sensing. They are:

  1. Origin of electromagnetic energy (sun, a transmitter carried by the sensor).
  2. Transmission of energy from the source to the surface of the earth and its interaction with the intervening atmosphere.
  3. Interaction of energy with the earth’s surface (reflection/absorption/transmission) or self-emission.
  4. Transmission of the reflected/emitted energy to the remote sensor placed on a suitable platform, through the intervening atmosphere.
  5. Detection of the energy by the sensor, converting it into a photographic image or electrical output.
  6. Transmission/recording of the sensor output.
  7. Pre-processing of the data and generation of the data products.
  8. Collection of ground truth and other collateral information.
  9. Data analysis and interpretation.
  10. Integration of interpreted images with other data towards deriving management strategies for various themes or other applications.

Applications of Remote Sensing

Some of the important applications of remote sensing technology are:

  1. Environmental assessment and monitoring (urban growth, hazardous waste).
  2. Global change detection and monitoring (atmospheric ozone depletion, deforestation, global warming).
  3. Agriculture (crop condition, yield prediction, soil erosion).
  4. Nonrenewable resource exploration (minerals, oil, natural gas).
  5. Renewable natural resources (wetlands, soils, forests, oceans).
  6. Meteorology (atmosphere dynamics, weather prediction).
  7. Mapping (topography, land use. Civil engineering).
  8. Military surveillance and reconnaissance (strategic policy, tactical assessment).
  9. News media (illustrations, analysis).

To meet the needs of different data users, there are many remote sensing systems, offering a wide range of spatial, spectral and temporal parameters. Some users may require frequent, repetitive coverage with relatively low spatial resolution (meteorology).

Others may desire the highest possible spatial resolution with repeat coverage only infrequently (mapping), while some users need both high spatial resolution and frequent coverage, plus rapid image delivery (military surveillance). Remote sensing data can be used to initialize and validate large computer models, such as Global Climate Models (GCMs), that attempt to simulate and predict the earth's environment.

Remote Sensors

The instruments used to measure the electromagnetic radiation reflected/emitted by the target under study are usually referred to as remote sensors. There are two classes of remote sensor: passive and active.

  • Passive remote sensor: Sensors which sense natural radiations, either emitted or reflected from the earth, are called passive sensors – the sun as a source of energy or radiation. The sun provides a very convenient source of energy for remote sensing. The sun's energy is either reflected, as it is for visible wavelengths, or absorbed and then reemitted, as it is for thermal infrared wavelengths. Remote sensing systems which measure the energy that is naturally available are called passive sensors. Passive sensors can only be used to detect energy when the naturally occurring energy is available. For all reflected energy, this can only take place during the time when the sun is illuminating the Earth. There is no reflected energy available from the sun at night. The energy that is naturally emitted (such as thermal infrared) can be detected day or night, as long as the amount of energy is large enough to be recorded.
  • Active remote sensor: Sensors which carry electromagnetic radiation of a specific wavelength or band of wavelengths to illuminate the earth’s surface are called active sensors. Active sensors provide their own energy source for illumination. The sensor emits radiation which is directed toward the target to be investigated. The radiation reflected from that target is detected and measured by the sensor. Advantages of active sensors include the ability to obtain measurements anytime, regardless of the time of day or season. Active sensors can be used for examining wavelengths that are not sufficiently provided by the sun, such as microwaves, or to better control the way a target is illuminated. However, active systems require the generation of a fairly large amount of energy to adequately illuminate targets. Some examples of active sensors are a laser fluorosensor and a synthetic aperture radar (SAR).

Parameters of a Sensing System

The major parameters of a sensing system which can be considered as indicators of the quality of data and which have bearing on optimum utilization for specific end-use include:

  1. Spatial resolution: the capability of the sensor to discriminate the smallest object on the ground of different sizes; usually specified in terms of linear dimension. As a general rule, the higher the resolution, the smaller the object that can be identified.
  2. Spectral resolution: the spectral bandwidth with which the data is collected.
  3. Radiometric resolution: the capability of the sensor to discriminate two targets based on its reflectance/emittance difference; it is measured in terms of the smallest reflectance/emittance that can be detected. The higher the radiometric resolution, the smaller the radiance differences that can be detected between two targets.
  4. Temporal resolution: the capability to view the same target, under similar conditions, at regular intervals.

Spectral Bands and Structure

The most important criterion for the location of spectral bands is that they should be in the atmospheric window and away from the absorption bands of atmospheric constituents. Field studies have shown that certain spectral bands are best suited for specific themes. The thematic mapper bands are selected based on such investigations.

Electromagnetic spectrum: The electromagnetic spectrum ranges from the shorter wavelengths (including gamma and x-rays) to the longer wavelengths (including microwaves and broadcast radio waves). There are several regions of the electromagnetic spectrum which are useful for remote sensing. For most purposes, the ultraviolet or UV portion of the spectrum has the shortest wavelengths which are practical for remote sensing. This radiation is just beyond the violet portion of the visible wavelengths, hence its name. Some of Earth's surface materials, primarily rocks and minerals, fluoresce or emit visible light when illuminated by UV radiation.

The light which our eyes – our "remote sensors" – can detect is part of the visible spectrum. It is important to recognize how small the visible portion is relative to the rest of the spectrum. There is a lot of radiation around us which is "invisible" to our eyes but can be detected by other remote sensing instruments and used to our advantage. The visible wavelengths cover a range from approximately 0.4 to 0.7 μm. The longest visible wavelength is red, and the shortest is violet. Common wavelengths of what we perceive as particular colors from the visible portion of the spectrum are listed below. It is important to note that this is the only portion of the spectrum we can associate with the concept of colors.

  1. Violet: 0.4–0.446 μm
  2. Blue: 0.446–0.500 μm
  3. Green: 0.500–0.578 μm
  4. Yellow: 0.578–0.592 μm
  5. Orange: 0.592–0.620 μm
  6. Red: 0.620–0.7 μm

The portion of the spectrum of more recent interest to remote sensing is the microwave region from about 1 mm to 1 m. This covers the longest wavelengths used for remote sensing. The shorter wavelengths have properties similar to the thermal infrared region, while the longer wavelengths approach the wavelengths used for radio broadcasts.

Advantages of Remote Sensing

The basic advantages of remote sensing are listed below:

  1. A relatively cheap and rapid method of acquiring up-to-date information over a large geographical area.
  2. It is the only practical way to obtain data from inaccessible regions, e.g., Antarctica, Amazonia.
  3. At small scales, regional phenomena which are invisible from the ground are clearly visible (e.g., beyond man's visibility); for example, faults and other geological structures.
  4. Cheap and rapid method of constructing base maps in the absence of detailed land surveys.
  5. Easy to manipulate with the computer and combine with other geographic coverage’s in the GIS.

Disadvantages of Remote Sensing

The basic disadvantages of remote sensing are given below:

  1. They are not direct samples of the phenomenon, so they must be calibrated against reality. This calibration is never exact; a classification error of 10% is excellent.
  2. They must be corrected geometrically and georeferenced in order to be useful as maps, not only as pictures.
  3. Distinct phenomena can be confused if they look the same to the sensor, leading to classification error – for example, artificial and natural grass in green light.
  4. Phenomena which were not meant to be measured can interfere with the image and must be accounted for.
  5. Resolution of satellite imagery is too coarse for detailed mapping and for distinguishing small contrasting areas.


Remote sensing is the gathering of information concerning the earth’s surface that does not involve contact with the surface or object under study. The techniques include aerial photography, multi-spectral, and infrared imagery, and radar. With the help of remote sensing, we can able to get accurate information about the earth’s surface including its components like forests, landscapes, water resources, oceans, etc. This information helps the researchers to their research activities about the earth’s components concerning its sustainable management and conservation and so on.

In order for a sensor to collect and record energy reflected or emitted from a target or surface, it must reside on a stable platform removed from the target or surface being observed. Platforms for remote sensors may be situated on the ground, on an aircraft or balloon (or some other platform within the Earth's atmosphere), or on a spacecraft or satellite outside of the Earth's atmosphere. Ground-based sensors are often used to record detailed information about the surface which is compared with information collected from aircraft or satellite sensors. In some cases, this can be used to better characterize the target which is being imaged by these other sensors, making it possible to better understand the information in the imagery.


1. Fundamentals of Remote Sensing- A CanadaCenter for Remote Sensing Tutorial, (Prentice-Hall, New Jersey).

2. Schowengerdt, R.A.2006, Remote Sensing Models and Methods for image processing, 2nd edition, Elsevier publication.

3. Joseph, G.2005, Fundamentals of Remote Sensing, 2nd edition, Universities Press (India) Private Ltd.

4. Jensen, J.R.2000, Remote Sensing of the environment, 3rdedition, Pearson Education (Singapore) Pte.Ltd.

© 2010 Rashel Nirjhon


Blessing Archibong on March 30, 2019:

Found this piece of material very educative. Thanks. More please

SRadwan on January 06, 2019:

very good thank

Prince on November 24, 2018:

I cannot understand the scope of remote sensing

Manvendra on October 01, 2018:

Uses of remote sensing

Harjot singj on June 09, 2018:

Thanks a lot of good intro thnks

Oliviya Joshy on March 11, 2017:

Good & simplified manner of explanation.It will help the newcomers a lot

puja mahato on December 11, 2015:

Thanks and good Intro

tapan ghosh on September 21, 2015:

Introduction is so good.but I cannot understand the scope of remote sensing. So briefly discussed about it.and please send stages and platforms of R.S.

gauri patil on July 28, 2015:

Good article & easy language,memorable artlcle

paschal sulumo on June 18, 2015:

highly appreciated thanks

paschal bazil on October 07, 2014:

Thanks a lot for good introduction of the topic. I like it.

alphonce olielo on April 08, 2014:

it's of desired pleasure to give thanks to this good work having been of greatest help to me bravo

Dolly mishra on April 01, 2014:

Good intro

Rashel Nirjhon (author) from Tangail on January 27, 2014:

welcome robi

Rashel Nirjhon (author) from Tangail on January 27, 2014:

welcome, Ashwini

ROBY on October 24, 2013:


Ashwini on September 05, 2013:

This are my seminar topic so Thank you provid the detail & eazy languege on July 03, 2013:

A good intro.,am like it! on May 15, 2013:

I'm too much fascinated.

Suhail qadir on May 08, 2013:

Excellent i m satisfied

selvakumar on February 16, 2013:

thank you we satisfied with your description and we wish to know more about our future job details about this course

Akho on December 26, 2012:

it was really a worth reading concept. thank u

FRENK JOSEPHATH on November 13, 2012:

Thanks for good description of the concept of remote sensing

RAM ANNA UNIVERSITY on October 31, 2012:


ramkumar on October 30, 2012:

thank you

jahidul islam jahid on April 24, 2012:

good one, am like it!

jahidul islam jahid on April 24, 2012:

good one, am like it!

Vipin yadav on March 26, 2012:

Great work

Godwin Enangson on March 13, 2012:

Great Work! A good intro.

G S Gundu Rao on September 19, 2010:

This is an excellent introduction to the subject of remote sensing. Congrats