Remote Sensing

Subject: Technology
Type: Exploratory Essay
Pages: 11
Word count: 2818
Topics: Engineering, Agriculture, Geography, Space Exploration

Remote sensing has a wide scope of application from the field of Agriculture, geography, land survey, glaciology to oceanography. Remote sensing is also applicable in planning, commerce and in national security. Remote sensing is the procedure of detecting and observing the physical properties of a geographical locality by measuring the reflected radiation that of the area at a distance from the place itself. This is contrary to normal on-site observation where the observer is stationed at the actual area being measured or monitored. In several instances, remote sensing deals with either active or passive study of a wide scope of electromagnetic spectrum during the process of emission, reflecting or scatter from the locality being studied. The other examples of waves that are also propagated and may be used in the study are sound waves. The ability of remote sensing to be conducted from far away locations from the actual phenomenon being studied allows for its wide scope of application. In the field of the environment, for example, it is applied in the quest to understand the changes that occur to the ecosystem whether human-made changes or naturally occurring ones. In such a field, for example, it can be applied land conservation where it can be used to watch out for deforestation and general land usage. This paper explores remote sensing and seeks to understand the process, its applications, its methodologies of operations and the challenges and strides that have been made in the field so far.

History of Remote Sensing

Through Research and inventions, human beings have made several strides in the field of Remote Sensing. Remote Sensing, however, dates back to the 1840s. The art began back then when balloonists captured images of the ground using a then-new invented photo-camera. Balloonist G. Tournachon was among the pioneers of the art as he took images of Paris from his balloon back in 1858 (Lillesand, Ralph and Jonathan 34). This followed several other developments in the field with kites, messenger pigeons, and rockets being used to take images. The practice, however, thrived most with the development and advancement of the flight industry. Aerial Photography came to play an important part in the First World War with the and later mushroomed fully during the Second World War. During this first century after the invention of Remote Sensing, the art focus primary on-camera photography as the tool for its functionality. The pioneer resemblance of modern Remote Sensing begun in the 1950s with improved availability of satellite platforms, electro-optical sensor systems and elaborate tools of analysis that are usable in measuring and breaking down of the images captured. 1959 was the year when images of the earth were captured from without the orbital space. 

By the year 1960, Television Infrared Observation Satellite was installed in space and used to monitor weather conditions and patterns of the earth (Atzberger 64). The Cold War acted as a motivating factor for speedy inventions and development in the art of Remote Sensing as nations participating in the war strived to take good and detailed images of their rivals to facilitate strategic planning. The 1970’s saw further advancements in the field with the launch of the pioneering Landsat multispectral scanner system that took satellite images of the earth. Through research and trials, several developments and advancements have been made in the field of Remote Sensing with organizations such as National Aeronautics and Space Administration (NASA) and U.S Geological Survey rising to further and guide the activities and development in the field.

Remote Sensing and Electromagnetic Spectral Range

Remote sensing is guided or dependant on the relationship of the phenomenon being measured and energy. This observed energy is the radiation that is available in the electromagnetic spectrum. Electromagnetic Radiation is the waves of energy that moves at the speed of light and whose spectrum is subdivided by wavelengths. The Spectrum that is visible to the human eye, for example, possesses wavelengths between 380 nanometers and 760 nanometers (Metz, Duccio and Markus 111). Other spectra such as Radio waves are however much larger in their wavelengths. It is this electromagnetic radiation that remote sensing equipment measures and analyzes to determine the particular phenomenon in the study. Depending on the wavelength areas under detection, remote sensing can be classified as either visible and reflective infrared, thermal infrared or microwave.

Visible and reflective infrared uses the sun as the source of energy hence is most useful in the study of materials on the earth surface. Since they do not emit radiations of their own, they are classified as a type of passive remote sensing. The wavelength range for visible infrared is 0.4 to 0.3 micrometers. Thermal infrared also know as long-wave remote sensing take measurements of the energy radiated through wavelengths of 5 and 10 micrometers. An example of this type of remote sensing is the infrared cameras used in national security. This type of sensing is not dependant on light and can be used even in the night. Microwave remote sensing, on the other hand, encompasses lager wavelengths that usually range between 1 mm and 30 centimeters. Microwave remote sensing uses both passive and active remote sensing systems.

Passive Remote Sensing

Remote sensing can be either passive or active. In passive remote sensing, the emitted or reflected radiation from the phenomenon in the study is detected and analyzed; the sensing system, however, does not emit any radiation itself. Passive remote sensing may involve visible and reflective infrared, thermal infrared and even some cases of microwave remote sensing. Sources of ration here can be solar or energy from the atmosphere, clouds, or ground.

Techniques and sensor types that can be categorized as passive remote sensing include but are not limited to digital and film photography, hyper-spectral imaging equipment, multispectral scanners, seismometers, photometers, and radiometers. When a film is used for remote sensing, it is mostly used as black and white and in aerial view. Film photography peeked as a technique of remote sensing after the First World War with the advancements in aircraft technology. By the time the Second World War was coming to an end, color photography was a normal practice in the field of remote sensing. Color photography is more expensive than panchromatic photography, but infrared photography is even more expensive. The advantage of Infrared photography, however, is that it shows the differences between healthy and unhealthy vegetation and water and land. Multilateral imaging can take several discrete spectral bands whereas hyper spectral technique works on almost the same basics but huge spectral ranges continuously. Radiometers take measurements of radiant flux, the collective power of a radiation of electromagnetic nature emitted by or landing on an object of study, while photometers deal with measurements of the luminous flux, the visible power of light from the object of study. Passive remote sensing also involves the use of sound waves to detect and study objects, passive sonar, and seismography which involves the use of seismic waves to decipher information on volcanic eruptions and such ground movements.

Active Remote Sensing

Active remote sensing systems and techniques involve the creation and propagation of artificial radiations on the object or phenomenon under study. The remote sensing systems create a fabricated radiation that is directed or emitted in the area or aspect that is under study. The most common forms that employ active remote sensing include Radio Detection Range (Radar) and Light Detection Range (LIDAR). Active Sonar is another example of active remote sensing, but it uses sound waves in the place of electromagnetic radiations. Radar employs the microwaves or radio waves of determining information about an object and using the techniques. It is possible to determine the speed, location and even direction of the object. Either the antenna or the dish transfers pulses of the radio waves or the microwaves to the object that reflects the waves back to the antenna or dish. The reflected wave is then studied and broken down so to determine the location, speed, and direction of the object. These waves function best with extremely conductive objects like metals.

Radar techniques of remote sensing are applicable in areas such as air traffic control, in the field of security to manufacturing missile detection systems and in monitoring weather conditions and patterns. Nevertheless, radar techniques have their share of shortcomings. These disadvantages include interference from other objects, jamming of signals, signal noise and potential bending of the emitted waves due to varying atmosphere influence. An example of radar used in real life includes the Doppler radar that is used by the police to detect speeding motorist due to its focus on the velocity of objects (Ulalby et al. 61). Another example is the Synthetic Aperture Radar (SAR) that releases radiation from a source in motion hence permitting the creation of high-quality images. SAR is mostly employed in environmental monitoring, mapping of terrains and in military expeditions.

The operation principles of LIDAR are similar to those of radar technology except that in the place of radio waves or microwaves, LIDAR uses visible, infrared or ultraviolet light (Muster et al. 61). Due to these properties, LIDAR is applicable in agriculture to as it can be used to create detailed maps of agricultural farms hence allowing farmers to get a detailed picture of different sections, information that is critical in ensuring maximum output. LIDAR is also applicable in the military in waging biological warfare and in the detection of hidden landmines. An example of LIDAR is the laser remote sensing of atmospheric properties (Gupta 38). Active sonar is applicable in the determination of the locations and directions of objects under water.

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The Resolutions of Remote Sensing

Remote Sensing systems function on the principle of the inverse problem. This is where the information gained about the area or phenomenon under study is arrived at by analyzing the observed characters, features or measurements of the area or the phenomenon. The nature of the measurements a remote sensing system can determine depends on four resolution types. These include spatial resolution, spectral resolution, radiometric resolution and temporal resolution.

Spatial Resolution

Spatial resolution is a terminology referring to the relationship between the pixel sizes of the image created by a remote sensing system and the size of the actual sample that is being studied. Typical spatial resolution pixels may relate to the locality in length for example from 1 to 1001meters (Mather and Brandt 91). The resolution varies depending on the phenomenon that is under study. Meteorologists whose only interest, for example, are the weather patterns do not require very detailed images that show even structures constructed by the humans’ such as roads and houses. Such an image is hence taken in low resolution as that is sufficient to highlight the weather conditions. An example of mid-resolution equipment is the one used in the Landsat project that has the capability of capturing moderate resolution enough enormous man-man structures but not smaller objects such as homes and vehicles. Other applications of remote sensing such as mapping and military planning nonetheless require high-resolution images to provide critical details. 

Spectral Resolution

This refers to the width of the wavelength of the frequency bands captured by a remote sensing equipment or system. Spectral resolution is studied concerning the number of bands that the remote sensing system can record. A particular example is the multispectral systems that take measurements regarding discrete bands. Each of the bands detected has certain wavelengths that mostly correspond to specific objects of study or phenomena (Rautiainen et al. 55). NASA’s MODIS, for example, can detect up to 36 bands of spectral, where bands with wavelengths of 890 to 965 micrometers represent the cloud and other properties of the atmosphere.

Radiometric Resolution

This refers to the ability of a remote sensing system to distinguish between varying quantities of energy represented in the format of binary data. Remote sensing systems or equipment that have high radiometric power can identify minor variations the magnitude of energies. This normally ranges between 8 and 14 bits and represents up to 256 levels for black and white and up to over 16300 shades for color in individual bands (Atzberger 67). Radiometric corrections can be carried out to avoid errors and distortions.

Temporal Resolution

Temporal resolution is the measure of the frequency through which a satellite moves over the area or phenomenon under study. In instances of meteorology and military applications, it is necessary to have a high temporal resolution to capture updated data and information. For mapping, however, equipment with low-resolution temporal values may be used.

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Extraction of Information from Remote Systems

Information collected from remote sensing systems is extensively wide and diverse. The process of extracting the information hence varies depending on the goal of the remote sensing process. The type of equipment and technique employed also vary with the nature of the phenomenon under observation. In mapping, for example, the process of extracting information is image centered hence it involves keeping the focus on the spatial relationship between images in the study area to develop bigger images (Rautiainen et al., 105). Where the extraction of information is image centered as such, photo-interpretation relies on the help of the human eye. Photo-interpretation is the process of analyzing patterns, shapes, sizes, textures, shadows, and tones of the images captured by the remote sensing systems. In cases where remote sensing is applied in mapping, however, the data-centered approach is more fitting. The data-centered approach in this scenario involves the analysis of all spectral absorption properties of the locality under study and the percentages of isotopes in the materials in the same locality. When applied for long-term determination and monitoring of environmental trends, remote sensing mostly uses all the two approaches, data-centered approach and image-centered approach.

Emerging Issues in Remote Sensing

High costs: The cost of running and maintaining remote sensing systems can be expensive. This is especially in cases where the nature of the information required is such it requires detailed data or information. These high costs limit the scope, and use of remote sensing systems as only the rich people or even nations can experiment extensively with the systems. The second emerging issue in remote sensing is the human made division into categories such as land, ocean, and atmosphere (Gupta 18). These divisions limit the ability of the stakeholders in the field and make the processes more expensive since these entities can use shared sensors instead of each running individuals sensors for all operations.


Remote sensing is applicable in several fields in collecting information that provides new opportunities to human beings. The benefits reaped from remote sensing can be better and more extensive if the organizations in charge of remote sensing systems such as NASA should manage their operations better. The divisions in the field act as obstacles limiting the extent of advancements that can be realized in the field of remote sensing. Governments should additionally allocate more funds to the research and growth of remote sensing systems. Information gained from remote sensing expeditions can help in planning and strategy of a better future. Governments should also create more opportunities in the field to lure young scholars into the field. This will ensure continuity and bring in new perspectives and ideas towards bettering remote sensing.


Remote sensing involves detecting and identifying the features of a physical locality or a phenomenon by measuring radiations reflected by the radiations. The scope of application of remote sensing is wide and runs from agriculture to geography and land survey. Other applications of remote sensing include oceanography, glaciology and in military planning and strategizing. Remotes sensing dates back to the 1840s and has since made several advancements. Remote sensing was widely adopted after World War one with the advancements in aircraft technology. It has evolved from balloonist photographs to using space satellites to capture information. Remote sensing processes are guided by the relationship between the object and energy of the electromagnetic spectrum. Depending on the area of the wavelength under detection, remote sensing can be classified as visible and reflective infrared, thermal infrared or as microwaves. Remote sensing can be either passive or active. Passive remote sensing systems are the systems that do not emit radiation but depends on the sun or other energy sources. Active systems, however, emit artificial radiations that are directed towards the object under study. An example of the active remote sensing system is LADAR and Radar. The nature of the measurements of a remote sensing system can be a spatial resolution, spectral resolution, radiometric resolution or temporal resolution. The information extracted from remote sensors can be either a data-centered approach or an image-centered approach. The practice of remote sensing faces the challenge of divisions among managing bodies and a high cost of operations. To improve the productivity of remote sensing expeditions, the remote sensing practitioners need to find a unified framework to operate within. Governments should also increase allocation towards research and advancement in the field aside from availing new opportunities to young scholars.

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  1. Atzberger, Clement. “Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs.” Remote Sensing 5.2 (2013): 949-981.
  2. Gupta, Ravi P. Remote Sensing Geology. Springer Science and Business Media, 2013.
  3. Lillesand, Thomas, Ralph W. Kiefer, and Jonathan Chipman. Remote Sensing and Image Interpretation. John Wiley and Sons, 2014.
  4. Mather, Paul, and Brandt Tso. Classification Methods for Remotely Sensed Data. CRC press, 2016.
  5. Metz, Markus, Duccio Rocchini, and Markus Neteler. “Surface Temperatures at the Continental Scale: Tracking Changes with Remote Sensing at Unprecedented Detail.” Remote Sensing 6.5 (2014): 3822-3840.
  6. Muster, Sina, et al. “Water Body Distributions across Scales: A Remote Sensing Based Comparison of Three Arctic Tundra Wetlands.” Remote Sensing 5.4 (2013): 1498-1523.
  7. Rautiainen, Miina, et al. “Seasonality of a Boreal Forest: A Remote Sensing Perspective.” EGU General Assembly Conference Abstracts. 18 (2016).
  8. Ulaby, Fawwaz Tayssir, et al. Microwave Radar and Radiometric Remote Sensing. 4.5. (2014). Ann Arbor: University of Michigan Press, 
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