Remote Sensing and Its Major Applications | Simplified 2021

There is energy source or illumination, radiation and the atmosphere and interaction with the target. Other critical stages are recording of energy by the sensor, transmission, reception and processing. We also have interpretation and analysis and finally application. Remote sensing finds wide applications in studying elements both on the global surfaces and the atmosphere. What makes remote sensing popular is its easiness in retrieving data. Moreover, another critical trait is its ability to respond fast to certain demands. 

Remote sensing by definition represents the science of information acquisition concerning the surface of the earth without being in contact with the actual surface. This is made possible through sensing as well as recording emitted or reflected energy and processing, analyzing and applying that information. This therefore demonstrates that the remote sensing process usually involves the interaction between incident radiation and the targets of interest. Remote sensing is mainly comprised of seven major elements. There is energy source or illumination, radiation and the atmosphere, interaction with the target, recording of energy by the sensor, transmission, reception and processing, interpretation and analysis and finally application.

remote sensing

Elements of Remote Sensing Process

Energy Source – This represents the first step of remote sensing. Evidently, the energy source is used to provide or illuminate electromagnetic energy to the target of interest. There are basically two main sources of energy: the sun and the remote sensing system itself. It is, however, critical to note that the sun provides most of the energy needed for remote sensing.

Radiation and atmosphere- All emitted energy must pass through the atmosphere. As the energy travels from its source to the target, it usually interacts greatly with the atmosphere. Evidently, this interaction can take place a second time as the energy travels from the target to the sensor. The atmospheric conditions, as well as the wavelength of the energy, determines the atmospheric effects on electromagnetic energy.

Interaction with the earth’s features- Once the energy reaches a given target, interaction between the two happens. However, this interaction is closely guided by the properties of both the radiation and the target. Once the energy reaches the target, some is absorbed, some is reflected while some is transmitted through the object.

Recording of energy by the sensor- After the energy has been emitted from or scattered by the target a sensor is needed to collect as well as record electromagnetic radiation. The sensor systems detect the energy from the object using the film a process referred to as photography or it could use electronic detectors such as digital cameras and scanners or it can use antennae.

Transmission, Reception, and Processing- The energy which is recorded by the sensor is transmitted in an electronic form to processing and receiving station. The data is then processed into images. An image can either be in a digital form or hard copy. The recorded data is then processed to generate data product for further analysis or for data product display. These products include photographic or digital image, image maps, and image mosaics.

Interpretation and Analysis- The processes image is usually interpreted to extract information about the object which was illuminated. There are two major categories of interpretation and analysis:

Visual Interpretation

Digital Imaging Processing (DIP) or Digital Analysis

Process of Digital Image Processing

The process of digital imaging processing follows three-step phases: pre-processing, image enhancements and information extraction.

  • Pre-Processing- Among the major phases of pre-processing include corrected for the geometry of the image, radiometric distortions as well as the image noise for purposes of conducting an analysis.
  • Image Enhancement- It is usually applied to more effectively display or record the image data for subsequent visual interpretation. Enhancement is therefore done to improve the current status of the image.
  • Information extraction- Text data which is usually present in images usually contain useful information for an automatic explanation, structuring as well as indexing of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement as well as recognition of the text from a given image. Among the method available for information extraction include image classification, change detection, Indices, Extraction of physical quantities as well as extraction of specific features.
Remote Sensing

Physics of Remote Sensing

Electromagnetic energy is usually a dynamic form caused by acceleration of electrical charge or synthetic and natural substances above-average absolute 0k (-273.160C). It usually emits a range of electromagnetic energy. Nearly all the electromagnetic energy which is ejected into the earth’s system is produced by the sun. The process of energy transfers follows three methods:

  • Radiation- Energy transfer from one body to another in the absence of an intervening material medium. This is considered to be the only method which solar energy reaches the earth and the energy transfer concerned in remote sensing.
  • Conduction- This represents the direct transfer of energy with direct physical contact.
  • Convection- This is the energy transfer by physical movements of either liquids or gasses.

Electromagnetic Radiation (EMR)

This by simple definition represents the electromagnetic energy which is in transit. It is usually detected when it comes into direct contact with matter. In the absence of matter, the electromagnetic radiation is known to travel at a speed of light (3×108m/s). Electromagnetic radiation is usually described by two models; wave model and particle model.

Remote Sensing
  • Wave model of EMR- This represents an EMR which is carried by a series of continuous waves which are equally spaced as well as repetitive in time and space. Clearly, electromagnetic radiation usually consists of two fluctuating fields. One is magnetic with the other one being magnetic which are perpendicular to each other. They are also perpendicular to the direction of the propagated wave. The relationship between wavelength and frequency is given by

C = Vλ where:

C = Speed of Light (3.0 x 108m/s)

V= Frequency (Oscillations/second or Hz).

λ = Wavelength

  • Particle model of EMR– This emphasizes the behavior of the EMR as if the radiation were composed of a collection of discrete particles like objects known as quantum or photons. Photons are known to carry particular-like traits such as momentum and energy from the source but usually have no mass. The intensity of EMR is directly related to the number of photons present as well as the energy of the quantum.

Quantum energy is calculated as:

Q= hv =hc/ λWhere;

Q= Energy of photos in Joules

H= Plank’s constant. (6.626×10-34J)

V= Frequency (Hz)

λ = Wavelength (m)

Note: Any object more than zero kelvin usually emit electromagnetic energy.

Energy Interaction with The Atmosphere and Earth’s Surface

The energy which is reflected by the remote sensing sensors is usually radiated by the sun. Through the speed of light, it is propagated through the vacuum of space. It then interacts with the earth’s atmosphere before interacting with the target of interest. It then interacts with the atmosphere again before it reaches the remote sensors where various interactions take place with the aid of the optical systems. This, therefore, demonstrates that the incident radiation may be scattered by the atmosphere or might be absorbed by the earth’s features. Another possible scenario is a reflection as well as could be emitted. Energy interaction with the features on the earth surface is thus given as follows:

Remote Sensing

EI(λ) (incident energy) = ER(λ) (reflected energy) + EA(λ) (absorbed energy) + ET(λ) (energy transmitted).

Energy reflected by the earth’s features is calculated as:

ER(λ) = EI(λ) – [EA(λ) + ET(λ)]

The Geometric manner through which objects reflect energy is a function of the surface roughness. It is usually categorized into three:

  1. Specular reflectors
  2. Diffuse reflectors
  3. Spread reflector
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Types of Remote Sensing

There are two types of remote sensing. They include:

Active Remote Sensing.

Passive Remote Sensing

Active Remote Sensing: the energy source is the remote sensing itself. The majority of the active sensors usually operate in the microwave portion of the electromagnetic spectrum. Among the active remote sensors include laser altimeter, lidar, radar, ranging instruments, scatterometer, and sounder.

Passive Remote Sensing: in this category of remote sensing, the naturally reflected or radiated energy from the earth’s surface features is measured by the sensors operating in various selected spectral bands on board the airborne platforms. Among the passive remote sensors include accelerometer, hyperspectral radiometer, imaging radiometer, radiometer, sounder, spectrometer, and spectroradiometer.

Remote Sensing can also be classified into three types:

  • Visible and Reflective Remote Sensing.
  • Thermal Remote Sensing.
  • Microwave Remote Sensing.
Remote Sensing


This is the bending of light when it passes from one medium to another due to varying densities. The index of refraction represents a measure of the optical density of a substance.


This represents the unpredicted diffusion of radiation by particles in the atmosphere. There are three types of scattering:

  • Rayleigh scattering – This represents the scattering done by air particles or molecules size < 1/10 wavelength. This type of scattering is strongly wavelength dependent. Moreover, it is considered to be over dominant from overhead and usually favors the short wavelength.
  • Mie scattering – This represents the type of scattering done by air molecules and particles > 1/10 wavelength. This type of scattering is considered not to be wavelength dependent. Its intensity is usually projected forward e.g the white light from the fog or the white glare around the sun.
  • Non-Selective Scattering- Occurs when the atmospheric molecules and particle diameters are much larger than the wavelength of the interactive radiation. Water droplets are known to scatter all visible as well as near to mid-infrared wavelength equally.


This represents the effective loss of energy to atmospheric constituents. The most efficient absorbers of EMR are carbon (ii) oxide, Ozone, and water.

Atmospheric Windows

The transmission traits of the earth’s features usually vary with wavelength. Some wavelengths are blocked while others are transmitted almost perfectly. The range of wavelength which is transmitted well by the atmosphere are referred to as atmospheric windows. It is these windows which are used for remote sensing. The common atmospheric windows are:

  1. Ultraviolet to near-infrared (0.3 μm – 1.2 μm)
  2. Mid Infrared Band (3 μm -5 μm & 8 μm-14 μm)
  3. Microwave Band 

Spectral Bands Used in Remote Sensing

Remote sensing in the ultraviolet spectrum.

Most of the UV light is usually scattered by the earth’s atmosphere. It is thus nit widely applied in remote sensing. However, some materials when well illuminated by U.V radiation re-emits it as visible light. Based on this, some specialized airborne remote sensing systems have been designed to illuminate a target area with UV and record the visible light emitted applied in oil spills detection on water.

Remote sensing in the visible spectrum

The wavelength, in this case, ranges from (0.4 μm – 0.7 μm). The energy which is provided by the sun and which is available for detection is maximum in the above range. In addition, remote sensing in this spectrum uses electronic sensors, digital scanners, cameras, and films. Remote sensing in the visible part of the spectrum has the following uses:

  • Visible blue (0.45 μm – 0.5 μm) – it is mainly used for the analysis of water characteristics such as coastal zonal mapping, water quality and depth among others. It is also used for soil and water discrimination, for soil types, geology, and identification of cultural features.  
  • Visible green (0.53 μm – 0.6μm) – used for vegetation discrimination, plant vigor assessment as well as analysis of cultural features and urban infrastructures such as roads and buildings.
  • Visible red (0.63 μm – 0.68 μm) – Used in chlorophyll absorption band for healthy green vegetation, for discrimination of vegetation type, assessing plant condition, delineating soil and geologic boundaries and furthermore, it is used for water quality analysis.
  • Panchromatic band (0.5 μm – 0.9 μm)- This is usually collected at higher spatial resolution.

Remote sensing in the infrared spectrum

This mainly ranges from (0.7 μm – 1000 μm). It mainly includes the near-infrared, short infrared, medium infrared, long-wave as well as the far-infrared. Clearly, the near-infrared is considered to be better in distributing vegetation types, for biomass estimation as well as condition monitoring. Additionally, the shortwave infrared is useful for land cover classifications and distinguishing clouds from ice and snow.

Remote sensing in the micro-wave region.

This one usually has wide applications because of its advantages. It usually has more energy and therefore not scattered by the atmosphere. This type is also used at night and in extreme weather conditions. Moreover, this type allows for overlap which produces 3D useful for terrain analysis.

Spectral Reflectance

This represents the portion of the incidence energy which is reflected and normally expressed as a percentage:

e(λ)= [ER(λ)/ EI(λ)] x 100 where:

e(λ) = spatial reflectance.

ER(λ) = reflected energy.

EI(λ) = Incident energy.

Spectral response pattern– This represents the spectral reflectance or emittance of a terrain feature.

Spectral signature curve – This is the spectral response measured to assess the type and or the position of the features.

Spectral reflectance curve – A graph for spectral reflectance of an object as a function of wavelength. It is critical to note that all features and phenomenon have varying and unique reflectance curves.

Temporal effects – These are factors which change the spectral characteristics of a feature over time. An example is vegetation in different seasons e.g winter and summer.

Spatial effects – These represents factors which cause the same type of feature at a given point of time to have different spectral characteristic at different locations.

Types of Remote Sensing Sensors.

  • Passive sensors – They sense naturally type of energy.
  • Active sensors – These sensors incorporate own energy source e.g radar.
  • Static sensors – These are sensors which are based on geostationary platforms.
  • Dynamic sensors – These are sensors on the orbiting platform.
  • Scanning sensors – Sensors with the capabilities of producing images.
  • Non-scanning sensors – These are sensors which produce profiles.

Remote Sensing Platforms

A platform represents a carrier or vehicle in which remote sensors are born. Typical platforms are aircraft and satellites. We also have the helicopters and balloons. It is critical to note that one platform can have more than one sensor. Evidently, among the major factors which should be considered when describing a platform include altitude, attitude, orbit and play load (weight of platform).

Uses of Remote Sensing

 Remote sensing is widely used in studying elements both on the global surfaces and the atmosphere. What makes remote sensing popular is its easiness in retrieving data as well as its ability to respond fast to certain demands. notable uses of remote sensing:

In meteorology, remote sensing finds usage in profiling of atmospheric temperature, pressure, water vapor as well as wind velocity.

In oceanography, remote sensing finds applications in measuring sea surface temperature as well as mapping ocean currents. Furthermore, remote sensing finds usage in wave energy spectra.

Glaciology – measuring ice cap volumes. Moreover, remote sensing finds applications in ice stream velocity as well as sea ice distribution.

Geology – In addition, geomorphology as well as identification of rock type. Moreover, there are applications in mapping faults and structure.

Geodesy – measuring the figure of the earth and its gravity field.

Topography and cartography – improving digital elevation models

Agriculture, forestry, and botany – monitoring the biomass of land vegetation, monitoring the health of crops as well as mapping soil moisture. Furthermore, it is used to forecast crop yields.

Hydrology – assessing water resources from snow, rainfall and underground aquifers.

Disaster warning and assessment – monitoring of floods and landslides, monitoring volcanic activity, assessing damage zones from natural disasters.

Planning applications – mapping ecological zone and monitoring deforestation. Additionally, it is used in monitoring urban land use.

Remote sensing is also used in oil and mineral exploration. It is applied in locating natural oil seeps and slicks as well as mapping geological structures. Furthermore, it is used in monitoring oil field subsidence.

In the military, one primary usage is in developing precise maps for planning. In addition, it is used in monitoring military infrastructure. Moreover, remote sensing is used in monitoring ship and troop movements . . . (This is where most of the US funding for remote sensing goes.

Remote sensed images find wide applications in:

The first application of remote sensed images island covers mapping. Moreover, these images find usage in land cover change. In addition, these images are used for sea surface temperatures. Additionally, some of the remotely sensed images are applied for snow survey. Furthermore, the remotely sensed images are applied in monitoring atmospheric constituents. Additionally, the remotely sensed images are used for geological interpretation as well as DEM generation.

Scanning Systems in Remote Sensing

There are three main types of a scanning system in remote sensing.

  1. Across track scanning – Also referred to as whiskbroom scanning. It usually scans the earth in a series of lines. The lines are perpendicularly oriented to the direction of motion of the sensor platforms. Each line is scanned from one side of the sensor to the other using a rotating mirror.
  1. Along track Scanning – Also referred to as push-broom scanning. It mainly uses the forward motion of the platform to record successive scan lines and build up a two-dimensional image perpendicular to the flight direction. Evidently, instead of using scanning mirrors, they apply a linear array of detectors which are located at the focal plane of the image.
Remote Sensing
Along track scanning

Common Terminologies Used in Remote Sensing.

  • Radiometric distortions – It represents the radiometric anomalies caused by sensor noise and responses of detectors. The variations in viewing geometry, as well as variations in atmospheric conditions, also causes this condition. However, it is imperative to note that variation in scene illumination and viewing geometry to a large extent results in non-uniform tonal or color balance of multidate image of the same location or images adjacent location. This affects change detection and mosaicking applications.
  • Spectral resolution – This represents the number of wavelength position and width of spectral bands that a sensor has. On the other hand, multispectral sensors usually have few but wide bands while hyperspectral sensors have many but narrow bands.
  • Spatial resolution – This represents the size of the smallest possible features which can be detected and it depends on the instantaneous field of view of a sensor.
  • Temporal resolution and Extent – Temporal resolution represents the shortest amount of time between image acquisitions of a given location. On the other hand, temporal extent, on the other hand, represents the time between sensor launch and retirement which may affect historical data availability.
  • Radiometric resolution – It describes the ability to discriminate very slight differences in energy. If a sensor uses 8 bits to record a data, then there will be 28 =256 levels of digital values.
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