Remote sensing

Remote sensing- GIS and its application


Remote Sensing

Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object and thus in contrast to on-site observation.

In current usage, the term “remote sensing” generally refers to the use of satellite- or aircraft-based sensor technologies to detect and classify objects on Earth, including on the surface and in the atmosphere and oceans, based on propagated signals.

Remote sensing is used in numerous fields, including geography, land surveying and most Earth Science disciplines for example, hydrology, ecology, oceanography, glaciology, geology.It also has military, intelligence, commercial, economic, planning, and humanitarian applications.


Geographic Information System (GIS) is a computer based application of technology involving spatial and attributes information to act as a decision support tool.

It keeps information in different layers and generates various combinations pertaining to the requirement of the decision-making. In the recent times, GIS has emerged as an effective tool in management of disasters since, geo-spatial data and socio-economic information need to be amalgamated for the better decision making in handling a disaster or to plan for tackling a disaster in a better way.


Disaster Management

The different line departments and agencies who are stakeholders in the disaster management process could utilize GIS. Some basic hardware like computer system, printer, network systems, along with GIS software is required to set up the GIS in any organisation.


The prime objectives of developing the GIS database are to help disaster managers at State, District and Block level for:

  1. i) Pre-disaster planning and preparedness
  2. ii) Prediction and early warning

iii)                 Damage assessment and relief management

GIS combines layers of information on various themes to enable the managers to take the most appropriate decisions under the given circumstances. For disaster management, a GIS database could be a useful managerial tool for various reasons, some of which are as under:

  • Disaster Managers could generate maps both at micro and macro level indicating vulnerability to different extents under different threat perceptions.
  • Locations likely to remain unaffected or remain comparatively safe could be identified.
  • Alternate routes to shelters, camps, and important locations in the event of disruption of normal surface communication could be worked out.
  • Smooth rescue and evacuation operations could be properly planned.
  • Rehabilitation and post-disaster reconstruction works could be properly organized.
  • Locations suitable for construction of shelters, godowns, housing colonies, etc. can be scientifically identified.
  • Areas where no construction should be taken up or existing habitations require relocation could be identified.


Remote sensing of hydrologic processes can provide information on locations where in situ sensors may be unavailable or sparse. It also enables observations over large spatial extents. Many of the variables constituting the terrestrial water balance, for example surface water storage, soil moisture, precipitation, evapotranspiration, and snow and ice, are measurable using remote sensing at various spatial-temporal resolutions and accuracies. Sources of remote sensing include land-based sensors, airborne sensors and satellite sensors, which can capture microwave, thermal and near-infrared data or use LIDAR.

Weather forecasting and Ecology

Many ecological research projects would benefit from the creation of a GIS to explore spatial relationships within and between the data.  In particular, while some projects can be done without using a GIS, many will be greatly enhanced by using it (click here for some examples of research projects which have used GIS).

The very act of creating a GIS will make you think about the spatial relationships within your data, and will help you formulate hypotheses to test or suggest new ones to explore.  In addition, thinking about your data in a spatial manner will help you identify potential spatial issues and/or biases with your data.

GIS can also be used to make measurements and carry out calculations which would otherwise be very difficult.  For example, a GIS can be used to work out how much of your study area consists of a specific habitat type, or how much of it is over 1,000m high, or has a gradient greater than 5º, and so on.  Similarly, a GIS can be used to calculate the size of the home range of an individual or the total area occupied by a specific species or how long your survey tracks are, or how much survey effort was put into different parts of your study area.

GIS can also be used to link data together in the way that is needed for statistical analysis.  For example, many statistical packages require all your data to be in a single table, with one line per sample and then information about that sample and the location where it came from in different columns or fields.  A GIS provides you with a way to easily create such tables and populate it with information, such as the altitude at each location, the gradient of slope and the direction it faces, from other data sets.  This makes preparing your data for statistical analysis much simpler.

Remote sensing refers to the measurement or acquisition of information about an object or phenomena from a distance without physical contact by using devices or sensors mounted on some platform. Remote sensors collect data by detecting the energy that is reflected from Earth. These sensors can be on satellites or mounted on aircraft.

Remote sensors can be either passive or active. Passive sensors respond to external stimuli. They record natural energy that is reflected or emitted from the Earth’s surface. The most common source of radiation detected by passive sensors is reflected sunlight.In contrast, active sensors use internal stimuli to collect data about Earth. For example, a laser-beam remote sensing system projects a laser onto the surface of Earth and measures the time that it takes for the laser to reflect back to its sensor.

The satellites of Indian Remote Sensing (IRS) satellites system which are in service today are IRS-1C, IRS-ID, IRS-P3, OCEANSAT-1, Technology Experimental Satellite (TES), RESOURCESAT-1, and the recently launched CARTOSAT-1 capable of taking stereo pictures. The upcoming Remote Sensing Satellite are Cartosat-2, RISAT (Radar Imaging Satellite) and Oceansat-2.


  • Coastal applications: Monitor shoreline changes, track sediment transport, and map coastal features. Data can be used for coastal mapping and erosion prevention.
  • Ocean applications: Monitor ocean circulation and current systems, measure ocean temperature and wave heights, and track sea ice. Data can be used to better understand the oceans and how to best manage ocean resources.
  • Hazard assessment: Track hurricanes, earthquakes, erosion, and flooding. Data can be used to assess the impacts of a natural disaster and create preparedness strategies to be used before and after a hazardous event.
  • Natural resource management: Monitor land use, map wetlands, and chart wildlife habitats. Data can be used to minimize the damage that urban growth has on the environment and help decide how to best protect natural resources.

A multispectral image consists of several bands of data. For visual display, each band of the image may be displayed one band at a time as a grey scale image, or in combination of three bands at a time as a colour composite image. Interpretation of a multispectral colour composite image will require the knowledge of the spectral reflectance signature of the targets in the scene. In this case, the spectral information content of the image is utilized in the interpretation.
The following three images show the three bands of a multispectral image extracted from a SPOT multispectral scene at a ground resolution of 20 m. The area covered is the same as that shown in the above panchromatic image. Note that both the XS1 (green) and XS2 (red) bands look almost identical to the panchromatic image shown above. In contrast, the vegetated areas now appear bright in the XS3 (near infrared) band due to high reflectance of leaves in the near infrared wavelength region. Several shades of grey can be identified for the vegetated areas, corresponding to different types of vegetation. Water mass (both the river and the sea) appear dark in the XS3 (near IR) band.

The Global Positioning System consists of 24 satellites, that circle the globe once every 12 hours, to provide worldwide position, time and velocity information. GPS makes it possible to precisely identify locations on the earth by measuring distance from the satellites. GPS allows you to record or create locations from places on the earth and help you navigate to and from those places.

GPS satellites circle the Earth twice a day in a precise orbit. Each satellite transmits a unique signal and orbital parameters that allow GPS devices to decode and compute the precise location of the satellite. GPS receivers use this information and trilateration to calculate a user’s exact location. Essentially, the GPS receiver measures the distance to each satellite by the amount of time it takes to receive a transmitted signal. With distance measurements from a few more satellites, the receiver can determine a user’s position.

GPS System has three segments:-
Space Segment
The space segment consists of a nominal constellation of 24 operating satellites that transmit one-way signals that give the current GPS satellite position and time. The space segment consists of 24 satellites circling the earth at 12,000 miles in altitude. This high altitude allows the signals to cover a greater area. The satellites are arranged in their orbits so a GPS receiver on earth can always receive a signal from at least four satellites at any given time.
Control Segment
AF flight control officer The control segment consists of worldwide monitor and control stations that maintain the satellites in their proper orbits through occasional command maneuvers, and adjust the satellite clocks. It tracks the GPS satellites, uploads updated navigational data, and maintains health and status of the satellite constellation.
User Segment
receiver The user segment consists of the GPS receiver equipment, which receives the signals from the GPS satellites and uses the transmitted information to calculate the user’s three-dimensional position and time.

GPS Aided Geo Augmentation Navigation (GAGAN) is a planned implementation of Satellite Based Navigation System (SBNS) developed by Airports Authority of India (AAI) and ISRO. GAGAN is expected to provide a civil aeronautical navigation signal consistent with International Civil Aviation Organization (ICAO) Standards and Recommended Practices as established by the Global Navigation Satellite System Panel. GAGAN was launched in August 2010. With this India has become the 4th Country in the World to have satellite based navigation system.  It is a system to improve the accuracy of a GNSS receiver by providing reference signals.


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