Remote Sensing: Meaning, Concept and Components | Geography

In this article we will discuss about:- 1. Introduction to Remote Sensing 2. Concept of Remote Sensing 3. Components 4. Satellite Remote Sensing.

Introduction to Remote Sensing:

Remote sensing in the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation. It is a technology for sampling electromagnetic radiation to acquire and interpret non-immediate geospatial data from which to extract information about features, objects and classes on the Earth’s land surface, oceans and atmosphere (and, where applicable, on the exteriors of other bodies in the solar system, or, in the broadest framework, celestial bodies such as stars and galaxies).

Without direct contact, some means of transferring information through space must be utilized. In other words, remote sensing refers to instrument-based techniques used in the acquisition and measurement of spatially organized (distributed) data/information on some property (ies) (spectral; spatial; physical) of an array of target points (pixels) within the sensed scene that correspond to features, objects and materials, doing this by applying one or more recording devices not in physical, intimate contact with the item(s) under surveillance.

The remote sensing techniques involve amassing knowledge pertinent to the sensed scene (target) by utilizing electromagnetic radiation, force fields, or acoustic energy by employing cameras, microwave radiometers and scanners, lasers, radio frequency receivers, radar systems, sonar, thermal devices, seismographs, magnetometers, gravimeters, scintillo­meters and other sensing instruments.

All these advanced instruments gather different types of data that can be interpreted to derive accurate, large-scale information about the Earth’s surface and atmosphere. Because these data and images are digital, they can easily be quantified and manipulated using computers.

This makes remote sensing a uniquely versatile tool, since the same data can be analyzed in different ways for different applications. Some of the fields that use remote sensing are agriculture, forestry, geology, archaeology, oceanography, architecture, meteorology, etc.

Concept of Remote Sensing:

When electromagnetic radiation falls upon a surface, some of its energy is absorbed while some is transmitted through the surface and the rest is reflected. Surfaces also naturally emit radiation in the form of heat. Photographic films or digital sensors in the satellite or aerial vehicle record the reflected and emitted radiation. Since the intensity and wavelengths of this radiation depend on the nature of surface, each surface is described as possessing a characteristic spectral signature.

Specific instruments and software’s are used to identify and distinguish between different spectral signatures which will be ultimately useful in mapping the extent of surfaces. Satellite remote sensing is widely used as a tool in many parts of the world for the management of the natural resources and global activities. The remote sensing is divided into two major categories – satellite remote sensing and aerial photography.

The satellite may be geostationary (which permits continuous sensing of a portion of the Earth) or sun-synchronous with polar orbit (which covers entire Earth at the same equator crossing time. The LANDSAT series satellites have a repeat period ranging from 16-18 days, whereas in IRS satellite, it is 22 days. Sensor is a device used for making observations and uses satellite as platform and observes large areas of the Earth surface.

Components of Remote Sensing:

Major Components of Remote Sensing Technology:

The following are major components of remote sensing system:

1. Energy Source:

i. Passive System:

Sun, irradiance from earth’s materials.

ii. Active System:

Irradiance from artificially generated energy sources such as radar.

2. Platforms:

These are vehicles to carry the sensor e.g. truck, aircraft, space shuttle, satellite, etc.

3. Sensors:

Device to detect electro-magnetic radiation e.g. camera, scanner, etc.

4. Detectors:

Handling signal data e.g. photographic, digital, etc.

5. Processing:

Handling signal data e.g. photographic, digital etc.

6. Institutionalization:

These are organizations for execution of all stages of remote sensing technology e.g. International and national organizations, research centres, universities, etc.

Classification of Remote Sensing:

With respect to the type of energy resources, remote sensing is classified into two categories – passive and active remote sensing.

i. Passive Remote Sensing:

It makes use of sensors that detect the reflected or emitted electro-magnetic radiation from natural sources.

ii. Active Remote Sensing:

It makes use of sensors that detect reflected responses from objects that are irradiated from artificially-generated energy sources, such as radar.

With respect to wavelength regions, remote sensing is classified into three categories:

i. Visible and Reflective Infrared Remote Sensing.

ii. Thermal Infrared Remote Sensing.

iii. Microwave Remote Sensing.

Satellite Remote Sensing:

The Earth is constantly under observation by many satellites orbiting the planet and collecting data. They are engaged in an activity called “remote sensing”, the act of obtaining information about something without being in direct contact with it. The satellite images, as well as the actual predictions, are obtained through remote sensing of the Earth.

The satellites don’t gather the information themselves; they simply orbit the Earth and provide platforms from which the sensors can observe large areas of the surface. Airplanes also provide platforms for remote sensing and some sensors operate from land. Remote sensing satellites are launched by government agencies of many countries including India, and are usually equipped with sensors that serve a particular purpose.

For the past four decades, Indian Space Research Organisation (ISRO) has launched more than 65 satellites for various scientific and technological applications like mobile communications, Direct-to-Home services, meteorological observations, telemedicine, tele- education, disaster warning, radio networking, search and rescue operations, remote sensing and scientific studies of the space.

ISRO has established two major space systems, the Indian National Satellite System (INSAT) series for communication, television broadcasting and meteorological services which is geo-stationary satellites, and Indian Remote Sensing Satellites (IRS) system for resources monitoring and management which is Earth observation satellites. ISRO has launched many experimental satellites which are generally small comparing to INSAT or IRS.

Important Terminologies:

i. Analog and Digital Images:

An image is a two-dimensional representation of objects in a real scene. Remote sensing images are representations of parts of the earth surface as seen from space. The images may be analog or digital. Aerial photographs are examples of analog images while satellite images acquired using electronic sensors are examples of digital images.

ii. Multilayer Image:

Several types of measurement may be made from the ground area covered by a single pixel. Each type of measurement forms an image which carries some specific information about the area. By “stacking” these images from the same area together, a multilayer image is formed. Each component image is a layer in the multilayer image. Multilayer images can also be formed by combining images obtained from different sensors and other subsidiary data.

iii. Multispectral Image:

A multispectral image consists of a few image layers, each layer represents an image acquired at a particular wavelength band. For example, if a sensor operating in the multispectral mode detects radiations in three wavelength bands: the green (500-590 nm), red (610-680 nm) and near infrared (790-890 nm) bands, then a single multispectral scene consists of three intensity images in the three wavelength bands.

In this case, each pixel of the scene has three intensity values corresponding to the three bands. While a Landsat TM multispectral image consists of seven bands: blue, green, red, near-IR bands, two SWIR bands and a thermal IR band.

iv. Superspectral Image:

The more recent satellite sensors are capable of acquiring images at many more wavelength bands e.g. nearly 36 spectral bands, covering the wavelength regions ranging from the visible, near infrared, short-wave infrared to the thermal infrared. The bands have narrower bandwidths, enabling the finer spectral characteristics of the targets to be captured by the sensor.

v. Hyperspectral Image:

A hyperspectral image consists of about a hundred or more contiguous spectral bands. The characteristic spectrum of the target pixel is acquired in a hyperspectral image. The precise spectral information contained in a hyperspectral image enables better characterization and identification of targets.

vi. Spatial Resolution:

It refers to the size of the smallest object that can be resolved on the ground. It is a measure of the smallest area identifiable on a digital image as a discrete separate unit (typically pixels) or measure of the smallest angular or linear separation between two objects that can be resolved by the sensor.

A “High Resolution” image refers to one with a small resolution size. Fine details can be seen in a high resolution image. On the other hand, a “Low Resolution” image is one with a large resolution size, i.e. only coarse features can be observed in the image.

vii. Spectral Resolution:

Spectral resolution describes the specific wavelengths that the sensor can record within the electromagnetic spectrum. Narrow bandwidths in certain regions of the electromagnetic spectrum allow the discrimination of various features more easily.

viii. Temporal Resolution:

Temporal resolution is a description of how often a sensor can obtain imagery of a particular area of interest. It is based on the repeat period of a parti­cular satellite. Ideally, the sensor obtains data repetitively to capture unique discriminating characteristics of the phenomena of interest.

ix. Radiometric Resolution:

Radiometric resolution refers to the smallest change in intensity level that can be detected by the sensing system. It is the capability to differentiate the spectral reflectance/ remittance from various targets. This depends on the number of quantization levels within the spectral band. In other words, the number of bits of digital data in the spectral band will decide the sensitivity of sensor.

Utilization of Satellite Remote Sensing Techniques:

Satellites have been providing multispectral images of the Earth continuously since the early 1970’s. A unique 40 years data record of the Earth’s land surface now exists. This unique retrospective portrait of the Earth’s surface has been used across disciplines to achieve improved understanding of the Earth’s land surface and the impacts of humans on the environment.

Satellite data have been utilized in a variety of government, public, private and national security applications. Examples include land and water management, global change research, oil and mineral exploration, agricultural yield forecasting, pollution monitoring, land surface change detection, cartographic mapping, etc.

Satellite based remotely sensed digital data have been used to map forest resources since the inception of the LANDSAT satellite programme in 1972. Satellites provide synoptic images and homogeneous data, which can be geographically registered over time and which can be therefore an efficient tool for providing high quality forest management information. Since the 1980s, with the availability of scanners, improvements in computer software and development of image processing algorithms, there have been many studies of remote sensing applications in forestry.