Remote Sensing: Types, Uses, Advantages and Disadvantages

Remote sensing is one of a group of geospatial technologies that is gaining traction in a range of fields, including business, research, and government policy. 

 

With advancements in sensor system technology and digital processing, the field of remote sensing has progressed from aerial photography interpretation to satellite imagery analysis, and from small region studies to worldwide assessments. 

 

Energy emitted, reflected, and/or transmitted from all sections of the electromagnetic spectrum may now be used to deliver data to distant sensor systems. 

 

Population and demography research, archaeological site investigations, energy studies utilizing hydrological models, urban planning, environmental treaty enforcement, and agricultural yields are all examples of applications that may be made using these data.

 

What is Remote Sensing?

 

Although remote sensing techniques have traditionally been thought of as a way to collect data that is subsequently evaluated by the user, they are increasingly being used in scientific and applied research for various purposes. 

 

Remotely sensed data on natural and anthropogenic factors including plant cover, land use, topography, and hydrography are currently being used to feed a variety of simulation models, including hydrologic, climatic, ecological, and economic models. 

 

Scientists blend classified photos of land use and land cover with demographic and socioeconomic data to create models that help them better understand processes like deforestation and land conversion. 

 

Remotely sensed images, as well as the products produced from imaging analysis, are key data sources for geographic information systems (GIS).

 

In fact, most comprehensive image analysis software packages now include GIS functions for change detection overlays, local spatial analysis techniques, conversions between raster (pixel-based grids) and vector (points, lines, and polygons defined and displayed on the basis of two-dimensional Cartesian coordinate pairs) data structures, and other processes that aren't strictly image-related. 

 

By necessity, GIS software programmes interact with raster data and pictures in a variety of formats, and they are increasingly including analytical features that were previously only available in dedicated image analysis tools.

 

Where is Remote Sensing Used?

 

Remote sensing cannot give the same level of information as field-based sampling when it comes to human and environmental issues like water quality, vegetation composition, soil qualities, or plant health. 

 

When combined with field surveying, remote sensing allows for the simultaneous viewing and mapping of enormous regions of the earth's surface, as well as the collection of data for places that would otherwise be difficult or impossible to sample owing to physical or economical restrictions.

 

Remote sensing has therefore become an important research and application tool in a variety of fields, including engineering, geology, geography, urban planning, forestry, and agriculture.

 

Additionally, the Internet has increased the availability and dissemination of remote sensing products, and falling costs combined with continuous improvements in spatial, spectral, radiometric, and temporal resolutions are making remote sensed data accessible to a broader range of end users and expanding the role of remote sensing in society.

 

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Types of Remote Sensing

 

Two common types of remote sensing are available: 

 

1. Active remote sensing

 

2. Passive remote sensing

 

Active and passive sensors are commonly found in remote-sensing systems. An active sensor sends out its own signal, which is then measured when it is reflected by the Earth's surface. A passive sensor detects solar radiation that is reflected or released by objects on the surface of the Earth.

 

Although most passive sensors function in the visible and infrared parts of the EMS, certain passive microwave sensors are also used to monitor variables like wind speed, air and sea surface temperature, soil moisture, rainfall, and atmospheric water vapor.

 

Passive sensors have the benefit of relying on the Sun's light to illuminate the target and hence do not require their own energy source, making them simpler equipment in general. Most passive optical sensors are limited by the fact that they require daylight to work, while certain sensors can capture nocturnal lights and clouds, as well as energy released from the Earth's surface. 

 

Weather and cloud cover have a negative impact on these sensors since they operate in the visible and infrared wavelengths. Finally, because sunlight is typically reflected from the top of a feature, such as a forest, it is impossible to quantify plant structure under a canopy.

 

Active sensors are required to get this type of data. Radar and lidar are active sensors that use their own energy to light a target and consist of a signal generator and receiver. 

 

Radar and Lidar

 

Radar and Lidar measure the signal intensity and the time delay between when the sensor produces energy and when it receives the returning pulse. 

 

These two forms of data are utilized to characterize the structure of the vegetation. The term "radio detection and ranging" is an abbreviation for "radio detection and range." Radar devices operate in the long-wavelength microwave section of the EMS, thus clouds and rain have little effect. They are all-weather systems.

 

The term "light detection and ranging" refers to systems that employ lasers to emit light in the visible and near-infrared parts of the electromagnetic spectrum. A single light pulse in a lidar system might reflect off of many vertical features, such as distinct strata in a forest. 

 

A single emitted pulse will generate a wave or series of returning pulses, which the detector will record. These return pulses can be captured as a continuous wave (full-waveform lidar) or in discrete portions that correspond to the returning signal's peaks. A variety of lidar systems have been created, but the majority of them can capture the first and last returns of the light pulse.

 

The returns correlate to the object's top (for example, the top of a tree canopy) and the object's base substrate (i.e., the ground). This is great for determining the height of things like trees and buildings.

 

In terms of how they interact with materials, radar systems differ from optical systems. Most radar systems' signals can easily penetrate a forest canopy, and radar systems with very long wavelengths (e.g., P-band systems) can even reach dry ground.

 

Although lidar is best known for its capacity to acquire digital elevation data that can be used to characterize topography, these systems show a lot of potential in terms of being able to measure plant structural traits directly.

 

Lidar can perform direct measurements of plant structure and offer vertical structural information that is largely lacking in data gathered with passive remote-sensing sensors that only record light reflected from the top of a canopy.

 

The electromagnetic radiation emitted or reflected by the item is the source of remote sensing data, which is subsequently used to help identify and classify the object.

 

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Components of Remote Sensing

 

1. Platform

 

The carrier for remote sensing sensors is characterized as a platform. Ground-based platforms (towers and cranes), aerial platforms (helicopters, low-altitude planes, and high-altitude planes), and spaceborne platforms are the three primary remote sensing platforms (space shuttles, polar-orbiting satellites, and geostationary satellites).

 

2. Sensors

 

It's a gadget that takes in electromagnetic radiation and turns it into a signal that may be stored and presented as numerical data or a picture.

 

Uses of Remote Sensing

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Uses of Remote Sensing

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1. Land Use Mapping

 

Remote sensing data can be used to get the most up-to-date land use patterns for large areas at any given time, as well as track changes over time. It may be used to update road maps, assess asphalt conditions, and identify wetlands. Regional planners and administrators utilize this data to help them formulate policies for the region's overall growth.

 

2. Weather Forecasting

 

In India, remote sensing is widely employed for weather forecasting. It's also used to alert people of approaching cyclones.

 

3. Environmental Study

 

It may be used to investigate deforestation, land degradation, air pollution, desertification, eutrophication of huge bodies of water, and oil spillage from oil tankers.

 

4. Study of Natural hazards

 

Earthquakes, volcanoes, landslides, floods, and ice melting in polar locations may all be studied via remote sensing. Remote sensing may often be used to anticipate the advent of natural disasters.

 

5. Resource exploration

 

Remote sensing data is useful for updating existing geological maps, producing lineament and tectonic maps quickly, detecting mineral quarrying sites, and discovering fossil fuel resources.

 

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Advantages and Disadvantages of Remote Sensing
 

Remote sensing has gone a long way in recent years and is now a powerful surveying tool with several benefits.

 

Advantages of Remote Sensing

 

1. Remote sensing is a quick method. Sensors are put on an aircraft, drone, or even a satellite to measure light reflections from surfaces. The sensors' location allows them to cover a broad region in a short amount of time. Remote sensors can scan and build maps of inaccessible locations by surveying from the air.

 

2. Once data from remote sensors has been acquired, it may be reused and analyzed for a variety of purposes. Remote sensors, for example, might collect data to inspect a building site. The same data, on the other hand, may be utilized to study and plan new roadways.

 

3. Alternatively, data acquired from forests to assess wildfire danger may be utilised to track biodiversity. LiDAR, a remote sensing technique, captures point cloud data, which was previously difficult to analyse. With point cloud software, this data can now be evaluated fast and simply. 

 

4. Because data is examined in a lab using software, the amount of effort required in the field is reduced. Surveys and post-scan analysis can be carried out by small groups.

 

5. The reflected light is measured by remote sensors, which might be natural sunlight or a light pulse. Remote sensing does not disrupt the scanned environment because this light is safe to objects, vegetation, and humans. As a result, it's ideal for surveying urban areas since no highways need to be closed, and communities can go about their business as usual.

 

Disadvantages of Remote Sensing

 

Unfortunately, no technology is without flaws, and remote sensing is no exception. While the benefits of remote sensing exceed the disadvantages, it's a good idea to think about the following drawbacks before investing in this survey approach.

 

1. Remote sensing equipment must be calibrated before use in order to acquire reliable measurements. If the instruments aren't calibrated properly, this leaves the possibility for human error.

 

2. Remote sensing data with high resolution might be difficult to store. You may collect data in a variety of sizes and resolutions with remote sensing. However, collecting high-resolution data might be challenging to store. Large projects might need storage of hundreds of terabytes. There are a variety of storage options available, including Amazon Cloud and Microsoft Azure.

 

Novel sensor techniques are anticipated to emerge as a result of the increased demand. "Interactive remote sensing," which involves farmers genetically "marking" their crops to improve the remotely detectable spectral signature for crop distress or optimal harvesting, is one potential. To lead this future, policy measures are underway.