Remote Sensing Fundamentals and Applications

Remote sensing is one of the process of receiving or monitoring the information of any object or place on the surface without direct contact, and it is through images obtained from satellites or from other resources like imaging systems on cranes and towers, aerial imaging systems like aircraft etc.,. Images from the satellite, Arial imaging system or from the aircraft can be used for remote sensing, where we can see more information that images taken from ground surface. Variations in the earth surface can be accurately predicted through remote sensing and even the temperature changes can also be identified clearly. For analyzing under sea objects these remote sensing concepts can be used to take pictures of objects present in the bottom of the sea through sonar systems.

Principle behind remote sensing is electromagnetic radiation to or from the object, which is used to find the details in the image.  Application areas for the remote sensing are enormous. Among them few important applications are weather forecasting, resource planning, Hydrology, Oceanography, geology, meteorology, etc., Research based ideas are having maximum scope in remote sensing applications.

The Information obtained through remote sensing is of both qualitative and quantitative. Example for qualitative information are identification of land type, forest type etc., similarly for quantitative information, amount of a particular mineral present in the land or nutrients present in the soil etc.,

The following are the pronounced applications of remote sensing and the brief details of those applications are given here,

(i) Soil analysis from the satellite images using sensors

Analysis of soil will be very much useful in various fields like agriculture, metallurgy, hydrology etc., Humidity levels of soil, temperature of soil, soil type based on its texture and color, soil moisture level are some of the features that can be identified from the images collected from satellite. These features are very much useful for real time applications. In particular Hyper spectral satellite images are used to identify the objects with higher accuracy.

(ii) Weather forecasting

The climatic changes can be identified from the satellite images through remote sensing concept.

From the images captured using remote sensing we can analyze the Earth’s water cycle, weather condition and details of floods, temperature level during day and night and lot more data’s can be obtained in this remote sensing process. Tracking clouds will help in this work to predict the weather condition.

(iii) Forest Fire detection

Remote sensing will be the appropriate technique to detect forest fire or the disasters happened in the forest, because inside the dense forest human cannot enter and identify what is happening there. If any disaster happens there due to fire or flood that can be identified from the images taken by satellite. Even after this the changes occurred due to these disasters can be identified accurately.

(iv) Usage of remote sensing for Geographers

Remote sensing can be used to monitor and identify or measure the physical phenomena present in various layers of earth’s surface like lithosphere, biosphere, atmosphere, and hydrosphere. For this process sensors are used based on the application. This is the main focus for geographers.

(v) Remote sensing for rescue operations

Many of the airplane crashes or missed aircraft can be identified using remote sensing. This will save many lives and rescue operations will be easy when the images are obtained through remote sensing and processed.

(vi) Hyper spectral remote sensing for identification of mineral deposits

There are plenty of natural minerals available in the earth’s surface. Each of the minerals will have different chemical composition. This chemical composition will be reflected with different color composition and it is identified by the hyper spectral images from remote sensing. This process will be very much useful for metallurgy and geology applications. Hyper spectral images have more spectral bands which will reflect the fine details present in the earth’s surface and based on that the details will be extracted.

(vii) Detection of forest disease and identification of its type

Healthy forest will provide healthy human life surrounded by the forest. If any abnormal incident occurred in forest, it will create an impact in the life of people in and around that area. Using remote sensing continuous monitoring of the forest plants and trees will be made and deformities in terms of the color of the trees or plants, changes in the texture of the leaves etc., will be identified with this remote sensing concept.

(viii) Detection of active volcanoes

Thermal remote sensing will be used to detect active volcanoes. Active volcanoes are very dangerous for human life and the environment. We cannot save any people from that situation, but if it is identified earlier it can save many lives. Hyper spectral remote sensing concept can be used to identify the vulnerability of the volcanoes and based on that we can create alert for people around that area.

(ix) Detection of impact of natural hazard

Remote sensing can be used to identify the changes occurred due to disasters like flood, earthquakes, landslides etc., Remote sensing will be used to predict the occurrence of these disasters based on its continuous monitoring of the earth’s surface. Images captured before and after disasters will be analyzed to identify the changes take place in the environment.

Quality of remote sensing

One of the important points to discuss is on the quality of the data obtained from remote sensing for further processing; it depends on various resolutions like spectral, spatial and radiometric. Spectral resolution deals with the frequency bands that has been observed, ex; Landsat data is based on seven different spectral bands with a resolution from 0.7 to 2.1 micrometer. Spatial resolution is based on the size of the image in terms of number of pixels. Image in a particular area can be represented with various pixel sizes. When the numbers of pixels are increased then resolution will get improved. Radiometric resolution is the ability to differentiate the intensity levels in an image; it depends on the number of color shades present in the image.

Conclusion

The information given in this blog is the basic concept of remote sensing and brief details of few applications of the remote sensing. Further in future detailed study will be given on each application. This will be useful for researchers to develop their own system using remote sensing.