Our planet, Earth, harbors countless enigmas concealed within its depths. However, human interaction with each of these mysteries is often impractical. This is where remote sensing proves invaluable. Through this method, mankind dispatches aircraft or satellites into the atmosphere or space, enabling exploration of Earth's remote corners and maximizing our understanding of the planet.
What is Remote Sensing?
Remote Sensing is the art and science of acquiring information of the earth surface without getting in contact with it. It is the phenomenon of measuring the emitted and the reflected radiation from the object.
Components:
Types of Remote Sensing:
There are two types of remote sensing techniques: Passive and active remote sensing.
(Illustration of passive and active remote sensing. Credits: Abdul-Hameed, Abeer. (2022))
Passive:
When the satellite uses the reflectance of the other source (example: sun) and records it. Optical sensing comes under passive remote sensing. (Eg: Sentinel-2, Landsat)
Active:
Satellite sends its own signal and records the reflected waves from the object. RADAR and LiDAR are examples of active remote sensing which also measures the time delay between the emission and the return, which provides us with more information. (eg: Sentinel-1)
Remote Sensing Platforms
A platform serves as the vehicle or carrier for remote sensors, providing the necessary infrastructure to support the instruments. In Remote Sensing, there are three primary types of platforms:
Ground-based platforms: Record detail information about the surface very closely.
Airborne platforms: Collect data over any portion of the Earth’s surface.
Spaceborne platforms: collecting data through Satellite’s.
(Types of Remote Sensing platforms. Credit: Tian,L. et al (2023))
Resolution
The resolution of sensor data influences its usability. Resolution varies according to the satellite's orbit and sensor type. There are four forms of resolution to consider for each dataset: radiometric, spatial, spectral, and temporal.
Radiometric resolution:
Radiometric resolution is the amount of information in each pixel, or the number of bits reflecting the energy recorded. For example, an 8 bit resolution is 28, which indicates that the sensor has 256 potential digital values (0-255) to store information. Thus, the greater the radiometric resolution, the more values are available to store information.
Spatial resolution:
Spatial resolution is the detail in pixels of an image. High spatial resolution means more detail and a smaller grid cell size. Whereas lower spatial resolution means less detail and larger pixel size.
(Landsat 8 image of Reykjavik, Iceland, acquired July 7, 2019, illustrating the difference in pixel resolution. Credit: NASA Earth Observatory.)
Spectral Resolution:
Spectral resolution refers to the level of spectral detail in a band. High spectral resolution implies narrower bands. In contrast, low spectral resolution has broader bands that cover a larger portion of the spectrum.
Temporal resolution:
Time taken for the satellite to revisit the same observation area. Example: Landsat-8 has a temporal resolution of 16 days.
Conclusion
In conclusion, remote sensing stands as a vital tool in unravelling the mysteries hidden within the depths of our planet, Earth. Human limitations in direct exploration make remote sensing indispensable, allowing us to delve into Earth's remote corners and deepen our understanding of its complexities. Remote sensing operates on the principle of acquiring information without physical contact, employing both passive and active techniques. These methods, facilitated by various platforms such as ground-based, airborne, and spaceborne, enable us to gather data crucial for scientific inquiry and practical applications. The resolution of sensor data, encompassing radiometric, spatial, spectral, and temporal aspects, further enhances the utility and precision of remote sensing, offering insights into Earth's dynamic processes with unprecedented detail. Through remote sensing, we continue to expand our knowledge and address real-world challenges, marking it as an indispensable tool in modern scientific exploration and decision-making.
Reference:
Abdul-Hameed, Abeer. (2022). Remote Sensing Optical Images Applications in Vegetation Monitoring and Mapping, Part of Baghdad Supervised by. 10.13140/RG.2.2.19915.26409.
Tian, L.; Wu, X.; Tao, Y.; Li, M.; Qian, C.; Liao, L.; Fu, W. Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects. Forests 2023, 14, 1086. https://doi.org/10.3390/f14061086