Study on Fusion Techniques for Classifying Satellite Images

By Swathika R

Remote sensing is a mechanism whereby a recording device acquires knowledge about certain events without being in physical contact with the object of interest. It provides a synaptic view of Earth's surface at different scale due to the ability of spaceborne sensors to collect data over large areas. In the past two decades, imaging technologies have made greater developments in terms of attainable spatial resolution, spectral resolution and radiometric resolution in the field of remote sensing. The temporal resolution has also improved drastically by the use of agile sensors and the constellation of multiple satellites. At the same time, on-board and ground processing technologies have also advanced to process an enormous amount of data in quick turnaround times. However, remote sensing data are difficult to capture with higher spectral, spatial and temporal resolutions by current satellite platforms due to the technology as well as budget constraints. Hence, it cannot be expected further for more dramatic gains in imaging and ground processing technologies. Even then, working with data provided by a single sensor might not be satisfactory for certain applications of remote sensing such as vegetation monitoring and land cover mapping in the sense of spatial, spectral or temporal resolution. Therefore, the use of multi-sensor data is very essential to overcome the limitations of obtaining a single sensor that meets all the requirements of a remote sensing application. Different sensors provide distinct categories of the images that have distinctive image resolutions, i.e., spatial, spectral, radiometric and temporal resolution. In high spectral resolution is required for exact discrimination of land covers from one viewpoint. At the same time, high spatial resolution is needed for an exact portrayal of the textures and shapes. In image handling, a few circumstances request both high spatial and high spectral data in a single image. In any case, the instruments are not equipped for giving such a sort of data on account of the plan and operational imperatives. Hence, remote sensing image fusion is required to deal with the diversity of data.

• Format: Paperback
• Language: English
• ISBN: 8119549511
• ISBN13: 9788119549511
• Release Date: August 2023
• Publisher: Swathika R
• Length: 142 Pages
• Weight: 0.44 lbs.
• Dimensions: 0.3" x 6.0" x 9.0"