Novel Techniques for Analysing Satellite Imagery Data

Abstract

With the rapid development of space technology, numerous applications are being developed utilising satellite imagery data, including environmental monitoring, meteorology and map making, mapping and monitoring the Earth's resources ecosystems and observing various particles in space. The satellite data can be analysed with the help of machine learning and artificial intelligence. Satellite data deliver the signal for information about the surface and surrounding changes in a location on the Earth. The satellite image quality of the target surface depends on many factors, including atmospheric circumstances, the direction of lighting source, scattering of the target and path view of the surface arena. All performance of different observatory technologies depends on whether the data is gathering through a passive or an active remote sensing method. The limitation of satellite images is their very low spatial a temporal resolution, making it challenging to use them for many practical applications. This research proposes to review the literature to critically analyse existing approaches to improve the resolution of satellite images. A novel technique will be developed and evaluated based on the fusion of satellite imagery data collection from various satellites to improve a target surface's spatial and temporal resolution.