Basics of SAR Remote Sensing and its Machine Learning Applications
Synthetic Aperture Radar | Deep Learning | Remote Sensing
In this story, we will talk about Radar Remote Sensing, Synthetic Aperture Radar and their applications with AI and Machine Learning.
SAR remote sensing is an modified version of radar remote sensing based on SAR principles to produce high resolution satellite imagery and interpret them to gain good results. While we talk more about SAR, let us also discuss on its pre-requisites on the fly.
Remote sensing is the methods and process of monitoring and detecting the physical characteristics of an area by measuring its reflected and emitted radiation at a distance. With the release of good number of satellites and the data availability, remote sensing field has been growing enormously. The importance of Remote Sensing has been recognised for monitoring, designing and managing better regulations in domains like agriculture, climate changes, urban planning, environmental monitoring etc. Advances in remote sensing science and associated technologies have made it possible to obtain valuable spatiotemporal information.
Each satellite uses different region of electromagnetic spectrum for remote sensing.
