2026-07-23 –, Room 1.38 (Ground Floor, Turing)
Remote Sensing has proved to be an important tool in monitoring our earth's ecosystem. Satellite imaging is a vital part of Remote Sensing. Predominantly, Satellite Imaging of the earth has been done in the optical domain and optical Images serve the majority of purpose for earth monitoring. But, these satellites do not have all-weather acquisition capability and this lacuna is filled by the satellite sensors working in the Microwave domain of the Electromagnetic spectrum. Synthetic Aperture Radar(SAR) is an Imaging Radar that acquires images of a particular area on Earth in the microwave region of electro-magnetic spectrum. This workshop deals with the processing of SAR Images and how these images can be beneficial in a variety of geographical applications.
Intended Audience : The workshop will be aimed at the audience belonging to any level of education. It will introduce them to the wonderful class of SAR images and help them develop a clear perspective of various applications.
Post workshop, the audience will be :
i) Able to understand the acquisition of SAR imagery.
ii) Able to understand the types of datasets utilized in remote sensing
iii) Able to use the GDAL library to perform operations on images
iv) Able to efficiently process SAR imagery using Python
v) Able to draw a roadmap in order to utilize SAR imagery for various geographic applications
Outline
The workshop will be divided into the following sub-sessions :
Sub-Session-1: Introduction to Microwave Remote Sensing (15 minutes) - This part will discuss the foundations of Microwave Remote Sensing. Theoretical aspects regarding the acquisition of images, the formation of images encompassing the generation of complex images and ground range detected images will be discussed.
Sub-Session-2: Pythonic Way to SAR Image Processing (75 minutes): This part will focus on achieving the following Key points:
1) Basic utilization of GDAL, Numpy and Matplotlib Libraries for opening and visualizing Images(25 minutes)
2) Codes will be developed separately for calibration for each SAR sensor(esp. Sentinel-1, Radarsat-2) from scratch.(25 minutes)
3) Utilization of the codes developed in (2) for various applications such as Oceanography, Forestry, etc.(25 minutes)
Datasets: Free Imagery data sets of Sentinel-1 SAR will be utilized. In addition, Sample Data sets of Radarsat-2, RISAT- 1 which are freely downloadable will be utilized.The sample datasets will be provided. Sentinel-1 Free SAR Imagery is available at https://browser.dataspace.copernicus.eu/
Conduct of the workshop : The workshop will be conducted through the means of Jupyter Notebooks.
Shubham Sharma is a Senior Data Scientist with more than ten years of experience at the convergence of Remote Sensing, Image Processing, Computer Vision, and Deep Learning. He has been an active contributor to the open-source scientific computing ecosystem, engaging with communities through conferences such as SciPy and as a past speaker at PyCon. His work includes significant experience in Synthetic Aperture Radar (SAR) image processing, and he is deeply committed to advancing knowledge of satellite image analysis using Python within the open source community.