On November 24, 2022 the city of Jeddah (Saadia Ariba) experienced a devastating flood killing at least 2 people and leaving many stranded. The southern part of Jeddah recorded 7.04 inches of rainfall, setting a new 24-hour record.

For this project, remote sensing was used to perform an in-depth analysis of the characteristics before and after the flood in the southern part of Jeddah. Satellite data was collected from the ESA (European Space Agency) to perform this analysis. In the following sections, we will take you through the analysis process in detail and provide the corresponding results observed.

To learn more details about this devastating flood, you can visit Floodlist.com using the following link: Floodlist.com - Saudi Arabia Flood Jeddah - Nov 2022

What is a Subset? It's a download of a a single Sentinel-1 file that provides data for a large portion of an area we want to look at. We create a subset, or smaller area, in order to focus in on the area of interest.

Multilooking is a filtering method that reduces speckle and decreases the spatial resolution. Filtering is used to remove noise and “smooth” out the SAR image. This step gives a wide degree of freedom to the user by allowing the user to adjust both filtering types and filtering power to their study area. When decreasing the resolution, pixel values are averaged together based on the number of range and azimuth looks; this removes high-frequency noise caused by speckle and creates square pixels. However, multilooking comes at the expense of resolution and feature edges.

Radiometric calibration, also known as radiometric correction, is important to successfully convert raw digital image data from satellite or aerial sensors to a common physical scale based on known reflectance measurements taken from objects on the ground's surface.

Terrain Correction corrects for geometric distortion that lead to geometric errors. Distortions can occur by side looking imaging rather than nadir imaging, and can be compounded by rugged terrain. Terrain correction moves pixels in their proper spatcial relationship.

Co-registration is the process of aligning the SAR images in slant-range geometry so that a pixel from one image matches up with the pixel of the other. Co-registration corrects for relative translation shift, as well as rotational and scale differences between images. This is done by keeping the older image as the reference and adjusting the pixels in the younger image by first performing coarse (pixel level) registration, followed by fine (sub-pixel [less than 1/8 of a pixel] level) registration.

The two images below are of the stack in SNAP. The image on the left is of the southern portion of Jeddah while the one on the right is of central Jeddah. These images are of both the 11/17 and the 11//29 stacked on top of each other. The red pixels indicate remain flood water left from the 11/24 flood.