# Assessment Analysis of Flood Susceptibility in Tropical Desert Area: A Case Study of Yemen
## 2 Methods and Data
### Data Pre-Processing and Processing  
Sentinel-1 (GRD and IW) data for 12 April 2021 (before the flood) and 6 May 2021 (after the flood) for Tarim City were acquired to identify and detect flood locations in the study area. The Sentinel Application Platform (SNAP 7.0) was used to manipulate radar data [66] and used the interferogram creation technique to apply pre- and post-flood data [38]. In addition to threshold data collected during the flood (Table 1). First of all, the data were clipped as the study area using the SNAP application, and their orbit files were successfully updated, followed by calibration to optimize extracted data. In most cases, raw satellite data contains speckle. As a result, they were smoothed using the SNAP speckle filtering tool. The pixel values in SAR imaging can be related to the scene's radar backscatter; calibration transforms the pixel values from the sensor's digital values into backscatter coefficient values, which are effectively calibrated backscatter coefficient values [66]. The purpose of speckle filtering is to reduce image noise and provide higher-quality imagery. All of the preprocessing steps are detailed below: \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dates** & **Product Type** & **Sensor Mode** & **Platform** & **Path** \\ \hline
12 April 2021 & Ground range & Interferometry & & \\
6 May 2021 & detected (GRD) & Wide swath (IW) & S1A & Ascending \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Technical attributes of Sentinel-1 data used for this work. (i) Apply orbit file: Orbit state vectors, which are included in the metadata of SAR results, are frequently inaccurate. The precise orbits of satellites are computed over several days and are available days to weeks after the product is created. The SNAP application of a precise orbit allows for the automatic download and update of the orbit state vectors for each SAR scene in its product metadata, delivering exact satellite location and velocity information [67]. (ii) Calibration: The process of converting digital pixel data to radio-metrically calibrated SAR backscatter is known as calibration. The calibration applies a constant offset and a range-dependent gain, including the absolute calibration constant, and reverses the scaling factor used during level-1 product development. (iii) Terrain correction: Terrain correction is the use of a digital elevation model to correct the location of each pixel to rectify geometric distortions induced by topography, such as foreshortening and shadows [67]. Distances can be altered in SAR images due to topographical changes and the tilt of the satellite sensor. Image data that are not in the nadir location of the sensor will be distorted. Terrain adjustments are meant to compensate for these distortions, bringing the geometric representation of the image as close to the real environment as possible (SNAP Toolbox) [68]. SAR geometry effects such as foreshortening, layover, and shadows may all be corrected with terrain correction [69]. (iv) Creating dB bands and stacking both data. In this step, a logarithmic transformation is used to convert the unitless backscatter coefficient to dB [68] Equation [69]:  
\[\beta^{\circ}db=10*\log_{10}\left(\beta^{\circ}\right) \tag{2}\]  
where \(\beta^{\circ}\) is the digital number value of the image and \(\beta^{\circ}\) db is the backscattered value in dB. To extract the maximum amount of information, a dB band was generated for both images. The data were then layered for further processing in ArcGIS. The free satellite data of Sentinel-1 were employed to detect the flooded areas. For the same place, two images on different dates were used, and the images represent the area before and after the flood occurrence; this method depends on the unique SAR interaction nature with water surface and flooded vegetation compared with the other features. Geometric distortions because of terrain effects of the study area are not considered in GRD imagery provided by ESA.