## 2 Materials and Methods  
### Location and Data  
A radar image is generated from the reflection of active microwaves emitted from the radar vehicle (airplane or satellite). The transmitter in a radar system is an antenna array consisting of a waveguide and emitting a very narrow beam of microwave waves. The radar sensor moves along a trajectory, and the area highlighted by the radar moves (known as the footprint) along the surface being swept to form an image. A digital radar image consists of many pixel dots representing the backscatter or backscatter of a point on the surface. Figure 1 shows an example of a SAR image from 2 January 2020 that is free from cloud cover with the bright dots showing high backscattering while the dark dots represent low backscattering, while Figure 2 is the optical image from the same date showing cloud cover. The radar system generally has a wavelength undisturbed by interference from water particles and water vapor in the air (clouds and rain). Because they are not dependent on illumination (irradiation) from the sun or other sources, the radar system can function day and night and in all weather. Synthetic Aperture Radar (SAR) works by detecting the phase-change of reflected signal caused by the movement of the platform to obtain the surface image with good resolution (i.e., visually discernible). The SAR system is generally divided into two wavelengths, namely short (C-band and X-band) and long (L-band and P-band) waves. Early SAR satellite systems use a single platform such as Radarsat. Currently, the most commonly used are satellite constellation systems such as TerraSAR-X and TanDEM-X pair, four-satellites Cosmo-SkyMed in X-band, three-satellites Radarsat Constellation Mission, and Sentinel 1 satellite pair, which give shorter revisit time and higher temporal resolution [20; 41; 42; 43]. Figure 3 shows the backscatter mechanism of shortwave radar (illustrated with black arrows) and long (illustrated arrows in blue) on various surfaces under normal conditions and during a flood. On the grass surface, there are surface reflections at both wavelengths due to the relative roughness of the surface. For short waves, the scattering is due to the thickness of the grass, while long waves can penetrate deeper [44]. When a flood occurs, specular reflection occurs in both types of waves. On objects in the form of trees or forests, the reflection is dominated by the scattering volume. For short waves, the scattering comes from the canopy (leaves) of the trees, while the longwave scattering by the branches and other tree structures is added by a double-bounce, which hits the ground surface and then the tree trunk or vice versa. When there is a flood, the double reflection will get more significant due to the specular reflection on the water surface (shown as a thick line of the direction of the reflection). In urban areas, the reflection on both waves is dominated by multiple reflections, although the surface will appear coarser on short waves. When there is a flood, this double reflection will be significantly strengthened due to the specular reflection on the water surface (shown as a thick line of the direction of the reflection). Figure 1: SAR image of Jakarta on 2 January 2020. Figure 2: An optical image from Landsat-8 of Jakarta on 2 January 2020. In this study, the flood data collected came from Sentinel-1a remote sensing satellite. The data are downloaded through Google Earth Engine by the Copernicus catalog and selecting available dates from the archive. The selected mode is Interferometric Wide Swath (IW) with 250 km swath and 5 m \(\times\) 20 m spatial resolution [45]. For our model, the pixel resolution is preset at 10 m \(\times\) 10 m. Remote sensing data combined with GIS data are integrated to create a flood hazard and potential map. Based on information obtained from remote sensing and GIS databases, the ML method can be applied for spatial modeling of flood vulnerability.