# A Tool for Pre-Operational Daily Mapping of Floods and Permanent Water Using Sentinel-1 Data
## 2 Data
### Ancillary Data  
In order to perform the geocoding of the S1 GRD data, the 1-arcsecond (30 m) Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is used by AUTOWADE. Recently, new DEMs have been proposed such as the corrected SRTM [32] and the Copernicus 30-m global DEM, referred to as GLO-30. The latter, open to the public since November 2020, will be tested in the following releases of AUTOWADE. A mosaicking of the SRTM tiles covering Italy has been performed once and for all during the design phase of the tool and, from this mosaic, a slope map has been extracted to be used in the generation of the exclusion mask (set of pixels where water mapping is unfeasible).  
Another static layer is used by AUTOWADE in the generation of the exclusion mask, namely a land cover map produced by rasterizing the CORINE Land Cover (CLC) level 3 vector file at a spatial resolution of 20 \(\times\) 20 m\({}^{2}\) on the WGS84 reference ellipsoid (projection LATLON-WGS84). The most recent version (2018) of the CLC data, released in the frame of the Copernicus program and available through the catalog of the Copernicus Land Monitoring Service (Pan-European component), has been chosen. The land cover map also represents the master product used to generate the AUTOWADE-derived product and consists of 66,000 \(\times\) 58,500 pixels.  
AUTOWADE also uses a reference water mask. It is a static layer derived from the water and wetness (WAW) product available through the Copernicus Land Monitoring Service (Pan-European component--high-resolution layers). WAW is a thematic map that identifies permanent water, temporary water, permanent wetness, and temporary wetness. Only the pixels labelled as permanent water have been included in the reference water mask. For this class, the accuracy is expected to exceed 85% [33].  
Not only static layers, but also constantly updated maps are included among the ancillary data. These maps are produced by another processor, described in [34], which works on Sentinel-2 (S2) level-2A (L2A) data. In particular, a map of Normalized Difference Vegetation Index (\(NDVI\)) and a map of snow cover, both projected on the CLC reference  
Figure 1: Portions of the Sentinel-1 orbits covering the Italian territory. Panel (**a**): descending orbits (morning overpasses); panel (**b**): ascending orbits (afternoon overpasses).  
grid, are used to search for flooded vegetation and to complement the exclusion mask. For each of the 66,000 \(\times\) 58,500 pixels, these data are derived from the most recent S2 observation performed under cloud-free conditions. If the most recent S2 observation is older than one month, \(NDVI\) and snow cover data are not used, and flooded vegetation is not searched for. An example of \(NDVI\) map is shown in Figure 2, while a summary of the main characteristic of the ancillary layers is reported in Table 1. From Table 1, it can be noted that the spatial resolution of the CLC data is coarser than that of S1 and the other data. However, since AUTOWADE makes use of the CLC only to mask urban areas, the impact of the use of this relatively low-resolution data on the accuracy of the maps of floodwater/permanent water is expected to be quite small.