# Detection of Surface Water and Floods with Multispectral Satellites
## 4 Discussion  
In this work, an up-to-date review of remote sensing applications for water mapping was carried out focusing on satellite remote sensing programs that offer free-of-charge optical data. Several documents were carefully screened, and the relevant literature on flood mapping using multispectral imagery was included. To the authors' knowledge, there is no similar scientific study focusing specifically on optical satellite imagery for flood mapping that also provides a review of spectral index performances in different flooded land cover classes. The most recent literature, in fact, has either focused on reviewing the use of optical data in the context of land cover classification [69] or on the application of radar data for inundation extent mapping [117; 118]. Others have focused on global remote sensing satellites for land monitoring [70], Earth observations [34], and flood management [119]. The proposed review allowed us to summarize the actual knowledge on the use of multispectral remote sensing for flood and water body delineation and to directly compare the potential and limitations of different spectral indices adopted in water segmentation. First, we analyzed the literature on flooded area and wetland inundation mapping with Landsat, MODIS, and Sentinel-2 satellite sensors in the period from 2002 to 2021. As expected, images from the Landsat program were the most used, since it constitutes the longest-running land monitoring program, offering a large dataset and allowing analyses to be conducted over several years. In addition, it offers medium-high resolution images (30-100 m spatial resolution), especially after the launch of the Landsat 7-ETM+ sensor. However, the revisit time is 16 days, thus limiting the possibility to have a frame of the flooded area at the exact moment of the event. Joining the Landsat 8 in orbit, the recent launch of the Landsat 9 satellite ensures a revisit coverage and data collection every 8 days. Sentinel-2 also belongs to the medium-high resolution class of satellite sensors (10 to 60 m spatial resolution) and has the advantage of having a 5-day revisit time; however, data are only available from 2015. Indeed, we found a relatively low number of studies that used Sentinel-2 images. Similarly, relevant studies that used data from the MODIS satellite were only found from 2008. Despite the coarse spatial resolution of the MODIS sensor (250 to 1000 m), it has the great advantage of a daily revisit time. Figure 6: Results of the performances of the MNDWI and NDWI in detecting land surface water, expressed in terms of overall accuracy (OA). The blue line represents the median value of the OA of each index, while red crosses represent outliers. An in-depth investigation of the water index method for flooded area mapping and water body delineation was carried out, from which it was possible to identify the most used multispectral indices and assess their performances. The performance metric considered for the analysis was the overall accuracy, while the selected spectral indices were the MNDWI, NDWI, NDVI, NDMI, AWEI\({}_{\text{nsh}}\), AWEI\({}_{\text{sh}}\), WRI, and MNDWI\({}_{7}\). The results showed that the best-performing index for flooded area mapping was the MNDWI, thanks to its ability to better recognize mixed pixels and turbid water (i.e., algae and vegetation). As regards surface water detection, both the MNDWI and NDWI showed good performances; however, few outliers were detected. These were mainly found in study areas in which shadows represented a major issue, influencing MNDWI accuracy, while turbidity problems affected NDWI performance [2; 68; 84]. In addition, issues were also related to the spatial resolution of the sensor used to map the water bodies, which sometimes may have a limited size that is not easily visible with the current low spatial resolution of sensors (e.g., [5]). Other sources of errors were also represented by snow presence in the study area [27; 120].