Imaging Floods and Glacier Geohazards with Remote Sensing

associated with the dynamics of the liquid and solid water of the Earth’s hydrosphere, such as and glacial processes, may pose signiﬁcant risks to populations, activities and properties. ﬂoods.

In the following paragraphs, this editorial paper provides an overview of the research articles composing the Special Issue (Table 1), via a summary of the remote sensing data and methods used and the initial scientific impact achieved in the first few months after publication of the last paper. The published Special Issue comprises 11 research articles. The pictorial word cloud in Figure 1 combines the thematic keywords used in their main metadata (namely, their titles, abstracts and Remote Sens. 2020, 12, 3874 3 of 5 keywords), while Table 1 summarizes the remote sensing data and methods used, and the areas of interest investigated in each article.
Liang and Liu 2020 [17] surge water height, land cover; National Map 3D Elevation Program DEM; NDWI, data fusion, daily inundation probability, weight of evidence 2017 inundations in Harris, Texas (USA) The published Special Issue comprises 11 research articles. The pictorial word cloud in Figure 1 combines the thematic keywords used in their main metadata (namely, their titles, abstracts and keywords), while Table 1 summarizes the remote sensing data and methods used, and the areas of interest investigated in each article. The cloud shows that among the most frequently used keywords, there are not only terms relating to the geophysical processes involved (e.g., surge, mass, deficit and storm) or the approaches employed for flood and glacier imaging (e.g., supervised classification and comparison) but also specific data types (e.g., digital elevation models), sensors and missions (e.g., Sentinel-1). The latter data, in particular, were exploited in more than one article (see Table 1) and reflect a higher-level trend that can be observed in the recent specialist literature in this field which increasingly exploits satellite Synthetic Aperture Radar (SAR) imagery. A significantly high number The cloud shows that among the most frequently used keywords, there are not only terms relating to the geophysical processes involved (e.g., surge, mass, deficit and storm) or the approaches employed for flood and glacier imaging (e.g., supervised classification and comparison) but also specific data types (e.g., digital elevation models), sensors and missions (e.g., Sentinel-1). The latter data, in particular, were exploited in more than one article (see Table 1) and reflect a higher-level trend that can be observed in the recent specialist literature in this field which increasingly exploits satellite Synthetic Aperture Radar (SAR) imagery. A significantly high number of articles also focused on image classifiers, probabilistic approaches and elevation and change detection methods.
Multi-sensor and multi-platform approaches were also quite common across the papers on specific events or sites, and so were studies focused on algorithm development and testing. Most contributions focused on flood events, hazard and risk, while only four on glacier monitoring.
MDPI's article metrics powered by TrendMD were exploited with the aim to gather a flavor of the visibility of the Special Issue across the journal readership in the first 6 months after the publication of the last paper. TrendMD uses technologies such as Google Analytics by Google Inc. to track the use of and interaction with webpages made by visitors (e.g., abstract and full-paper views and downloads). The metrics for the 11 articles of the Special Issue show that since the publication of the first article at the end of March 2019, the Special Issue received more than 15,500 views in total over the 20-month-long time span between March 2019 and November 2020. This reflected an average number of 100 views/month for each paper. A positive exception is represented by the boosted performance of the article by Uddin et al. 2019 [10], which attracted over 4400 views since its publication in July 2019 and as of mid-November 2020, i.e., approximately 260 views/month. The overall 64 citations in the indexed literature received as of mid-November 2020 also provide an indication of the good scientific impact that the Special Issue is building across the scientific community in the first few months after publication. A portion of these citations were made by articles published in MDPI open-access journals, including Remote Sensing, Sustainability, Water, Hydrology and Applied Sciences, while many others were received from articles in scientific journals of other publishers, focused on the fields of hydrology, remote sensing and environmental and Earth sciences. Looking at the scale of single articles, while generally, most of the papers of the Special Issue received 1 to 6 citations so far, two apparent positive outliers are the research articles by Benoudjit and Guida 2019 [8] and Uddin et al. 2019 [10], with outstanding achievements of 16 and 30 citations already attracted, respectively.
Overall, the body of literature collected in the Special Issue provides a good representation of the current state of the art and trends in this topical research field, showcasing remote sensing tools currently used for imaging, characterizing and modeling floods and glacier processes. A wide range of platforms, data sources, processing and analysis methods and models have been presented and discussed, with several cases studies distributed globally. The Special Issue, thus, contributes, together with other thematic volumes published in Remote Sensing, to the technical and scientific discussion on the use of remote sensing data in geology, geomorphology and hydrology.
Author Contributions: Conceptualization, F.C. and H.X.; formal analysis, F.C.; data curation, F.C.; visualization, F.C. and H.X.; writing-original draft preparation, F.C.; writing-review and editing, H.X. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.