Reply to Editor NHESS-2017-420 Dear Davide Notti and Co-Authors, Thank You Very Much for Submitting the Revised Version of Your
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Reply To Editor NHESS-2017-420 Dear Davide Notti and co-authors, thank you very much for submitting the revised version of your manuscript. I think all reviewer comments and your suggested changes to the manuscript have been implemented in a satisfactory manner. However, reading through the manuscript it becomes apparent that English writing needs further improvement. This concerns grammar, terminology and spelling. Please consider proof reading by a native speaker. R: The English writing is now revised by the America Journal Expert service. We add the certificate in the attached PDF Please harmonize writing and use of abbreviations (e.g. SfM, sfm; façades, facades) R: done, we used: SfM, facades, RPAS Please harmonize referencing to Figures (Fig. or Figure or Fig), and check the sequence of referencing to Figures. R: Done, we used (Fig. ) specific comments: L 397 Consider if 'Supervised Classification.' can be deleted. R: Removed L403 The last sentence is incomplete. R: Changed in “We obtained the worse results for the area flooded by the Chiosla and Oitana streams” L 465 ad -> as R: Corrected LL 500 - 502: how can infer an exponential decrease from two instances in time? please consider rephrasing. R: We rewrite “greatly decreases” instead of “exponential” L515 2 - 3 m. The upper limit of the legend is 2m. R: The upper limit of WD model is 2-4 m, we better specify it in the legend of figure 11. L526 units are missing R: Added the units (m) L534 purpose -> propose R: Done LL 577 - 579 This sentence is not clear, please rephrase. R: We rewrite as follow: “For example, the two Sentinel-1 satellites provided free images every six days all over Europe, while other satellites have quite high costs and the acquisition is often on-demand. Moreover, most of the time, the on-demand acquisitions are activated only when authorities activate an emergency procedure (e.g., the EMSR of the European Union or by civil protection). L 600 and 604 measures - > measurements R: Done Please check if Fig. 2 is still needed after including Fig. 13. R: We think that both figures are necessary because the flow charts, even similar, show different things: The first (Fig. 2) is the methodology used for this work, the second is a general methodological approach proposed for the readers. caption Fig 6: photo took -> photos taken R: Corrected caption Fig 7: 'allowed' can this be deleted? ... 'cut a:an erosion' Please check. R: Corrected caption Fig 8: 'map of flooded Chisola flooded area' Please check.# R: Changed in “map of areas flooded by Chisola stream” Figure 11: In the legend: River embankment ropture -> rupture; the GPS and SfM symbols cannot be seen on the map R: Corrected, we also improved the visibility of symbols EDITORIAL CERTIFICATE This document certifies that the manuscript listed below was edited for proper English language, grammar, punctuation, spelling, and overall style by one or more of the highly qualified native English speaking editors at American Journal Experts. Manuscript title: Low cost, multiscale and multi-sensor application for flooded areas mapping Authors: Daniele Giordan Date Issued: April 30, 2018 Certificate Verification Key: 565C-109C-52FC-74DD-39A3 This certificate may be verified at www.aje.com/certificate. This document certifies that the manuscript listed above was edited for proper English language, grammar, punctuation, spelling, and overall style by one or more of the highly qualified native English speaking editors at American Journal Experts. Neither the research content nor the authors' intentions were altered in any way during the editing process. Documents receiving this certification should be English-ready for publication; however, the author has the ability to accept or reject our suggestions and changes. To verify the final AJE edited version, please visit our verification page. If you have any questions or concerns about this edited document, please contact American Journal Experts at [email protected]. American Journal Experts provides a range of editing, translation and manuscript services for researchers and publishers around the world. Our top-quality PhD editors are all native English speakers from America's top universities. Our editors come from nearly every research field and possess the highest qualifications to edit research manuscripts written by non-native English speakers. For more information about our company, services and partner discounts, please visit www.aje.com. Low cost, multiscale and multi-sensor application for flooded areas mapping. Daniele Giordan1, Davide Notti1, Alfredo Villa2, Francesco Zucca3, Fabiana Calò4, Antonio Pepe4, Furio Dutto5, Paolo Pari6, Marco Baldo1, Paolo Allasia1 5 1National Research Council of Italy, Research Institute for Geo-Hydrological Protection (CNR-IRPI), Strada delle Cacce 73, Torino 10135., Italy; 2ALTEC S.p.A., Torino, 10146, Italy; 3Department of Earth and Environmental Science, University of Pavia, Via Ferrata 1, 27100 Pavia, Italy 4National Research Council of Italy, Institute for the Electromagnetic Sensing of the Environment (CNR-IREA), Via 10 Diocleziano 328, Napoli 80124, Italy; 5Civil protection Service of Torino, Grugliasco, 10095, Italy; 6Digisky S.r.l., Torino, 10146, Italy. Correspondence to: Davide Notti ([email protected]) Abstract 15 Flood mapping and estimation of the maximum water depth are essential elements for athe first damagesdamage evaluation, civil protection interventionsintervention planning and detection of areas where remedial are moreremediation is needed. In this work, we present and discuss a methodology for mapping and quantifying flood severity over plain areasfloodplains. The proposed methodology considers a multiscale and multi-sensormultisensor approach using free or low-cost data/sensors. We applied this method to the November 2016 Piemonte (NW Italy) flood. We first mapped the flooded areas at the basin 20 scale using free satellite data from low- to medium-high resolution usingfrom both the SAR (Sentinel-1, COSMO-Skymed) and multispectral sensors (MODIS, Sentinel-2). Using very- and ultra- high-resolution images from the low-cost aerial platform and Remotely Piloted Aerial System, we refined the flooded zone, and we detected the most damaged sector. The presented method considers both urbanized and not non-urbanized areas. Nadiral images have several limitations, in particular, in urbanized areas, where the use of terrestrial images solved this limitation. Very- and ultra-high -resolution images have 25 beenwere processed with Structure from Motion (SfM) for the realization of 3-D models. These data, combined with an available digital elevationterrain model, allowed us to obtain maps of the flooded area, maximum high water higharea, and damaged infrastructures. 1 Introduction Floods are among the natural disasters that cause significant damagesdamage and casualties (Barredo, 2007). 30 Mapping and modelling the areas affected by floods is a crucial task to: i) identify the most critical areas for civil protection actions; ii) evaluate damages,damage; and iii) and do correctperform appropriate urban planning. (Amadio et al., 2016). In order to makeTo perform a precise quantification of damages, adamage, detailed mapping of flooded areas is required, with and a reasonable estimation of the water level and flow velocity are required (Arrighi et al., 2013; Luino et al., 2009; Merz et al., 2010; Kreibich, 2009). Advances in remote sensing and technology have introduced the possibility, in the last few years, 35 of havinggenerating rapid maps and models during or littlewithin a short time after a flood event (e.g., Copernicus Emergency Management Service (© European Union, 2012-2017)). With satellite remote sensing data, it is possible to map flood effects over vast areas at different spatial and temporal resolutionresolutions using multispectral (Brakenridge, et al., 2006; Gianinetto et al.,2006; Nigro et al., 2014; Wang et al., 2012; Yan et al., 2015; Rahman and Di, 2017) or Synthetic Aperture Radar (SAR) images (Boni et al., 2016; Mason et al., 2014; Schumann et al., 2015; Refice et al., 2014; Pulvirenti et al., 2011; Clement et 40 al., 2017; Brivio et al., 2002). A good description of the main methodologies that are used to map floodfloods with satellite data has been published by Fayne et al.,. (2017). Moreover, the increasing availability of free-of-charge satellite data with global coverage (e.g., Sentinel-1 and -2 from ESA, and Landsat and MODIS satellites from NASA) makes possible analyses of flooded areas with low-cost solutions possible. Flood mapping and damagesdamage assessment is also an important issue for European Communities authorities that support projects like, such as the Copernicus Emergency Management Service 45 mapping (EMSR) and the European Flood Awareness System (EFAS), which manage the activation procedure to acquire satellite data over the areas affected by a natural hazard. De Moel et al.,. (2009) and Paprotny atet al.,. (2017) described further details about different experiences inof flood mapping in Europe. In urban areas, remote sensing data are often less efficient infor the detection of flooded areas, especially if images acquired during the maximum of the inundation are not available. A partial solution could be the use of a Remotely Piloted Aerial 50 Systems (RPAS) (Perks et al., 2016; Feng et al., 2015), thatwhich are usually able to acquire ultra-high -resolution images over small areas. The quantificationQuantification of the maximum water level caused by the inundation