This page has only limited features, please log in for full access.
The assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing-based procedure for quickly updating the assessment of the population exposed to natural hazards. A relationship between satellite nightlights intensity and urbanization density from global available cartography is first assessed when all data are available. This is used to extrapolate urbanization data at different time steps, updating exposure each time new nightlights intensity maps are available. To test the reliability of the proposed methodology, the number of people exposed to riverine flood in Italy is assessed, deriving a probabilistic relationship between DMSP nightlights intensity and urbanization density from the GUF database for the year 2011. People exposed to riverine flood are assessed crossing the population distributed on the derived urbanization density with flood hazard zones provided by ISPRA. The validation against reliable exposures derived from ISTAT data shows good agreement. The possibility to update exposure maps with a higher refresh rate makes this approach particularly suitable for applications in developing countries, where urbanization and population densities may change at a sub-yearly time scale.
Giorgio Boni; Silvia De Angeli; Angela Taramasso; Giorgio Roth. Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards. Remote Sensing 2020, 12, 3943 .
AMA StyleGiorgio Boni, Silvia De Angeli, Angela Taramasso, Giorgio Roth. Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards. Remote Sensing. 2020; 12 (23):3943.
Chicago/Turabian StyleGiorgio Boni; Silvia De Angeli; Angela Taramasso; Giorgio Roth. 2020. "Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards." Remote Sensing 12, no. 23: 3943.
Along the Mediterranean coastlines, intense and localized rainfall events are responsible for numerous casualties and several million euros of damage every year. Numerical forecasts of such events are rarely skillful, because they lack information in their initial and boundary conditions at the relevant spatio-temporal scales, namely O(km) and O(h). In this context, the tropospheric delay observations (strongly related to the vertically integrated water vapor content) of the future geosynchronous Hydroterra satellite could provide valuable information at a high spatio-temporal resolution. In this work, Observing System Simulation Experiments (OSSEs) are performed to assess the impact of assimilating this new observation in a cloud-resolving meteorological model, at different grid spacing and temporal frequencies, and with respect to other existent observations. It is found that assimilating the Hydroterra observations at 2.5 km spacing every 3 or 6 h has the largest positive impact on the forecast of the event under study. In particular, a better spatial localization and extent of the heavy rainfall area is achieved and a realistic surface wind structure, which is a crucial element in the forecast of such heavy rainfall events, is modeled.
Martina Lagasio; Agostino Meroni; Giorgio Boni; Luca Pulvirenti; Andrea Monti-Guarnieri; Roger Haagmans; Stephen Hobbs; Antonio Parodi. Meteorological OSSEs for New Zenith Total Delay Observations: Impact Assessment for the Hydroterra Geosynchronous Satellite on the October 2019 Genoa Event. Remote Sensing 2020, 12, 3787 .
AMA StyleMartina Lagasio, Agostino Meroni, Giorgio Boni, Luca Pulvirenti, Andrea Monti-Guarnieri, Roger Haagmans, Stephen Hobbs, Antonio Parodi. Meteorological OSSEs for New Zenith Total Delay Observations: Impact Assessment for the Hydroterra Geosynchronous Satellite on the October 2019 Genoa Event. Remote Sensing. 2020; 12 (22):3787.
Chicago/Turabian StyleMartina Lagasio; Agostino Meroni; Giorgio Boni; Luca Pulvirenti; Andrea Monti-Guarnieri; Roger Haagmans; Stephen Hobbs; Antonio Parodi. 2020. "Meteorological OSSEs for New Zenith Total Delay Observations: Impact Assessment for the Hydroterra Geosynchronous Satellite on the October 2019 Genoa Event." Remote Sensing 12, no. 22: 3787.
The assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing based procedure for quick updating the assessment of the population exposed to natural hazards. A relationship between satellite nightlights intensity and urbanization density from global available cartography is first assessed when all data are available. This can be used to extrapolate urbanization data at different time steps, updating exposure each time new nightlights intensity maps are available. As reliability test for the proposed methodology, the number of people exposed to riverine flood in Italy is assessed, deriving a probabilistic relationship between DMSP nightlights intensity and urbanization density from GUF database for the year 2011. People exposed to riverine flood are assessed crossing the population distributed on the derived urbanization density with flood hazard zones provided by ISPRA. The validation on reliable exposures derived from ISTAT data shows good agreement. The possibility to update exposure maps with higher refresh rate makes this approach particularly suitable for applications in developing countries, where exposure may change at sub-yearly scale.
Giorgio Boni; Silvia De Angeli; Angela Celeste Taramasso; Giorgio Roth. Remote Sensing Based Methodology for the Quick Update of Population Exposed to Natural Hazards. 2020, 1 .
AMA StyleGiorgio Boni, Silvia De Angeli, Angela Celeste Taramasso, Giorgio Roth. Remote Sensing Based Methodology for the Quick Update of Population Exposed to Natural Hazards. . 2020; ():1.
Chicago/Turabian StyleGiorgio Boni; Silvia De Angeli; Angela Celeste Taramasso; Giorgio Roth. 2020. "Remote Sensing Based Methodology for the Quick Update of Population Exposed to Natural Hazards." , no. : 1.
On 14 August 2018, Morandi Bridge in Genoa, Italy, collapsed to the ground that was 40 m below. This tragedy killed 43 people. Preliminary investigations indicated poor design, questionable building practices, and insufficient maintenance—or a combination of these factors—as a possible cause of the collapse. However, around the collapse time, a thunderstorm associated with strong winds, lightning, and rain also developed over the city. While it is unclear if this thunderstorm played a role in the collapse, the present study examines the weather conditions before and during the bridge collapse. The study particularly focuses on the analysis of a downburst that was observed around the collapse time and a few kilometers away from the bridge. Direct and remote sensing measurements are used to describe the evolution of the thunderstorm during its approached from the sea to the city. The Doppler lidar measurements allowed the reconstruction of the gust front shape and the evaluation of its displacement velocity of 6.6 m s−1 towards the lidar. The Weather Research and Forecasting simulations highlighted that it is still challenging to forecast localized thunderstorms with operational setups. The study has shown that assimilation of radar reflectivity improves the timing and reconstruction of the gust front observed by local measurements.
Massimiliano Burlando; Djordje Romanic; Giorgio Boni; Martina Lagasio; Antonio Parodi. Investigation of the Weather Conditions During the Collapse of the Morandi Bridge in Genoa on 14 August 2018 Using Field Observations and WRF Model. Atmosphere 2020, 11, 724 .
AMA StyleMassimiliano Burlando, Djordje Romanic, Giorgio Boni, Martina Lagasio, Antonio Parodi. Investigation of the Weather Conditions During the Collapse of the Morandi Bridge in Genoa on 14 August 2018 Using Field Observations and WRF Model. Atmosphere. 2020; 11 (7):724.
Chicago/Turabian StyleMassimiliano Burlando; Djordje Romanic; Giorgio Boni; Martina Lagasio; Antonio Parodi. 2020. "Investigation of the Weather Conditions During the Collapse of the Morandi Bridge in Genoa on 14 August 2018 Using Field Observations and WRF Model." Atmosphere 11, no. 7: 724.
Risk exposure adjournment in flood prone areas is usually limited by the unavailability of frequently updated information about urbanization and census. This limitation is produced mainly by the complexity of the long process that lead to thematic maps compliant with common product requirements.
Therefore, the mapping of exposed elements and population does not fully exploit the potential high refresh rate typical of remote sensing. This aspect may be particularly important in developing countries, where exposure may change at sub-yearly scale.
This work explores the potential of the combination of the high refresh rate of satellite night-time light products with the high precision of urban maps and census information. Target is the evaluation of the population exposure to the flood risk in urban areas.
The idea is to calibrate nightlight vs. urban density/population relations where contemporary estimations of both variables are available. These, combined with flood hazard maps, allows the estimation of the flood risk. Results will be validated using independent estimates of the population exposed to the flood risk in the same area.
Moreover, time series of nightlight products will be used to estimate the same variables at different times, demonstrating the possibility of rapid updates.
The work is based upon DMSP night-time light series, global urban footprint (GUF) maps by the German AeroSpace Center (DLR) and census data from the Italian institute of statistics (ISTAT). The independent data for the population exposed to risk are provided by the Italian Environmental Protection Agency (ISPRA).
Giorgio Boni; Angela Celeste Taramasso; Giorgio Roth. Estimation of flood risk exposure with cross fertilization between multi-platform remote sensing and census information. 2020, 1 .
AMA StyleGiorgio Boni, Angela Celeste Taramasso, Giorgio Roth. Estimation of flood risk exposure with cross fertilization between multi-platform remote sensing and census information. . 2020; ():1.
Chicago/Turabian StyleGiorgio Boni; Angela Celeste Taramasso; Giorgio Roth. 2020. "Estimation of flood risk exposure with cross fertilization between multi-platform remote sensing and census information." , no. : 1.
On 14 August 2018, Morandi Bridge in Genoa, Italy, collapsed sending vehicles and tons of rubble to the ground about 40 m below and killing 43 people. Preliminary investigations indicated poor design, questionable building practices and insufficient maintenance or a combination of these factors as a possible cause of collapse. However, at the time of collapse, a thunderstorm associated with strong winds, lightning and rain was developed over the city. While it is still not clear whether or not it played a role in this disaster, the present paper documents the weather conditions during the collapse and analyzes in detail a downburst that occurred at the time of the collapse a few kilometers from the bridge. The thunderstorm is analyzed using direct and remote measurements in an attempt to describe the evolution of the cumulonimbus cloud as it approached the coast from the sea. The detected downburst is investigated using a lidar scanner and the anemometric network in the Port of Genoa. The paper shows that the unique lidar measurements enabled a partial reconstruction of the gust front shape and displacement velocity. The Weather Research and Forecasting (WRF) simulations, carried out with three different forcing conditions, forecasted the cumuliform convection at larger scales but did not accurately replicate the downburst signature at the surface that was measured by radar, lidar, and anemometers. This result demonstrates that the localized wind conditions during the collapse time could not be operationally forecasted.
Massimiliano Burlando; Djordje Romanic; Giorgio Boni; Martina Lagasio; Antonio Parodi. Investigation of the weather conditions during the collapse of the Morandi Bridge in Genoa on 14 August 2018. 2019, 2019, 1 -42.
AMA StyleMassimiliano Burlando, Djordje Romanic, Giorgio Boni, Martina Lagasio, Antonio Parodi. Investigation of the weather conditions during the collapse of the Morandi Bridge in Genoa on 14 August 2018. . 2019; 2019 ():1-42.
Chicago/Turabian StyleMassimiliano Burlando; Djordje Romanic; Giorgio Boni; Martina Lagasio; Antonio Parodi. 2019. "Investigation of the weather conditions during the collapse of the Morandi Bridge in Genoa on 14 August 2018." 2019, no. : 1-42.
The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied—a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.
Martina Lagasio; Antonio Parodi; Luca Pulvirenti; Agostino N. Meroni; Giorgio Boni; Nazzareno Pierdicca; Frank S. Marzano; Lorenzo Luini; Giovanna Venuti; Eugenio Realini; Andrea Gatti; Giulio Tagliaferro; Stefano Barindelli; Andrea Monti Guarnieri; Klodiana Goga; Olivier Terzo; Alessio Rucci; Emanuele Passera; Dieter Kranzlmueller; Bjorn Rommen. A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast. Remote Sensing 2019, 11, 2387 .
AMA StyleMartina Lagasio, Antonio Parodi, Luca Pulvirenti, Agostino N. Meroni, Giorgio Boni, Nazzareno Pierdicca, Frank S. Marzano, Lorenzo Luini, Giovanna Venuti, Eugenio Realini, Andrea Gatti, Giulio Tagliaferro, Stefano Barindelli, Andrea Monti Guarnieri, Klodiana Goga, Olivier Terzo, Alessio Rucci, Emanuele Passera, Dieter Kranzlmueller, Bjorn Rommen. A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast. Remote Sensing. 2019; 11 (20):2387.
Chicago/Turabian StyleMartina Lagasio; Antonio Parodi; Luca Pulvirenti; Agostino N. Meroni; Giorgio Boni; Nazzareno Pierdicca; Frank S. Marzano; Lorenzo Luini; Giovanna Venuti; Eugenio Realini; Andrea Gatti; Giulio Tagliaferro; Stefano Barindelli; Andrea Monti Guarnieri; Klodiana Goga; Olivier Terzo; Alessio Rucci; Emanuele Passera; Dieter Kranzlmueller; Bjorn Rommen. 2019. "A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast." Remote Sensing 11, no. 20: 2387.
The next generation of synthetic aperture radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤1 km) and temporal (≤12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications, and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture–data assimilation (SM-DA) experiment was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products, characterized by diverse spatio-temporal resolutions. The experiment was also designed to understand if GEO SAR-like SM maps could provide an added value with respect to SM products retrieved from SAR images acquired from satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems provide a valuable contribution for hydrological applications, especially if the possibility to generate many sub-daily observations is sacrificed in favor of higher spatial resolution. In the experiment, it was found that the assimilation of two GEO SAR-like observations a day, with a spatial resolution of 100 m, maximized the performances of the hydrological predictions, for both streamflow and SM state forecasts. Such improvements of the model performances were found to be 45% higher than the ones obtained by assimilating POLAR SAR-like SM maps.
Luca Cenci; Luca Pulvirenti; Giorgio Boni; Nazzareno Pierdicca. Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring. Remote Sensing 2018, 10, 1950 .
AMA StyleLuca Cenci, Luca Pulvirenti, Giorgio Boni, Nazzareno Pierdicca. Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring. Remote Sensing. 2018; 10 (12):1950.
Chicago/Turabian StyleLuca Cenci; Luca Pulvirenti; Giorgio Boni; Nazzareno Pierdicca. 2018. "Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring." Remote Sensing 10, no. 12: 1950.
GeoSTARe is a proposed GEOsynchronous satellite mission designed to carry aboard a Synthetic Aperture Radar (GEOSAR) payload, which can provide radar images with unprecedented temporal resolution. The research activity described in this paper aimed at investigating the potentialities of such system for soil moisture (SM) monitoring finalized to hydrological applications. The objective was defining the GEOSAR requirements, in term of spatio-temporal resolution, for SM mapping. GEOSAR is capable to produce images with different sub-daily temporal resolution, with associated spatial resolution, according to the length of the synthetic antenna focused on ground. To this aim, three GEOSAR-derived SM products, characterized by different spatio-temporal resolutions (matching the expected performances of GEOSAR), were simulated. Then, these products were used in a synthetic hydrological SM data assimilation experiment to evaluate their impact on model discharge predictions. Results showed that, for such system, the best performances were obtained when the highest spatial resolution was used.
Luca Cenci; Giorgio Boni; Luca Pulvirenti; Flavio Pignone; Alessandro Masoero; Valerio Basso; Simone Gabellani; Nazzareno Pierdicca. Spatio-Temporal Requirements of a Geosynchronous SAR Soil Moisture Product for Hydrological Applications. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium 2018, 5517 -5520.
AMA StyleLuca Cenci, Giorgio Boni, Luca Pulvirenti, Flavio Pignone, Alessandro Masoero, Valerio Basso, Simone Gabellani, Nazzareno Pierdicca. Spatio-Temporal Requirements of a Geosynchronous SAR Soil Moisture Product for Hydrological Applications. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. 2018; ():5517-5520.
Chicago/Turabian StyleLuca Cenci; Giorgio Boni; Luca Pulvirenti; Flavio Pignone; Alessandro Masoero; Valerio Basso; Simone Gabellani; Nazzareno Pierdicca. 2018. "Spatio-Temporal Requirements of a Geosynchronous SAR Soil Moisture Product for Hydrological Applications." IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium , no. : 5517-5520.
This paper presents MULESME, a software designed for the systematic mapping of surface soil moisture using Sentinel-1 SAR data. MULESME implements a multi-temporal algorithm that uses time series of Sentinel-1 data and ancillary data, such as a plant water content map, as inputs. A secondary software module generates the plant water content map from optical data provided by Landsat-8, or Sentinel-2, or MODIS. Each output of MULESME includes another map showing the level of uncertainty of the soil moisture estimates. MULESME was tested by using both synthetic and actual data. The results of the tests showed that root mean square error is in the range between 0.03 m3/m3 (synthetic data) and 0.06 m3/m3 (actual data) for bare soil. The accuracy decreases in the presence of vegetation (root mean square in the range 0.08–0.12 m3/m3), as expected.
Luca Pulvirenti; Giuseppe Squicciarino; Luca Cenci; Giorgio Boni; Nazzareno Pierdicca; Marco Chini; Cosimo Versace; Paolo Campanella. A surface soil moisture mapping service at national (Italian) scale based on Sentinel-1 data. Environmental Modelling & Software 2018, 102, 13 -28.
AMA StyleLuca Pulvirenti, Giuseppe Squicciarino, Luca Cenci, Giorgio Boni, Nazzareno Pierdicca, Marco Chini, Cosimo Versace, Paolo Campanella. A surface soil moisture mapping service at national (Italian) scale based on Sentinel-1 data. Environmental Modelling & Software. 2018; 102 ():13-28.
Chicago/Turabian StyleLuca Pulvirenti; Giuseppe Squicciarino; Luca Cenci; Giorgio Boni; Nazzareno Pierdicca; Marco Chini; Cosimo Versace; Paolo Campanella. 2018. "A surface soil moisture mapping service at national (Italian) scale based on Sentinel-1 data." Environmental Modelling & Software 102, no. : 13-28.
The assimilation of satellite-derived soil moisture estimates (soil moisture–data assimilation, SM–DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM–DA in recent years (e.g. the Advanced SCATterometer – ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM–DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014–February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM–DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM–DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further research activities, we believe this research is timely in order to enhance our understanding of the potential contribution of the S1 data within the SM–DA framework for flash flood risk mitigation.
Luca Cenci; Luca Pulvirenti; Giorgio Boni; Marco Chini; Patrick Matgen; Simone Gabellani; Giuseppe Squicciarino; Nazzareno Pierdicca. An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation. Advances in Geosciences 2017, 44, 89 -100.
AMA StyleLuca Cenci, Luca Pulvirenti, Giorgio Boni, Marco Chini, Patrick Matgen, Simone Gabellani, Giuseppe Squicciarino, Nazzareno Pierdicca. An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation. Advances in Geosciences. 2017; 44 ():89-100.
Chicago/Turabian StyleLuca Cenci; Luca Pulvirenti; Giorgio Boni; Marco Chini; Patrick Matgen; Simone Gabellani; Giuseppe Squicciarino; Nazzareno Pierdicca. 2017. "An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation." Advances in Geosciences 44, no. : 89-100.
The objective of this research was to develop a method for water level retrieval in natural and artificial lakes. It was thought to be applied for monitoring purposes and flood control applications, especially in data-scarce environments. The method is based on a combined GIS, remote sensing and statistical modeling approach. It was tested on both optical (Landsat 8) and SAR (Cosmo-SkyMed®) data. The topographic information, required by the method, were obtained from freely available digital elevation models (SRTM and ASTER) to compare their performances. The Place Moulin Lake, an Alpine reservoir, was selected as study area since it represents a very challenging case study for developing the proposed methodology. The results showed that: i) the method provided reasonably accurate results when the degree of filling of the reservoir was high. ii) The accuracy of the results strongly relied on the accuracy of the topographic information. iii) The combination of Cosmo-SkyMed® and SRTM data provided more reliable results. Further analyses are required to evaluate the method in different environmental conditions.
Luca Cenci; Giorgio Boni; Luca Pulvirenti; Giuseppe Squicciarino; Simone Gabellani; Fabio Gardella; Nazzareno Pierdicca; Marco Chini. Monitoring reservoirs' water level from space for flood control applications. A case study in the Italian Alpine region. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2017, 5617 -5620.
AMA StyleLuca Cenci, Giorgio Boni, Luca Pulvirenti, Giuseppe Squicciarino, Simone Gabellani, Fabio Gardella, Nazzareno Pierdicca, Marco Chini. Monitoring reservoirs' water level from space for flood control applications. A case study in the Italian Alpine region. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2017; ():5617-5620.
Chicago/Turabian StyleLuca Cenci; Giorgio Boni; Luca Pulvirenti; Giuseppe Squicciarino; Simone Gabellani; Fabio Gardella; Nazzareno Pierdicca; Marco Chini. 2017. "Monitoring reservoirs' water level from space for flood control applications. A case study in the Italian Alpine region." 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , no. : 5617-5620.
The utility of synthetic aperture radar (SAR) data to produce flood delineation maps is well established. However, for what concerns urban settlements, flood mapping still represents a challenge, because the radar signatures of flooded urban pixels are generally ambiguous. As a matter of fact, flood mapping algorithms generally do not consider urban areas, thus producing a lot of missed detection errors. To cope with this problem, this study proposes a new method that basically analyzes the complex coherence of urban pixels characterized by high backscatter combined with high temporal stability (stable scatterers). Contextual information is also used to reduce the noise of the maps. The rationale is that, since water surfaces show no coherence in a repeat-pass interferogram, a decrease of coherence may occur even for (some) stable scatterers if floodwater is present in a resolution cell. To develop the algorithm, the inundation that hit Houston (Texas, USA) in April 2016 was considered. This event was observed by Sentinel-1 in Interferometric Wide Swath mode. Results showed that looking at the coherence of stable scatterers could represent a reliable road to at least mitigate the problem of missed detection of flooded urban settlements.
Luca Pulvirenti; Marco Chini; Nazzareno Pierdicca; Giorgio Boni. Detection of flooded urban areas using sar: An approach based on the coherence of stable scatterers. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2017, 5701 -5704.
AMA StyleLuca Pulvirenti, Marco Chini, Nazzareno Pierdicca, Giorgio Boni. Detection of flooded urban areas using sar: An approach based on the coherence of stable scatterers. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2017; ():5701-5704.
Chicago/Turabian StyleLuca Pulvirenti; Marco Chini; Nazzareno Pierdicca; Giorgio Boni. 2017. "Detection of flooded urban areas using sar: An approach based on the coherence of stable scatterers." 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , no. : 5701-5704.
In this paper we investigate the double bounce enhancement due to standing water in flooded agricultural fields to assess the capability of an X-band radar to recognize the presence of floodwater under vegetation. The investigation was carried out by analyzing a polarimetric and multifrequency SAR dataset (COSMO-SkyMed, Alos-2, Radarsat-2) collected over the Vercelli district in North Italy, characterized by a widespread and intense cultivation of rice crop, were the fields were routinely artificially flooded and dried according to the agricultural practice. The investigation demonstrated that in July, when rice is well developed, high backscatter in X-band was observed in fields were the L-band polarimetric data recognized the double bounce return. The presence of a double bounce scattering enhancement at X-band was then established. At C-band the dihedral type of return was not clearly recognized because of the smaller incidence angle of Radarsat-2 acquisitions.
Nazzareno Pierdicca; Luca Pulvirenti; Giorgio Boni; Giuseppe Squicciarino; Marco Chini. Radar multispectral and polarimetric signature of rice fields: An investigation on the double bounce mechanism in flooded vegetation. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2017, 5245 -5248.
AMA StyleNazzareno Pierdicca, Luca Pulvirenti, Giorgio Boni, Giuseppe Squicciarino, Marco Chini. Radar multispectral and polarimetric signature of rice fields: An investigation on the double bounce mechanism in flooded vegetation. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2017; ():5245-5248.
Chicago/Turabian StyleNazzareno Pierdicca; Luca Pulvirenti; Giorgio Boni; Giuseppe Squicciarino; Marco Chini. 2017. "Radar multispectral and polarimetric signature of rice fields: An investigation on the double bounce mechanism in flooded vegetation." 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , no. : 5245-5248.
As part of the Copernicus Programme, Sentinel 1 (S1) synthetic aperture radar (SAR) mission represents a unique monitoring tool whose potentialities for hydrological risk mitigation need to be evaluated. To this aim, S1-A derived soil moisture maps with high spatial resolution (100 m) and moderate temporal resolution (12 days) were assimilated within a time-continuous, spatially-distributed, physically-based hydrological model (Continuum) with the specific objective to evaluate the impact on discharge predictions and (flash) flood modelling. A Nudging assimilation scheme was chosen for the DA experiment due to its computational efficiency, particularly useful for operational applications. Results were evaluated in the Orba River catchment (Italy) in the time period October 2014 - November 2016, corresponding to the first two years of activity of the S1-A mission.
Luca Cenci; Luca Pulvirenti; Giorgio Boni; Marco Chini; Patrick Matgen; Simone Gabellani; Giuseppe Squicciarino; Valerio Basso; Flavio Pignone; Nazzareno Pierdicca. Exploiting Sentinel 1 data for improving (flash) flood modelling via data assimilation techniques. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2017, 4939 -4942.
AMA StyleLuca Cenci, Luca Pulvirenti, Giorgio Boni, Marco Chini, Patrick Matgen, Simone Gabellani, Giuseppe Squicciarino, Valerio Basso, Flavio Pignone, Nazzareno Pierdicca. Exploiting Sentinel 1 data for improving (flash) flood modelling via data assimilation techniques. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2017; ():4939-4942.
Chicago/Turabian StyleLuca Cenci; Luca Pulvirenti; Giorgio Boni; Marco Chini; Patrick Matgen; Simone Gabellani; Giuseppe Squicciarino; Valerio Basso; Flavio Pignone; Nazzareno Pierdicca. 2017. "Exploiting Sentinel 1 data for improving (flash) flood modelling via data assimilation techniques." 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , no. : 4939-4942.
The capability of COSMO-SkyMed (CSK) radar to remotely sense standing water beneath vegetation using an automatic algorithm working on a single image is investigated. The objective is to contribute to tackle the problem of missed detection of inundated vegetation by near real-time flood mapping algorithms using SAR data. The focus is on CSK because its four-satellite constellation is very suitable for rapid mapping. A set of CSK observations of an area in Northern Italy where many rice fields are present and recurrent artificial inundations occur were analyzed. Considering that double-bounce is the key process to detect floodwater under vegetation and that polarimetry is potentially able to discriminate double-bounce among different scattering mechanisms, single polarization CSK observations were compared with ALOS-2 and RADARSAT-2 fully polarimetric data. Such a multifrequency and multiangle dataset helped understanding the multitemporal signature of CSK data. A set of Landsat-8 images collected under cloud free conditions were also used as reference. Satellite acquisitions were gathered in order to ensure both spatial overlap among the images of the various sensors and temporal overlap along most of the rice growing season. The comparison between CSK and polarimetric data showed that at least for a slender leaf plant like rice, CSK can be able to detect the enhancement of double-bounce backscattering involving water and vertical plant stems. For some selected fields, it was found a good agreement between CSK-derived floodwater maps and those produced using the normalized-difference water index derived from Landsat-8 images, as well as double-bounce detection from polarimetric data.
Nazzareno Pierdicca; Luca Pulvirenti; Giorgio Boni; Giuseppe Squicciarino; Marco Chini. Mapping Flooded Vegetation Using COSMO-SkyMed: Comparison With Polarimetric and Optical Data Over Rice Fields. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2017, 10, 2650 -2662.
AMA StyleNazzareno Pierdicca, Luca Pulvirenti, Giorgio Boni, Giuseppe Squicciarino, Marco Chini. Mapping Flooded Vegetation Using COSMO-SkyMed: Comparison With Polarimetric and Optical Data Over Rice Fields. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2017; 10 (6):2650-2662.
Chicago/Turabian StyleNazzareno Pierdicca; Luca Pulvirenti; Giorgio Boni; Giuseppe Squicciarino; Marco Chini. 2017. "Mapping Flooded Vegetation Using COSMO-SkyMed: Comparison With Polarimetric and Optical Data Over Rice Fields." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10, no. 6: 2650-2662.
Highly localized and persistent back-building mesoscale convective systems represent one of the most dangerous flash-flood-producing storms in the north-western Mediterranean area. Substantial warming of the Mediterranean Sea in recent decades raises concerns over possible increases in frequency or intensity of these types of events as increased atmospheric temperatures generally support increases in water vapour content. However, analyses of the historical record do not provide a univocal answer, but these are likely affected by a lack of detailed observations for older events. In the present study, 20th Century Reanalysis Project initial and boundary condition data in ensemble mode are used to address the feasibility of performing cloud-resolving simulations with 1 km horizontal grid spacing of a historic extreme event that occurred over Liguria: the San Fruttuoso case of 1915. The proposed approach focuses on the ensemble Weather Research and Forecasting (WRF) model runs that show strong convergence over the Ligurian Sea (17 out of 56 members) as these runs are the ones most likely to best simulate the event. It is found that these WRF runs generally do show wind and precipitation fields that are consistent with the occurrence of highly localized and persistent back-building mesoscale convective systems, although precipitation peak amounts are underestimated. Systematic small north-westward position errors with regard to the heaviest rain and strongest convergence areas imply that the reanalysis members may not be adequately representing the amount of cool air over the Po Plain outflowing into the Ligurian Sea through the Apennines gap. Regarding the role of historical data sources, this study shows that in addition to reanalysis products, unconventional data, such as historical meteorological bulletins, newspapers, and even photographs, can be very valuable sources of knowledge in the reconstruction of past extreme events.
Antonio Parodi; Luca Ferraris; William Gallus; Maurizio Maugeri; Luca Molini; Franco Siccardi; Giorgio Boni. Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915. Climate of the Past 2017, 13, 455 -472.
AMA StyleAntonio Parodi, Luca Ferraris, William Gallus, Maurizio Maugeri, Luca Molini, Franco Siccardi, Giorgio Boni. Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915. Climate of the Past. 2017; 13 (5):455-472.
Chicago/Turabian StyleAntonio Parodi; Luca Ferraris; William Gallus; Maurizio Maugeri; Luca Molini; Franco Siccardi; Giorgio Boni. 2017. "Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915." Climate of the Past 13, no. 5: 455-472.
Postflood indirect peak flow estimates provide key information to advance understanding of flash flood hydrometeorological processes, particularly when peak observations are combined with flood simulations from a hydrological model. However, indirect peak flow estimates are affected by significant uncertainties, which are magnified when floods are associated with important geomorphic processes. The main objective of this work is to advance the integrated use of indirect peak flood estimates and hydrological model simulations by developing and testing a procedure for the assessment of the geomorphic impacts–related uncertainties. The methodology is applied to the analysis of an extreme flash flood that occurred on the Magra River system in Italy on 25 October 2011. The event produced major geomorphic effects and peak discharges close to the maxima observed for high-magnitude rainstorm events in Europe at basin scales ranging from 30 to 1000 km2. Results show that the intensity of geomorphic impacts has a significant effect on the accuracy of postflood peak discharge estimation and model-based flood response analysis. It is shown that the comparison between rainfall–runoff model simulations and indirect peak flow estimates, accounting for uncertainties, may be used to identify erroneous field-derived estimates and isolate consistent hydrological simulations. Comparison with peak discharges obtained for other Mediterranean flash floods allows the scale-dependent flood response of the Magra River system to be placed within a broader hydroclimatological context. Model analyses of the hydrologic response illustrate the role of storm structure and evolution for scale-dependent flood response.
William Amponsah; Lorenzo Marchi; Davide Zoccatelli; Giorgio Boni; Marco Cavalli; Francesco Comiti; Stefano Crema; Ana Lucía; Francesco Marra; Marco Borga. Hydrometeorological Characterization of a Flash Flood Associated with Major Geomorphic Effects: Assessment of Peak Discharge Uncertainties and Analysis of the Runoff Response. Journal of Hydrometeorology 2016, 17, 3063 -3077.
AMA StyleWilliam Amponsah, Lorenzo Marchi, Davide Zoccatelli, Giorgio Boni, Marco Cavalli, Francesco Comiti, Stefano Crema, Ana Lucía, Francesco Marra, Marco Borga. Hydrometeorological Characterization of a Flash Flood Associated with Major Geomorphic Effects: Assessment of Peak Discharge Uncertainties and Analysis of the Runoff Response. Journal of Hydrometeorology. 2016; 17 (12):3063-3077.
Chicago/Turabian StyleWilliam Amponsah; Lorenzo Marchi; Davide Zoccatelli; Giorgio Boni; Marco Cavalli; Francesco Comiti; Stefano Crema; Ana Lucía; Francesco Marra; Marco Borga. 2016. "Hydrometeorological Characterization of a Flash Flood Associated with Major Geomorphic Effects: Assessment of Peak Discharge Uncertainties and Analysis of the Runoff Response." Journal of Hydrometeorology 17, no. 12: 3063-3077.
First results of the assimilation of high-resolution Sentinel-1A based soil moisture products in a distributed, physically based, hydrological model are presented. A comprehensive evaluation of the assimilation's impact on discharge predictions is provided. Results are further compared to those obtained when assimilating the lower-resolution ASCAT-based soil moisture product. The exercise was carried out within the MIDA project framework (funded by the Italian Space Agency) aiming at producing root zone soil moisture maps useful for flood risk management applications. The experimental site is the Orba River Catchment (Italy). The period of investigation is October 2014-February 2015. Using a relatively simple data assimilation technique (Nudging) the results of our case study show that overall the assimilation of currently available Sentinel-1 data only marginally improves discharge simulations. However, the impact becomes more significant when specifically considering predictions of high flow. Further improvements are expected when both Sentinel-1A and B data will be available.
Luca Cenci; Luca Pulvirenti; Giorgio Boni; Marco Chini; Patrick Matgen; Simone Gabellani; Lorenzo Campo; Francesco Silvestro; Cosimo Versace; Paolo Campanella; Laura Candela. Satellite soil moisture assimilation: Preliminary assessment of the sentinel 1 potentialities. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2016, 3098 -3101.
AMA StyleLuca Cenci, Luca Pulvirenti, Giorgio Boni, Marco Chini, Patrick Matgen, Simone Gabellani, Lorenzo Campo, Francesco Silvestro, Cosimo Versace, Paolo Campanella, Laura Candela. Satellite soil moisture assimilation: Preliminary assessment of the sentinel 1 potentialities. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2016; ():3098-3101.
Chicago/Turabian StyleLuca Cenci; Luca Pulvirenti; Giorgio Boni; Marco Chini; Patrick Matgen; Simone Gabellani; Lorenzo Campo; Francesco Silvestro; Cosimo Versace; Paolo Campanella; Laura Candela. 2016. "Satellite soil moisture assimilation: Preliminary assessment of the sentinel 1 potentialities." 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , no. : 3098-3101.
Highly localized and persistent back-building mesoscale convective systems represent one of the most dangerous flash-flood producing storms in the north-western Mediterranean area. Substantial warming of the Mediterranean Sea in recent decades raises concerns over possible increases in frequency or intensity of these types of events as increased atmospheric temperatures generally support increases in water vapor content. However, analyses of the historical record do not provide a univocal answer, but these are likely affected by a lack of detailed observations for older events. In the present study, 20th Century Reanalysis Project initial and boundary condition data in ensemble mode are used to address the feasibility of performing cloud-resolving simulations with 1 km horizontal grid spacing of a historic extreme event that occurred over Liguria: The San Fruttuoso case of 1915. The proposed approach focuses on the ensemble Weather Research and Forecasting (WRF) model runs that show strong convergence over the Liguria sea, as these runs are the ones most likely to best simulate the event. It is found that these WRF runs generally do show wind and precipitation fields that are consistent with the occurrence of highly localized and persistent back-building mesoscale convective systems, although precipitation peak amounts are underestimated. Systematic small north-westward position errors with regard to the heaviest rain and strongest convergence areas imply that the Reanalysis members may not be adequately representing the amount of cool air over the Po Plain outflowing into the Liguria Sea through the Apennines gap. Regarding the role of historical data sources, this study shows that in addition to Reanalysis products, unconventional data, such as historical meteorological bulletins newspapers and even photographs can be very valuable sources of knowledge in the reconstruction of past extreme events.
Antonio Parodi; Luca Ferraris; William Gallus; Maurizio Maugeri; Luca Molini; Franco Siccardi; Giorgio Boni. Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: The San Fruttuoso case of 1915. 2016, 2016, 1 -28.
AMA StyleAntonio Parodi, Luca Ferraris, William Gallus, Maurizio Maugeri, Luca Molini, Franco Siccardi, Giorgio Boni. Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: The San Fruttuoso case of 1915. . 2016; 2016 ():1-28.
Chicago/Turabian StyleAntonio Parodi; Luca Ferraris; William Gallus; Maurizio Maugeri; Luca Molini; Franco Siccardi; Giorgio Boni. 2016. "Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: The San Fruttuoso case of 1915." 2016, no. : 1-28.