An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

Abstract. An algorithm developed to map flooded areas from synthetic aperture radar imagery is presented in this paper. It is conceived to be inserted in the operational flood management system of the Italian Civil Protection and can be used in an almost automatic mode or in an interactive mode, depending on the user's needs. The approach is based on the fuzzy logic that is used to integrate theoretical knowledge about the radar return from inundated areas taken into account by means of three electromagnetic scattering models, with simple hydraulic considerations and contextual information. This integration aims at allowing a user to cope with situations, such as the presence of vegetation in the flooded area, in which inundation mapping from satellite radars represents a difficult task. The algorithm is designed to work with radar data at L, C, and X frequency bands and employs also ancillary data, such as a land cover map and a digital elevation model. The flood mapping procedure is tested on an inundation that occurred in Albania on January 2010 using COSMO-SkyMed very high resolution X-band SAR data

Impact of ASAR soil moisture data on the MM5 precipitation forecast for the Tanaro flood event of April 2009

Abstract. The representation of land-atmosphere interactions in weather forecast models has a strong impact on the Planetary Boundary Layer (PBL) and, in turn, on the forecast. Soil moisture is one of the key variables in land surface modelling, and an inadequate initial soil moisture field can introduce major biases in the surface heat and moisture fluxes and have a long-lasting effect on the model behaviour. Detecting the variability of soil characteristics at small scales is particularly important in mesoscale models because of the continued increase of their spatial resolution. In this paper, the high resolution soil moisture field derived from ENVISAT/ASAR observations is used to derive the soil moisture initial condition for the MM5 simulation of the Tanaro flood event of April 2009. The ASAR-derived soil moisture field shows significantly drier conditions compared to the ECMWF analysis. The impact of soil moisture on the forecast has been evaluated in terms of predicted precipitation and rain gauge data available for this event have been used as ground truth. The use of the drier, highly resolved soil moisture content (SMC) shows a significant impact on the precipitation forecast, particularly evident during the early phase of the event. The timing of the onset of the precipitation, as well as the intensity of rainfall and the location of rain/no rain areas, are better predicted. The overall accuracy of the forecast using ASAR SMC data is significantly increased during the first 30 h of simulation. The impact of initial SMC on the precipitation has been related to the change in the water vapour field in the PBL prior to the onset of the precipitation, due to surface evaporation. This study represents a first attempt to establish whether high resolution SAR-based SMC data might be useful for operational use, in anticipation of the launch of the Sentinel-1 satellite

Life Cycle Assessment of a Lithium-Ion Battery Pack Unit Made of Cylindrical Cells

Saving energy is a fundamental topic considering the growing energy requirements with respect to energy availability. Many studies have been devoted to this question, and life cycle assessment (LCA) is increasingly acquiring importance in several fields as an effective way to evaluate the energy demand and the emissions associated with products’ life cycles. In this work, an LCA analysis of an existent lithium-ion battery pack (BP) unit is presented with the aim to increase awareness about its consumption and offering alternative production solutions that are less energy intensive. Exploiting the literature data about cradle-to-grave and cradle-to-gate investigations, and after establishing reasonable approximations, the main BP sub-elements were considered for this study, such as the plastic cells support, the Li-ion cells brick, the PCBs for a battery management system (BMS), the liquid-based battery thermal management system (BTMS) and the BP container. For each of these components, the impacts of the extraction, processing, assembly, and transportation of raw materials are estimated and the partial and total values of the energy demand (ED) and global warming potential (GWP) are determined. The final interpretation of the results allows one to understand the important role played by LCA evaluations and presents other possible ways of reducing the energy consumption and (Formula presented.) emissions

Integrating physical and topographic information into a fuzzy scheme to map flooded area by SAR

A flood mapping procedure based on a fuzzy sets theory has been developed. The method is based on the integration of Synthetic Aperture Radar (SAR) measurements with additional data on the inundated area, such as a land cover map and a digital elevation model (DEM). The information on land cover has allowed us to account for both specular reflection, typical of open water, and double bounce backscattering, typical of forested and urban areas. DEM has been exploited to include simple hydraulic considerations on the dependence of inundation probability on surface characteristics. Contextual information has been taken into account too. The proposed algorithm has been tested on a flood occurred in Italy on November 1994. A pair of ERS-1 images, collected before and after (three days later) the flood, has been used. The results have been compared with the data provided by a ground survey carried out when the flood reached its maximum extension. Despite the temporal mismatch between the survey and the post-inundation SAR image, the comparison has yielded encouraging results, with the 87% of the pixels correctly classified as inundated

Retrieval and analysis of land surface microwave emissivity from SSM/I data

The retrieval of land surface emissivity from microwave radiometric measurements is useful for monitoring the surface properties without being affected by the contribution of the atmosphere, which can be significant at higher frequencies. It is based on the inversion of the radiative transfer equation, assuming the absence of scattering phenomena. In this work, a method to improve the accuracy of the emissivity estimates through the removal of the effects of the atmosphere from the radiometric data and through the consideration of the surface elevation information is proposed. We have used the Special Sensor Microwave/Imager (SSM/I) observations over Italy throughout 1995. The atmospheric parameters have been derived from the NCEP vertical profiles, whilst the presence of clouds has been detected through METEOSAT images co-located with the SSM/I ones. The data provided by a digital elevation model (DEM) have been also exploited. Monthly average maps of microwave emissivity relative to a geographical area including Italy have been produced to assess the whole estimation procedure, as well as to give examples of monitoring the seasonal trend of this parameter in a mountainous zone (Alps) and in a flat area (Po Plain)

Physiological and driving behaviour changes associated to different road intersections

Road traffic injuries claim more than 1.2 million lives each year in the world and have a huge impact on health and development. It is commonly acknowledged that the human factor and the interaction between the human factor and the road environment are among the most common causes of road accidents. Intersections are among the most complex road environments: their geometric and traffic characteristics weigh the driver workload, affecting the driving behaviour and consequently the risk of accident. This study intends therefore to contribute for a better understanding of the relationship between different types of intersection and the human factor. The ultimate aim is to understand how at grade intersections affect the driving behaviour by comparing the drivers’ stress level for roundabouts and standard intersections. Electrodermal activity can provide a real-time assessment of the driver's stress level. Electrodermal activity was therefore collected continuously during a driving study which took place on a test environment based at Cranfield University and surrounding roads. Twenty participants were involved within the study. The analysis focused on four crossing manoeuvres on three at grade intersections (two T-junctions and a roundabout) situated on the study location. Results showed that the number of SCR peaks as well as the amplitude of the peaks are overall higher for the two manoeuvres on the roundabout. The stress level induced by each type of intersection was evaluated through an Electrodermal Impact Index which takes into account both the number and the amplitude of SCR peaks. Results suggested that the stress level induced by roundabouts is more than double that induced by standard intersections

Sentinel-1 InSAR coherence to detect floodwater in urban areas: Houston and hurricane harvey as a test case

This paper presents an automatic algorithm for mapping floods. Its main characteristic is that it can detect not only inundated bare soils, but also floodwater in urban areas. The synthetic aperture radar (SAR) observations of the flood that hit the city of Houston (Texas) following the landfall of Hurricane Harvey in 2017 are used to apply and validate the algorithm. The latter consists of a two-step approach that first uses the SAR data to identify buildings and then takes advantage of the Interferometric SAR coherence feature to detect the presence of floodwater in urbanized areas. The preliminary detection of buildings is a pre-requisite for focusing the analysis on the most risk-prone areas. Data provided by the Sentinel-1 mission acquired in both Strip Map and Interferometric Wide Swath modes were used, with a geometric resolution of 5 m and 20 m, respectively. Furthermore, the coherence-based algorithm takes full advantage of the Sentinel-1 mission's six-day repeat cycle, thereby providing an unprecedented possibility to develop an automatic, high-frequency algorithm for detecting floodwater in urban areas. The results for the Houston case study have been qualitatively evaluated through very-high-resolution optical images acquired almost simultaneously with SAR, crowdsourcing points derived by photointerpretation from Digital Globe and Federal Emergency Management Agency's (FEMA) inundation model over the area. For the first time the comparison with independent data shows that the proposed approach can map flooded urban areas with high accuracy using SAR data from the Sentinel-1 satellite mission