13,101 research outputs found
Further insights into platinum carbonyl Chini clusters
Get PDFThe oxidation of [Ph3P(CH2)12PPh3][Pt15(CO)30] with CF3COOH in THF afforded [Ph3P(CH2)12PPh3][Pt18(CO)36] as a precipitate which was re-crystallized from dmf/iso-propanol. This salt self-assembles in the solid state adopting an unprecedented morphology which consists of infinite chains of [Pt9(CO)18]– units. The solid state structure of [Ph3P(CH2)12PPh3][Pt18(CO)36] may be viewed as a snapshot in which [Pt9(CO)18]– units are approaching and ready to exchange outer Pt3(CO)6 fragments. The reactions of Chini clusters with isonitriles proceed via redox-fragmentation, at difference with those involving phosphines that may occur both via non-redox substitution and redox fragmentation, depending on the experimental conditions. Thus, the reaction of [Pt6(CO)12]2– with CNXyl afforded Pt5(CNXyl)10, whereas Pt9(CNXyl)13(CO) was obtained from the reaction of [Pt15(CO)30]2– with CNXyl. These two new neutral clusters have been structurally characterized as their Pt5(CNXyl)10·2toluene and Pt9(CNXyl)13(CO)·solv solvates. DFT studies on the CO exchange of [Pt6(CO)12]2– suggest an associative interchange mechanism, which may be extended also to larger Chini clusters and the initial steps of their reactions with other soft nucleophiles
Analysis and interpretation of the COSMO-SkyMed observations of the 2011 Japan tsunami
No full textThe major outcomes of the analysis of the COSMO-SkyMed (CSK) synthetic aperture radar (SAR) observations of the area hit by the 2011 Japan tsunami are presented. The height of the tsunami waves was such as to cause a widespread inundation of the coastal area. The SAR acquisitions have been performed on March 12 (i.e., one day after the tsunami occurred) and March 13, 2011 in interferometric mode, so that not only the information on the intensity of the radar signals, but also the complex coherence has been used. The interpretation of the available data has allowed us to detect the flooded areas, as well as the receding of the floodwater from March 12 to March 13, 2011 and the presence of the debris floating above the water surface. Moreover, thanks to the high spatial resolution of the CSK images, the presence of floodwater in some urban areas in the Sendai harbor has been revealed by exploiting the information on the coherence. Our interpretations have been confirmed by a couple of optical images used as benchmarks. © 2012 IEEE
Analysis of Cosmo-SkyMed observations of the 2008 flood in Myanmar
No full textTwo Cosmo-SkyMed observations of the inundation occurred in Myanmar on May 2008are analyzed in this paper to study the potentiality of this sensor for flood mapping. The first image is temporally close to the peak of the event, while the other one was acquired one week later. Our study accounts for the physics of the radar return in the presence of water surfaces. In particular, both specular reflection, typical of open water, and double bounce backscattering, typical of forested and urban areas, are considered. From the analysis of the Cosmo-SkyMed images, a map representing the extension of the flood at the time of the first radar acquisition is derived
MABS validation through repeated execution and data mining analysis
No full textAgent Based Modelling is the most interesting and advanced approach for simulating a complex system: in a social context, the single parts and the whole are often very hard to describe in detail. Besides, there are agent based formalisms which allow to study the emergency of social behaviour with the creation and study of models, known as artificial societies. Thanks to the ever increasing computational power, it's been possible to use such models to create software, based on intelligent agents, which aggregate behaviour is complex and difficult to predict, and can be used in open and distributed systems. Data mining is born in the last decades in order to help users in finding useful knowledge from the otherwise overwhelming amount of data available nowadays from the web and the data collected every day by companies. Data Mining techniques can therefore be the keystone to reveal non-trivial knowledge expressed by the initial assumption used to build the micro-level of the model and the structure of the society of agents that emerged from the simulation
Thematic mapping at regional scale using SIASGE Radar data at X and L band and optical images
No full textThis work aims to assess the potential of Synthetic Aperture Radar (SAR) data combined with optical data to support local administrations in the knowledge of the land use and land cover at regional scale. In particular, the contribution of data available in the future through the SIASGE project, combining L-band and X-band radar imagery, is assessed in order to produce thematic maps. Moreover, the further contribution brought by C-band has been evaluated. The classification, focused on two regions in the north side of Italy, is driven by the legend of already existing maps tackling the real needs of the land managing authorities. As the combination of data from optical imagery is fundamental to achieve good thematic accuracy, the work has exploited the Support Vector Machine learning technique, which is more suitable than standard statistical parametric approaches in this respect. Concerning the classification step, some algorithmic issues has been faced to improve the results, such as training set selection strategy and data fusion techniques. The work has proved as the multi source data set (SAR and optical) is fairly suitable to produce thematic maps comparable to what already in use at local administrative level, allowing to obtain reliable maps with a classification accuracy in the order of 90 %. © 2011 IEEE
Improving Flood Detection in Vegetated Areas through Multi-Frequency, Polarimetric and Interferometric SAR Data
No full textMapping flooded vegetation using COSMO-SkyMed: Comparison with polarimetric and optical data over rice fields
No full textThe 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 inNorthern Italy wheremany 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 comparedwithALOS-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 floodwatermaps and those produced using the normalized-differencewater index derived fromLandsat-8 images, as well as double-bounce detection from polarimetric data
Floodwater Mapping in Urban Areas using SAR Data
No full textChini et al. in [1], developed an algorithm to automatically map urban floods from Synthetic Aperture Radar (SAR) data, which can function in near-real time worldwide. It has been tested on the extreme Pakistani floods, which started in the summer of 2022 and lasted for several months. This test case also served to study the characteristics of interferometric phase (in-phase) Standard Deviation (SD), to ensure the preservation of the original information. Then, using four classification methods: thresholding, region growing (RG), Bayesian network fusion (BNF) and BNF with RG, all the possible combinations between intensity, coherence and in-phase are tested to map floods in urban areas. For smaller areas (tens of square kilometers), it appears that in-phase SD does not add significantly more information. However, for larger areas (more than hundreds of square kilometers), the combination of the three SAR features in a BNF provides the best results.ECE
Flood Mapping in Vegetated and Urban Areas and Other Challenges: Models and Methods
No full textFloods are the most frequent weather disasters in the world and the most costly in terms of economic losses. Mapping flood extension is fundamental to ascertain the damage and for relief organization. Spaceborne synthetic aperture radar (SAR) systems represent a powerful tool to monitor floods because of their all-weather capability, the very high spatial resolution of the new generation of instruments, and the short revisit time of the present and future satellite constellations. However, mapping flooded vegetated and urban areas still represents a challenging problem.
Modeling different targets both in the presence and in the absence of flood water is a very complex task. In the first part of the chapter we review these challenging conditions, showing their potential effects on radar data and in particular on COSMO-SkyMed images. In some cases the potential of electromagnetic models to predict the radar response is shown.
A second part of the chapter illustrates a number of strategies one can exploit, with examples showing the achievable performances with respect to a simple mapping of dark areas in the SAR image
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