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Analysis of Morphological Processes in a Disturbed Gravel-Bed River （Piave River）： Integration of lidar data and Colour Bathymetry

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Journal of Civil Engineering and Architecture 2014年第5期8卷 639-648页

作者： Fabio Delai Johnny Moretto Lorenzo Picco Emanuel Rigon Diego Ravazzolo Mario Aristide Lenzi Department of Land Environment Agriculture and Forestry University of Padova Legnaro 35020 Italy

The magnitude of river morphological changes are better analyzed through the use of quantitative approaches, wherein resolution accuracy and uncertainty assessment are treated as crucial key-factors. In this sense, the creation of precise DEMs （Digital Elevation Models） of rivers represents an affordable tool to analyze geomorphic variations and budgets, except for wetted areas, where reliable channel digitalization can normally be obtained only using expensive bathymetric surveys. The proposed work aims at improving channel surface models without having available bathymetric sensors, by deriving dry areas elevations from lidar data and water depth of wetted areas from aerial photos through a predictive depth-colour relationship. The methodology was applied to two different sub-reaches of the Piave River, a gravel-bed river which suffered severe flood events in 2010. Erosion and deposition patterns were identified through DEM differencing, showing a predominance of scour processes which can lead to channel instability situations. The bathymetric output was compared to other previously-derived models confirming the accuracy of the in-channel elevation estimates. Finally, a discussion on the role played by longitudinal protections during the studied flood events is proposed, focusing the attention on the incidence of two major bank erosions that removed significant volumes of stable areas.

关键词： Colour bathymetry lidar data flood impacts fluvial erosion-deposition processes effect of river protections.

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Analysis of mobility data-A focus on Mobile Mapping Systems

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Geo-Spatial Information Science 2020年第1期23卷 68-74页

作者： Monika Sester Institute of Cartography and Geoinformatics Leibniz Universitat HannoverHannoverGermany

The increasing availability of devices to capture the position of moving objects(and other environmental information)leads to a very large amount and variety of mobility *** order to obtain important information about the objects,their behavior or the environment of the objects,an automatic analysis is *** article highlights current research questions in the context of the analysis of mobility data and presents them on the basis of work carried out at the Institute of Cartography and Geoinformatics(ikg)at Leibniz University of Hannover,Germany.A focus is put on the analysis and exploitation of information from Mobile Mapping vehicles.

关键词： Trajectories lidar data automatic analysis traffic applications

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Developing Blue Spots Model for Tennessee Using GIS, and Advanced data Analytics: Literature Review

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Journal of Geoscience and Environment Protection 2023年第6期11卷 145-154页

作者： Fasesin Kingsley Department of Computing and the Department of Geosciences East Tennessee State University Johnson City Tennessee USA

Climate change and global warming results in natural hazards, including flash floods. Flash floods can create blue spots;areas where transport networks (roads, tunnels, bridges, passageways) and other engineering structures within them are at flood risk. The economic and social impact of flooding revealed that the damage caused by flash floods leading to blue spots is very high in terms of dollar amount and direct impacts on people’s lives. The impact of flooding within blue spots is either infrastructural or social, affecting lives and properties. Currently, more than 16.1 million properties in the U.S are vulnerable to flooding, and this is projected to increase by 3.2% within the next 30 years. Some models have been developed for flood risks analysis and management including some hydrological models, algorithms and machine learning and geospatial models. The models and methods reviewed are based on location data collection, statistical analysis and computation, and visualization (mapping). This research aims to create blue spots model for the State of Tennessee using ArcGIS visual programming language (model) and data analytics pipeline.

关键词： Blue Spots Floods Risks and Management GIS Hydrological Models Geospatial Model Builder lidar data Remote Sensing data Analytics Pipe-line

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