Impact analysis of accidents on the traffic flow based on massive floating car data

The wide usage of GPS-equipped devices enables the mass recording of vehicle movement trajectories describing the movement behavior of the traffic participants. An important aspect of the road traffic is the impact of anomalies, like accidents, on traffic flow. Accidents are especially important as they contribute to the the aspects of safety and also influence travel time estimations. In this paper, the impact of accidents is determined based on a massive GPS trajectory and accident dataset. Due to the missing precise date of the accidents in the data set used, first, the date of the accident is estimated based on the speed profile at the accident time. Further, the temporal impact of the accident is estimated using the speed profile of the whole day. The approach is applied in an experiment on a one month subset of the datasets. The results show that more than 72% of the accident dates are identified and the impact on the temporal dimension is approximated. Moreover, it can be seen that accidents during the rush hours and on high frequency road types (e.g. motorways, trunks or primaries) have an increasing effect on the impact duration on the traffic flow

Modelling below- and above-ground utility network features with the CityGML Utility Network ADE: Experiences from Rotterdam

Precise and comprehensive knowledge about 3D urban space is required for simulation and analysis in the fields of urban and environmental planning, city administration and disaster management. In order to facilitate these applications, geo-information about functional, semantic, and topographic aspects of urban features, their mutual dependencies and relations is needed. Substantial work has been done in the modelling and representation of above-ground features in the context of 3D city modelling. However, the belowground part of the real world, of which utility networks form a big part, is often neglected. Existing data models for utility networks are generally very domain-specific and, therefore, not suitable either. This paper describes a 3D data modelling approach for integrated management of below-ground utility networks and related above-ground city objects. This approach consists of manipulating first the structure of existing utility data in the commonly used Feature Manipulation Engine ETL software in order to make the data compliant to the CityGML Utility Network ADE data model. Subsequently, workspaces are created that take care of storing the CityGML data into the free and open-source 3D City Database, which has been extended in order to manage utility network data, too. Moreover, the research shows the suitability of the extended 3DCityDB to perform graph-based topological operations by means of the PostgreSQL pgRouting extension. Lastly, the results are visualized in typical GIS applications, e.g. QGIS and ArcGIS.Urban Data Scienc

SOLAR RADIATION ESTIMATION ON BUILDING ROOFS AND WEB-BASED SOLAR CADASTRE

The aim of this study is the estimation of solar irradiance on building roofs in complex Alpine landscapes. Very high resolution geometric models of the building roofs are generated by means of advanced automated image matching methods. Models are combined with raster and vector data sources to estimate the incoming solar radiation hitting the roofs. The methodology takes into account for atmospheric effects, site latitude and elevation, slope and aspect of the terrain as well as the effects of shadows cast by surrounding buildings, chimneys, dormers, vegetation and terrain topography. An open source software solution has been developed and applied to a study area located in a mountainous site and containing some 1250 residential, commercial and industrial buildings. The method has been validated by data collected with a pyranometer and results made available through a prototype WebGIS platform

SOLAR RADIATION ESTIMATION ON BUILDING ROOFS AND WEB-BASED SOLAR CADASTRE

The aim of this study is the estimation of solar irradiance on building roofs in complex Alpine landscapes. Very high resolution geometric models of the building roofs are generated by means of advanced automated image matching methods. Models are combined with raster and vector data sources to estimate the incoming solar radiation hitting the roofs. The methodology takes into account for atmospheric effects, site latitude and elevation, slope and aspect of the terrain as well as the effects of shadows cast by surrounding buildings, chimneys, dormers, vegetation and terrain topography. An open source software solution has been developed and applied to a study area located in a mountainous site and containing some 1250 residential, commercial and industrial buildings. The method has been validated by data collected with a pyranometer and results made available through a prototype WebGIS platform

Solar radiation estimation on building roofs and web-based solar cadaster

The aim of this study is the estimation of solar irradiance on building roofs in complex Alpine landscapes. Very high resolution geometric models of the building roofs are generated by means of advanced automated image matching methods. Models are combined with raster and vector data sources to estimate the incoming solar radiation hitting the roofs. The methodology takes into account for atmospheric effects, site latitude and elevation, slope and aspect of the terrain as well as the effects of shadows cast by surrounding buildings, chimneys, dormers, vegetation and terrain topography. An open source software solution has been developed and applied to a study area located in a mountainous site and containing some 1250 residential, commercial and industrial buildings. The method has been validated by data collected with a pyranometer and results made available through a prototype WebGIS platform

Towards a framework for point-cloud-based visual analysis of historic gardens: Jichang Garden as a case study

Historic gardens, regarded as a significant genre of cultural heritage, encapsulate the enduring essence of bygone eras while concurrently transcending temporal boundaries to resonate with the present and future. These gardens provide us vitality and inspiration, holding a collective repository of human memory and serving as a testament to our shared heritage. However, like landscapes, gardens constantly change through natural processes and human interventions. How can we preserve these gardens, though changes are unavoidable? Spatial and visual characteristics are the gardens' essential characteristics, and point-cloud (LiDAR) technologies are powerful tools to reveal and analyze gardens’ spatial-visual relationships and characteristics. Therefore, this paper aims to present a point-cloud-based approach to identifying spatial-visual design principles and making them operational to protect and develop historic gardens. Additionally, several methods have been proposed in this research, including (a) a voxel-based method to transfer points into a solid model for GIS-based computation, (b) a novel method to analyze the field of view (FOV), and (c) a systemic framework to reveal historic gardens’ spatial-visual characteristics based on the voxelized model. Jichang Garden, a historic garden in Wuxi, China, known for its visual design and spatial arrangement, has been selected as a case study to showcase how to apply the methods proposed by this paper. The findings include the design principles for the water body, the arrangement for a route, and the planting strategies of the garden. The conservational strategies have been formed based on the findings, and the appliable potentials and limitations of the methods have also been discussed.Landscape ArchitectureUrban Data Scienc

Towards a Practical Method for Voxel-based Visibility Analysis with Point Cloud Data for Landscape Architects: Jichang Garden (Wuxi, China) as an Example

This paper focuses on GIS-based visibility analysis to explore landscape architecture com-positions as a means to understand visual-spatial characteristics and identify related design principles. More specifically, the paper elaborates a practical method to employ high-resolution data acquired by terrestrial LiDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging) for this pur-pose. Though LiDAR provides a powerful means to digitally capture the real-world, methods like GIS-based visual landscape research that utilize viewshed analysis ideally require a continuous Digital Landscape Model conduct visibility computation. Therefore, one of the obstacles before the visual analysis is to process the points into surface or solid models. Voxel-based algorithms are powerful means to process LiDAR data. There are many applications known of voxel-based visibility analysis but requires often specialist software that is hard to handle or unavailable to landscape architects in practice. This paper showcases an attempt to use standard software for voxel-based visibility analysis. It presents a practical method for applications in landscape architecture analysis. Jichang Garden (Wuxi, China) is used as an example. The historical garden is an evocative example of a landscape architecture compo-sition that displays skilful applications of spatial-visual design principles and therefore worthy of ana-lyse.Landscape ArchitectureUrban Data Scienc