scholarly journals INTEROPERABLE VISUALIZATION OF 3D CITY MODELS USING OGC’S STANDARD 3D PORTRAYAL SERVICE

2018 ◽  
Vol IV-4 ◽  
pp. 113-118
Author(s):  
A. Koukofikis ◽  
V. Coors ◽  
R. Gutbell
Keyword(s):  
Spatial Data ◽  
Urban Areas ◽  
Hierarchical Structures ◽  
Hierarchical Data ◽  
Web Map ◽  
3D Data ◽  
Delivery Format ◽  
3D Scene ◽  
Community Standard ◽  
City Models

<p><strong>Abstract.</strong> The demand of serving large 3D spatial data, mainly of urban areas, reflects the need of hierarchical data structures for 3D data. During the last years the OGC community standard I3S (Indexed 3d Scene Layer, ESRI) and 3D Tiles (Analytical Graphics, Inc.) emerged in order to deal with this challenge. Conceptually, hierarchical structures for 3D data operate similarly to web map tiles, differing only in the implementation. Although 3D hierarchical formats can transmit arbitrary sized geospatial data, they are not interoperable with consuming/visualization technologies on the client. A series of prototype implementations focus on rendering of hierarchical organized massive 3D data in various web client technologies employing the 3D Portrayal Service. As a result, the user can query a scene via the 3D Portrayal Service by specifying a spatial region, rather than a specific resource via a URI. The result is delivered either using I3S or 3D Tiles as a data delivery format, depending on which data is available for the specified region. The client APIs are capable of rendering either the I3S or the 3D Tiles content.</p>

scholarly journals Towards an Underground Utilities 3D Data Model for Land Administration

2019 ◽  
Vol 11 (17) ◽  
pp. 1957 ◽  
Author(s):  
Jingya Yan ◽  
Siow Jaw ◽  
Kean Soon ◽  
Andreas Wieser ◽  
Gerhard Schrotter
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Urban Areas ◽  
Spatial Information ◽  
Three Dimensional ◽  
Data Governance ◽  
Land Administration ◽  
3D Data ◽  
Underground Utilities ◽  
2D Data

With the pressure of the increasing density of urban areas, some public infrastructures are moving to the underground to free up space above, such as utility lines, rail lines and roads. In the big data era, the three-dimensional (3D) data can be beneficial to understand the complex urban area. Comparing to spatial data and information of the above ground, we lack the precise and detailed information about underground infrastructures, such as the spatial information of underground infrastructure, the ownership of underground objects and the interdependence of infrastructures in the above and below ground. How can we map reliable 3D underground utility networks and use them in the land administration? First, to explain the importance of this work and find a possible solution, this paper observes the current issues of the existing underground utility database in Singapore. A framework for utility data governance is proposed to manage the work process from the underground utility data capture to data usage. This is the backbone to support the coordination of different roles in the utility data governance and usage. Then, an initial design of the 3D underground utility data model is introduced to describe the 3D geometric and spatial information about underground utility data and connect it to the cadastral parcel for land administration. In the case study, the newly collected data from mobile Ground Penetrating Radar is integrated with the existing utility data for 3D modelling. It is expected to explore the integration of new collected 3D data, the existing 2D data and cadastral information for land administration of underground utilities.

scholarly journals Spatial ETL for 3D Building Modelling Based on Unmanned Aerial Vehicle Data in Semi-Urban Areas

2020 ◽  
Vol 12 (12) ◽  
pp. 1972 ◽  
Author(s):  
Urška Drešček ◽  
Mojca Kosmatin Fras ◽  
Jernej Tekavec ◽  
Anka Lisec
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Spatial Data ◽  
Urban Areas ◽  
Point Cloud ◽  
Process Model ◽  
Laser Scanning ◽  
3D City Models ◽  
Aerial Vehicle ◽  
Spatial Etl ◽  
City Models

This paper provides the innovative approach of using a spatial extract, transform, load (ETL) solution for 3D building modelling, based on an unmanned aerial vehicle (UAV) photogrammetric point cloud. The main objective of the paper is to present the holistic workflow for 3D building modelling, emphasising the benefits of using spatial ETL solutions for this purpose. Namely, despite the increasing demands for 3D city models and their geospatial applications, the generation of 3D city models is still challenging in the geospatial domain. Advanced geospatial technologies provide various possibilities for the mass acquisition of geospatial data that is further used for 3D city modelling, but there is a huge difference in the cost and quality of input data. While aerial photogrammetry and airborne laser scanning involve high costs, UAV photogrammetry has brought new opportunities, including for small and medium-sized companies, by providing a more flexible and low-cost source of spatial data for 3D modelling. In our data-driven approach, we use a spatial ETL solution to reconstruct a 3D building model from a dense image matching point cloud which was obtained beforehand from UAV imagery. The results are 3D building models in a semantic vector format consistent with the OGC CityGML standard, Level of Detail 2 (LOD2). The approach has been tested on selected buildings in a simple semi-urban area. We conclude that spatial ETL solutions can be efficiently used for 3D building modelling from UAV data, where the data process model developed allows the developer to easily control and manipulate each processing step.

scholarly journals THE IMPACT OF 3D DATA QUALITY ON IMPROVING GNSS PERFORMANCE USING CITY MODELS INITIAL SIMULATIONS

2016 ◽  
Vol IV-2/W1 ◽  
pp. 171-178 ◽  
Author(s):  
C. Ellul ◽  
M. Adjrad ◽  
P. Groves
Keyword(s):  
Urban Areas ◽  
Elevation Angle ◽  
3D City Models ◽  
Matching Process ◽  
3D City Model ◽  
3D Data ◽  
Satellite Visibility ◽  
Increasing Demand ◽  
The Impact ◽  
City Models

There is an increasing demand for highly accurate positioning information in urban areas, to support applications such as people and vehicle tracking, real-time air quality detection and navigation. However systems such as GPS typically perform poorly in dense urban areas. A number of authors have made use of 3D city models to enhance accuracy, obtaining good results, but to date the influence of the quality of the 3D city model on these results has not been tested. This paper addresses the following question: how does the quality, and in particular the variation in height, level of generalization and completeness and currency of a 3D dataset, impact the results obtained for the preliminary calculations in a process known as Shadow Matching, which takes into account not only where satellite signals are visible on the street but also where they are predicted to be absent. We describe initial simulations to address this issue, examining the variation in elevation angle &amp;ndash; i.e. the angle above which the satellite is visible, for three 3D city models in a test area in London, and note that even within one dataset using different available height values could cause a difference in elevation angle of up to 29&amp;deg;. Missing or extra buildings result in an elevation variation of around 85&amp;deg;. Variations such as these can significantly influence the predicted satellite visibility which will then not correspond to that experienced on the ground, reducing the accuracy of the resulting Shadow Matching process.

scholarly journals Literature Mapper: A QGIS Plugin for Georeferencing Citations in Zotero

2021 ◽  
Vol 14 ◽  
pp. 117862212110092
Author(s):  
Michele M Tobias ◽  
Alex I Mandel
Keyword(s):  
Data Storage ◽  
Spatial Data ◽  
Future Research ◽  
Web Mapping ◽  
Web Map ◽  
Public Sharing ◽  
Academic Publications ◽  
Spatial Coordinates ◽  
Study Sites ◽  
Soil And Water

Many studies in air, soil, and water research involve observations and sampling of a specific location. Knowing where studies have been previously undertaken can be a valuable addition to future research, including understanding the geographical context of previously published literature and selecting future study sites. Here, we introduce Literature Mapper, a Python QGIS plugin that provides a method for creating a spatial bibliography manager as well as a specification for storing spatial data in a bibliography manager. Literature Mapper uses QGIS’ spatial capabilities to allow users to digitize and add location information to a Zotero library, a free and open-source bibliography manager on basemaps or other geographic data of the user’s choice. Literature Mapper enhances the citations in a user’s online Zotero database with geo-locations by storing spatial coordinates as part of traditional citation entries. Literature Mapper receives data from and sends data to the user’s online database via Zotero’s web API. Using Zotero as the backend data storage, Literature Mapper benefits from all of its features including shared citation Collections, public sharing, and an open web API usable by additional applications, such as web mapping libraries. To evaluate Literature Mapper’s ability to provide insights into the spatial distribution of published literature, we provide a case study using the tool to map the study sites described in academic publications related to the biogeomorphology of California’s coastal strand vegetation, a line of research in which air movement, soil, and water are all driving factors. The results of this exercise are presented in static and web map form. The source code for Literature Mapper is available in the corresponding author’s GitHub repository: https://github.com/MicheleTobias/LiteratureMapper

scholarly journals Measuring Walkability with GIS—Methods Overview and New Approach Proposal

2021 ◽  
Vol 13 (4) ◽  
pp. 1883
Author(s):  
Agnieszka Telega ◽  
Ivan Telega ◽  
Agnieszka Bieda
Keyword(s):  
Spatial Data ◽  
Urban Areas ◽  
Modern World ◽  
Single Family ◽  
New Approach ◽  
Parks And Recreation ◽  
Gis Tools ◽  
Point Data ◽  
Pedestrian Infrastructure ◽  
Gis Methods

Cities occupy only about 3% of the Earth’s surface area, but half of the global population lives in them. The high population density in urban areas requires special actions to make these areas develop sustainably. One of the greatest challenges of the modern world is to organize urban spaces in a way to make them attractive, safe and friendly to people living in cities. This can be managed with the help of a number of indicators, one of which is walkability. Of course, the most complete analyses are based on spatial data, and the easiest way to implement them is using GIS tools. Therefore, the goal of the paper is to present a new approach for measuring walkability, which is based on density maps of specific urban functions and networks of generally accessible pavements and paths. The method is implemented using open-source data. Density values are interpolated from point data (urban objects featuring specific functions) and polygons (pedestrian infrastructure) using Kernel Density and Line Density tools in GIS. The obtained values allow the calculation of a synthetic indicator taking into account the access by means of pedestrian infrastructure to public transport stops, parks and recreation areas, various attractions, shops and services. The proposed method was applied to calculate the walkability for Kraków (the second largest city in Poland). The greatest value of walkability was obtained for the Main Square (central part of the Old Town). The least accessible to pedestrians are, on the other hand, areas located on the outskirts of the city, which are intended for extensive industrial areas, single-family housing or large green areas.

scholarly journals EXTRACTION AND VISUALIZATION OF 3D BUILDING MODELS IN URBAN AREAS FOR FLOOD SIMULATION

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 669-673 ◽  
Author(s):  
C. E. Kilsedar ◽  
F. Fissore ◽  
F. Pirotti ◽  
M. A. Brovelli
Keyword(s):  
Urban Areas ◽  
Three Dimensional ◽  
Decision Makers ◽  
Three Dimensions ◽  
Adaptation Measures ◽  
Flood Simulation ◽  
Domain Experts ◽  
Effective Strategies ◽  
Web Map ◽  
Building Models

<p><strong>Abstract.</strong> Floods pose a risk that is likely to worsen in the future due to climate change. Therefore, it is essential that decision makers and domain experts have the tools to evaluate the effects of floods. We developed a tool that visualizes the earth and buildings in three dimensions to simulate floods so that effective strategies can be developed to enhance resilience and mitigate the effects of floods. We opted to use open standards and free and open source software (FOSS) for Web to maximize interoperability, replicability, reusability, and accessibility. As a result of the literature review, we decided to use CityGML and CesiumJS for three-dimensional geospatial data visualization. However, as CityGML data is not available for the cities that our project focuses on, we developed software called shp2city that converts Esri shapefile to CityGML data in LOD1 or LOD2. Moreover, as CityGML data cannot be immediately used with CesiumJS, we used 3DCityDB to store, represent, and manage the CityGML data; 3DCityDB Importer/Exporter to export the CityGML data in KML/COLLADA/glTF format to be used within the 3DCityDB Web-Map-Client that is based on CesiumJS for visualization. Finally, we simulated floods to aid in the informed decision-making process regarding adaptation measures and mitigation of flooding effects.</p>

scholarly journals Relationships between landslides and land use changes in the Sanbagawa and Mikabu Belts, Shikoku, Japan

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Roxanne Lai ◽  
Takashi Oguchi
Keyword(s):  
Land Use ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Urban Areas ◽  
Land Use Changes ◽  
Land Abandonment ◽  
Crystalline Schist ◽  
Agricultural Abandonment ◽  
Landslide Kinematics

<p><strong>Abstract.</strong> Changing land use is an increasingly important issue as human habits, behaviors, and needs change. There has been an increase in land and agricultural abandonment in some places of the world. In Japan, movement of the population from rural to urban areas have resulted in much land and agricultural abandonment. In 2016, a land ministry survey showed that 4.1 million hectares of land in Japan had unclear ownership, with farmland making up 16.9% of the total. As vegetation cover changes after land abandonment, this temporal and spatial effect may have important effects on geomorphic processes such as landslide susceptibility and landslide kinematics.</p><p>Here we track long-term land use changes over vegetated landslide areas of the Sanbagawa and Mikabu Belts of Shikoku Island, Japan. The Sanbagawa and Mikabu Belts are metamorphic belts that run across Southwest Japan, and are home to numerous large crystalline schist landslides, including the widely-studied slow but continuously moving Zentoku landslide. Villages and communities have been built on these landslide areas due to historical and cultural factors, as well as the fertility of the soil. Consequently, given the changing land uses including land abandonment in these landslide areas over time, we use long-term high-resolution land cover vegetation datasets to examine first the long-term land use changes, and then use statistical methods to explore their relationships with landslide susceptibility and kinematics. Mapping of spatial data and their analysis using GIS constitute a core part of the research. The results suggest interconnections between land use changes and land movement.</p>

scholarly journals Estimation of Building Heights and DEM Accuracy Assessment Using ICESat-2 Data Products

2021 ◽  
Vol 10 (1) ◽  
pp. 37
Author(s):  
Goddu Pavan Sai Goud ◽  
Ashutosh Bhardwaj
Keyword(s):  
Spatial Data ◽  
Rural Areas ◽  
Urban Areas ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Population Expansion ◽  
Cost Effective ◽  
Absolute Error ◽  
Google Earth ◽  
Surface Geometry

The use of remote sensing for urban monitoring is a very reliable and cost-effective method for studying urban expansion in horizontal and vertical dimensions. The advantage of multi-temporal spatial data and high data accuracy is useful in mapping urban vertical aspects like the compactness of urban areas, population expansion, and urban surface geometry. This study makes use of the ‘Ice, cloud, and land elevation satellite-2′ (ICESat-2) ATL 03 photon data for building height estimation using a sample of 30 buildings in three experimental sites. A comparison of computed heights with the heights of the respective buildings from google image and google earth pro was done to assess the accuracy and the result of 2.04 m RMSE was obtained. Another popularly used method by planners and policymakers to map the vertical dimension of urban terrain is the Digital Elevation Model (DEM). An assessment of the openly available DEM products—TanDEM-X and Cartosat-1 has been done over Urban and Rural areas. TanDEM-X is a German earth observation satellite that uses InSAR (Synthetic Aperture Radar Interferometry) technique to acquire DEM while Cartosat-1 is an optical stereo acquisition satellite launched by the Indian Space Research Organization (ISRO) that uses photogrammetric techniques for DEM acquisition. Both the DEMs have been compared with ICESat-2 (ATL-08) Elevation data as the reference and the accuracy has been evaluated using Mean error (ME), Mean absolute error (MAE) and Root mean square error (RMSE). In the case of Greater Hyderabad Municipal Corporation (GHMC), RMSE values 5.29 m and 7.48 m were noted for TanDEM-X 90 and CartoDEM V3 R1 respectively. While the second site of Bellampalli Mandal rural area observed 5.15 and 5.48 RMSE values for the same respectively. Therefore, it was concluded that TanDEM-X has better accuracy as compared to the CartoDEM V3 R1.

scholarly journals SEMI-AUTOMATED APPROACH FOR MAPPING URBAN TREES FROM INTEGRATED AERIAL LiDAR POINT CLOUD AND DIGITAL IMAGERY DATASETS

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 127-134 ◽  
Author(s):  
M. A. Dogon-Yaro ◽  
P. Kumar ◽  
A. Abdul Rahman ◽  
G. Buyuksalih
Keyword(s):  
Digital Image ◽  
Spatial Data ◽  
Urban Areas ◽  
Point Cloud ◽  
Structural Complexity ◽  
Urban Ecosystems ◽  
Field Work ◽  
Urban Trees ◽  
Decision Makers ◽  
Image Datasets

Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.

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