scholarly journals A Method for the Automated Construction of 3D Models of Cities and Neighborhoods from Official Cadaster Data for Solar Analysis

2021 ◽  
Vol 13 (11) ◽  
pp. 6028
Author(s):  
Carlos Beltran-Velamazan ◽  
Marta Monzón-Chavarrías ◽  
Belinda López-Mesa

3D city models are a useful tool to analyze the solar potential of neighborhoods and cities. These models are built from buildings footprints and elevation measurements. Footprints are widely available, but elevation datasets remain expensive and time-consuming to acquire. Our hypothesis is that the GIS cadastral data can be used to build a 3D model automatically, so that generating complete cities 3D models can be done in a short time with already available data. We propose a method for the automatic construction of 3D models of cities and neighborhoods from 2D cadastral data and study their usefulness for solar analysis by comparing the results with those from a hand-built model. The results show that the accuracy in evaluating solar access on pedestrian areas and solar potential on rooftops with the automatic method is close to that from the hand-built model with slight differences of 3.4% and 2.2%, respectively. On the other hand, time saving with the automatic models is significant. A neighborhood of 400,000 m2 can be built up in 30 min, 50 times faster than by hand, and an entire city of 967 km2 can be built in 8.5 h.

Author(s):  
A. Uyar ◽  
N. N. Ulugtekin

In recent years, 3D models have been created of many cities around the world. Most of the 3D city models have been introduced as completely graphic or geometric models, and the semantic and topographic aspects of the models have been neglected. In order to use 3D city models beyond the task, a generalization is necessary. CityGML is an open data model and XML-based format for the storage and exchange of virtual 3D city models. Level of Details (LoD) which is an important concept for 3D modelling, can be defined as outlined degree or prior representation of real-world objects. The paper aim is first describes some requirements of 3D model generalization, then presents problems and approaches that have been developed in recent years. In conclude the paper will be a summary and outlook on problems and future work.


Author(s):  
K. Al Kalbani ◽  
A. Abdul Rahman

Abstract. The paper investigates the capability to integrate the surface and subsurface 3D spatial objects data structure within the 3D spatial data infrastructure (3D SDI) based on the CityGML standards. In fact, a number of countries around the world have started applying the 3D city models for their planning and infrastructure management. While others are still working toward 3D SDI by using CityGML standards. Moreover, most of these initiatives focus on the surface spatial objects with less interest to model subsurface spatial objects. However, dealing with 3D SDI requires both surface and subsurface spatial objects with clear consideration on the issues and challenges in terms of the data structure. On the other hand, the study has used geospatial tools and databases such as FME, PostgreSQL-PostGIS, and 3D City Database to generate the 3D model and to test the capability for integrating the surface and subsurface 3D spatial objects data structure within the 3D SDI. This paper concludes by describing a framework that aims to integrate surface and subsurface 3D geospatial objects data structure in Oman SDI. The authors believe that there are possible solutions based on CityGML standards for surface and subsurface 3D spatial objects. Moreover, solving the issues in data structure can establish a better vision and open new avenues for the 3D SDI.


Author(s):  
G. S. Floros ◽  
C. Ellul ◽  
E. Dimopoulou

<p><strong>Abstract.</strong> Applications of 3D City Models range from assessing the potential output of solar panels across a city to determining the best location for 5G mobile phone masts. While in the past these models were not readily available, the rapid increase of available data from sources such as Open Data (e.g. OpenStreetMap), National Mapping and Cadastral Agencies and increasingly Building Information Models facilitates the implementation of increasingly detailed 3D Models. However, these sources also generate integration challenges relating to heterogeneity, storage and efficient management and visualization. CityGML and IFC (Industry Foundation Classes) are two standards that serve different application domains (GIS and BIM) and are commonly used to store and share 3D information. The ability to convert data from IFC to CityGML in a consistent manner could generate 3D City Models able to represent an entire city, but that also include detailed geometric and semantic information regarding its elements. However, CityGML and IFC present major differences in their schemas, rendering interoperability a challenging task, particularly when details of a building’s internal structure are considered (Level of Detail 4 in CityGML). The aim of this paper is to investigate interoperability options between the aforementioned standards, by converting IFC models to CityGML LoD 4 Models. The CityGML Models are then semantically enriched and the proposed methodology is assessed in terms of model’s geometric validity and capability to preserve semantics.</p>


Author(s):  
Juha Hyyppä ◽  
Lingli Zhu ◽  
Zhengjun Liu ◽  
Harri Kaartinen ◽  
Anttoni Jaakkola

Smartphones with larger screens, powerful processors, abundant memory, and an open operation system provide many possibilities for 3D city or photorealistic model applications. 3D city or photorealistic models can be used by the users to locate themselves in the 3D world, or they can be used as methods for visualizing the surrounding environment once a smartphone has already located the phone by other means, e.g. by using GNSS, and then to provide an interface in the form of a 3D model for the location-based services. In principle, 3D models can be also used for positioning purposes. For example, matching of images exported from the smartphone and then registering them in the existing 3D photorealistic world provides the position of the image capture. In that process, the central computer can do a similar image matching task when the users locate themselves interactively into the 3D world. As the benefits of 3D city models are obvious, this chapter demonstrates the technology used to provide photorealistic 3D city models and focus on 3D data acquisition and the methods available in 3D city modeling, and the development of 3D display technology for smartphone applications. Currently, global geoinformatic data providers, such as Google, Nokia (NAVTEQ), and TomTom (Tele Atlas), are expanding their products from 2D to 3D. This chapter is a presentation of a case study of 3D data acquisition, modeling and mapping, and visualization for a smartphone, including an example based on data collected by mobile laser scanning data from the Tapiola (Espoo, Finland) test field.


Author(s):  
O. Wysocki ◽  
B. Schwab ◽  
L. Hoegner ◽  
T. H. Kolbe ◽  
U. Stilla

Abstract. Nowadays, the number of connected devices providing unstructured data is rapidly rising. These devices acquire data with a temporal and spatial resolution at an unprecedented level creating an influx of geoinformation which, however, lacks semantic information. Simultaneously, structured datasets like semantic 3D city models are widely available and assure rich semantics and high global accuracy but are represented by rather coarse geometries. While the mentioned downsides curb the usability of these data types for nowadays’ applications, the fusion of both shall maximize their potential. Since testing and developing automated driving functions stands at the forefront of the challenges, we propose a pipeline fusing structured (CityGML and HD Map datasets) and unstructured datasets (MLS point clouds) to maximize their advantages in the automatic 3D road space models reconstruction domain. The pipeline is a parameterized end-to-end solution that integrates segmentation, reconstruction, and modeling tasks while ensuring geometric and semantic validity of models. Firstly, the segmentation of point clouds is supported by the transfer of semantics from a structured to an unstructured dataset. The distinction between horizontal- and vertical-like point cloud subsets enforces a further segmentation or an immediate refinement while only adequately depicted models by point clouds are allowed. Then, based on the classified and filtered point clouds the input 3D model geometries are refined. Building upon the refinement, the semantic enrichment of the 3D models is presented. The deployment of a simulation engine for automated driving research and a city model database tool underlines the versatility of possible application areas.


Urban Science ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 47
Author(s):  
Renoy Girindran ◽  
Doreen S Boyd ◽  
Julian Rosser ◽  
Dhanya Vijayan ◽  
Gavin Long ◽  
...  

A 3D model communicates more effectively than a 2D model, hence the applications of 3D city models are rapidly gaining significance in urban studies. However, presently, there is a dearth of free of cost, high-resolution 3D city models available for use. This paper offers potential solutions to this problem by providing a globally replicable methodology to generate low-cost 3D city models from open source 2D building data in conjunction with open satellite-based elevation datasets. Two geographically and morphologically different case studies were used to develop and test this methodology: the Chinese city of Shanghai and the city of Nottingham in the UK. The method is based principally on OpenStreetMap (OSM) and Advanced Land Observing Satellite World 3D digital surface model (AW3D DSM) data and use GMTED 2010 DTM data for undulating terrain. Further enhancement of the resultant 3D model, though not compulsory, uses higher resolution elevation models that are not always open source, but if available can be used (i.e., airborne LiDAR generated DTM). Further we test and develop methods to improve the accuracy of the generated 3D models, employing a small subset of high resolution data that are not open source but can be purchased with a minimal budgets. Given these scenarios of data availability are globally applicable and time-efficient for 3D building generation (where 2D building footprints are available), our proposed methodology has the potential to accelerate the production of 3D city models, and thus to facilitate their dependent applications (e.g., disaster management) wherever commercial 3D city models are unavailable.


Author(s):  
E. Muñumer Herrero ◽  
C. Ellul ◽  
J. Morley

<p><strong>Abstract.</strong> Popularity and diverse use of 3D city models has increased exponentially in the past few years, providing a more realistic impression and understanding of cities. Often, 3D city models are created by elevating the buildings from a detailed 2D topographic base map and subsequently used in studies such as solar panel allocation, infrastructure remodelling, antenna installations or even tourist guide applications. However, the large amount of resulting data slows down rendering and visualisation of the 3D models, and can also impact the performance of any analysis. Generalisation enables a reduction in the amount of data – however the addition of the third dimension makes this process more complex, and the loss of detail resulting from the process will inevitably have an impact on the result of any subsequent analysis.</p><p>While a few 3D generalization algorithms do exist in a research context, these are not available commercially. However, GIS users can create the generalised 3D models by simplifying and aggregating the 2D dataset first and then extruding it to the third dimension. This approach offers a rapid generalization process to create a dataset to underpin the impact of using generalised data for analysis. Specifically, in this study, the line of sight from a tall building and the sun shadow that it creates are calculated and compared, in both original and generalised datasets. The results obtained after the generalisation process are significant: both the number of polygons and the number of nodes are minimized by around 83<span class="thinspace"></span>% and the volume of 3D buildings is reduced by 14.87<span class="thinspace"></span>%. As expected, the spatial analyses processing times are also reduced. The study demonstrates the impact of generalisation on analytical results – which is particularly relevant in situations where detailed data is not available and will help to guide the development of future 3D generalisation algorithms. It also highlights some issues with the overall maturity of 3D analysis tools, which could be one factor limiting uptake of 3D GIS.</p>


Author(s):  
J. Yan ◽  
A. A. Diakité ◽  
S. Zlatanova

<p><strong>Abstract.</strong> The navigation of pedestrians can be regarded as their movements from one unoccupied space to another unoccupied and connected space. These movements generally occur in three types of environments: indoor, outdoor, and semi-bounded (top-bounded, and/or side-bounded) spaces. While the two former types of spaces are subject to most of the attention, the latter (semi-bounded) also presents a valuable impact on the navigation behaviour. For example, top-bounded environments (e.g. roofs, shelters, etc.) are very popular for pedestrian navigation since a top structure can offer protection from harsh weather, rain, or strong sun. However, such semibounded spaces are completely missing in current navigation models and systems. This is partly explained by the fact that modelling the space, which is by defining a three-dimensional boundless and extensible component (mainly out of the indoor environment), is a very challenging task. In this paper, we propose a structure-based approach for top-bounded space extraction in the built environment, relying on 3D models. Thanks to the rapid expansion and availability of 3D city models, our approach can help to account for such type of spaces in 3D pedestrian navigation systems.</p>


Author(s):  
G. Bitelli ◽  
V. A. Girelli ◽  
A. Lambertini

3D city models are becoming increasingly popular and important, because they constitute the base for all the visualization, planning, management operations regarding the urban infrastructure. These data are however not available in the majority of cities: in this paper, the possibility to use geospatial data of various kinds with the aim to generate 3D models in urban environment is investigated.<br> In 3D modelling works, the starting data are frequently the 3D point clouds, which are nowadays possible to collect by different sensors mounted on different platforms: LiDAR, imagery from satellite, airborne or unmanned aerial vehicles, mobile mapping systems that integrate several sensors. The processing of the acquired data and consequently the obtainability of models able to provide geometric accuracy and a good visual impact is limited by time, costs and logistic constraints.<br> Nowadays more and more innovative hardware and software solutions can offer to the municipalities and the public authorities the possibility to use available geospatial data, acquired for diverse aims, for the generation of 3D models of buildings and cities, characterized by different level of detail.<br> In the paper two cases of study are presented, both regarding surveys carried out in Emilia Romagna region, Italy, where 2D or 2.5D numerical maps are available. The first one is about the use of oblique aerial images realized by the Municipality for a systematic documentation of the built environment, the second concerns the use of LiDAR data acquired for other purposes; in the two tests, these data were used in conjunction with large scale numerical maps to produce 3D city models.


2013 ◽  
pp. 1011-1052 ◽  
Author(s):  
Juha Hyyppä ◽  
Lingli Zhu ◽  
Zhengjun Liu ◽  
Harri Kaartinen ◽  
Anttoni Jaakkola

Smartphones with larger screens, powerful processors, abundant memory, and an open operation system provide many possibilities for 3D city or photorealistic model applications. 3D city or photorealistic models can be used by the users to locate themselves in the 3D world, or they can be used as methods for visualizing the surrounding environment once a smartphone has already located the phone by other means, e.g. by using GNSS, and then to provide an interface in the form of a 3D model for the location-based services. In principle, 3D models can be also used for positioning purposes. For example, matching of images exported from the smartphone and then registering them in the existing 3D photorealistic world provides the position of the image capture. In that process, the central computer can do a similar image matching task when the users locate themselves interactively into the 3D world. As the benefits of 3D city models are obvious, this chapter demonstrates the technology used to provide photorealistic 3D city models and focus on 3D data acquisition and the methods available in 3D city modeling, and the development of 3D display technology for smartphone applications. Currently, global geoinformatic data providers, such as Google, Nokia (NAVTEQ), and TomTom (Tele Atlas), are expanding their products from 2D to 3D. This chapter is a presentation of a case study of 3D data acquisition, modeling and mapping, and visualization for a smartphone, including an example based on data collected by mobile laser scanning data from the Tapiola (Espoo, Finland) test field.


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