Major cities and urban areas are beginning to develop and use 3D properties and public facilities. Consequently, 3D cadastral surveys are increasingly being employed for strata unit ownership registration as a part of land administration services. At present, most national land information systems do not support 2D and 3D cadastral visualizations. A field survey or validation survey is required to determine the geometry of 3D spatial units for property registration. However, the results of 3D surveys and mapping are not stored in the land information system. This work aims to integrate 2D and 3D geospatial data of property units collected from cadastral surveys with their corresponding legal data. It reviews the workflow for the use of 3D survey data for first-titling of 3D properties in Indonesia. A scenario of use and a prototype were developed based on existing practices and the possibility of extending Indonesia’s Land Administration Domain Model (LADM) to represent 3D units. Data submitted to the prototype as 3D geometries was survey data from 3D cadastral surveys or validation surveys utilizing terrestrial survey methods. The prototype used PostGIS and Cesium Ion to store 3D geometries of data from six 3D surveys. Registrars in local land offices could use the prototype to undertake strata unit registration that establishes a relationship among geospatial features and their survey documents and legal documents. Cesium JS was used as a 3D browser, customized as a web application, to manage and visualize 3D survey data to support strata title registration. The results demonstrate that the first titling of 3D cadaster objects could be conducted and properly visualized in Indonesia by extending the existing LADM with more support for 3D spatial representations and survey documents.

This paper is focused to address the map display usability for finding given POI addresses in a popular urban city area. LOD 1 of 3D representations of city buildings are presented into a 2.5D map for pedestrian navigation test. This 3D map display is evaluated against familiar 2D map system on the test participants’ smartphones. 16 participants were involved in the field test. The typical walking model of a searching task that is focused only to look for a certain address of building is chosen as the way finding model during the field test. Three kinds of navigation processes i.e. self-orientation, spatial knowledge acquisition and navigation decision for searching task were evaluated for each test participant. Usability measures of 3D map-based display over 2D-map based display for pedestrian navigation were collected from test participants’ mobile devices. In addition to that, activities of test participants in terms of acceleration and orientation information are used to support analysis of pattern and trends of test participants. As the testing app is also intended to support smart city application, its ability to provide user report on complaints was also assessed. Most participants agreed with the statements in the questionnaire that were organized into three sections, i.e. addressing participants’ interaction, participants’ responses in navigation processes and crowdsensing. The results suggest that 3D map-based pedestrian navigation is more usable to be used to look for a certain address of building in central tourist area of urban city.

Indonesia is one of the nations located in the Ring of Fire. Indonesia has a high level of geodynamic activities so that it's often earthquake tectonics. The earthquakes are caused by Indonesia position located in the confluence of four main plates. At present, the history of earthquake data in Indonesia has been accessible by the public. However, general visualization which can present history earthquake in the form maps and summary statistics have not been available. Therefore, this research aims to visualize the history of earthquake data interactively combining spatial data and temporal data. The data used for this research was obtained from BMKG website. The data variables used in this research include CORS stations and history of earthquake phenomenons between 2004 and 2019. The earthquake phenomenon consists of occurrence time, coordinate position, depth and magnitude. The data are processed using Ms Excel and ArcGIS Online Map then are visualized by Web AppBuilder for ArcGIS. The results of the data processing are maps presented in a dashboard with time-series animation and widgets features. We performed maps, graphics and time-series animation as interactive visual interfaces and matched the tasks to visual analytics techniques that are capable to support them. In this paper, we introduce the relationship between variables and present the visual analytics techniques using several example scenarios of Spatio-temporal earthquake data.

The safety of autonomous vehicles (AVs) remains a major challenge, particularly within specific Operational Design Domains (ODDs). While physical testing lacks scalability, computer simulations effectively evaluate AV safety. However, most studies rely on virtual maps generated by simulation software, neglecting real-world complexities and focusing on single intersections rather than broader road networks. To fill the gap, this study lie in the development of a novel simulation workflow combining CARLA and VISSIM simulation softwares using High-definition (HD) maps while reducing data collection efforts and enabling the seamless integration of simulation results. Additionally, this study validates the effectiveness of emergency braking indicators within the AV simulation, confirming their applicability in assessing AV safety performance. The study area conducted near Tainan-City High-Speed Railway Station, Taiwan, analyzes emergency braking events across a network of three intersections and four road segments to identify high-risk zones. HD maps of the study area data were integrated into the CARLA to generate realistic traffic scenarios, while VISSIM modeled traffic flow and signal phases. The results indicate that emergency braking hotspots are concentrated at intersections, turns, and sharp curves near safety islands. This finding suggests that AVs make slower decisions than human drivers due to complex perception and computational models. Additionally, it highlights the importance of HD maps and traffic flow analysis in AV simulations and provides recommendations for improving AV safety, including simplifying road layouts, minimizing sharp turns, and restricting arbitrary lane changes.