Previous Issue

Table of Contents

ISPRS Int. J. Geo-Inf., Volume 8, Issue 5 (May 2019)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-42
Export citation of selected articles as:
Open AccessArticle
Spatiotemporal Pattern Analysis of China’s Cities Based on High-Resolution Imagery from 2000 to 2015
ISPRS Int. J. Geo-Inf. 2019, 8(5), 241; https://doi.org/10.3390/ijgi8050241 (registering DOI)
Received: 28 March 2019 / Revised: 30 April 2019 / Accepted: 14 May 2019 / Published: 22 May 2019
PDF Full-text (14902 KB) | HTML Full-text | XML Full-text
Abstract
The urbanization level in China has increased rapidly since beginning of the 21st century, and the monitoring and analysis of urban expansion has become a popular topic in geoscience applications. However, problems, such as inconsistent concepts and extraction standards, low precision, and poor [...] Read more.
The urbanization level in China has increased rapidly since beginning of the 21st century, and the monitoring and analysis of urban expansion has become a popular topic in geoscience applications. However, problems, such as inconsistent concepts and extraction standards, low precision, and poor comparability, existing in urban monitoring may lead to wrong conclusions. This study selects 337 cities at the prefecture level and above in China as research subjects and uses high-resolution images and geographic information data in a semi-automatic extraction method to identify urban areas in 2000, 2005, 2010, and 2015. City size distribution patterns, urban expansion regional characteristics, and expansion types are analyzed. Results show that Chinese cities maintained a high-speed growth trend from 2000 to 2015, with the total area increasing by 115.79%. The overall scale of a city continues to expand, and the system becomes increasingly complex. The urban system is more balanced than the ideal Zipf distribution, but it also exhibited different characteristics in 2005. Urban areas are mostly concentrated in the eastern and central regions, and the difference between the east and the west is considerable. However, cities in the western region continuously expand. Beijing, Shanghai, Tianjin, and Guangzhou are the four largest cities in China. Approximately 73.30% of the cities are expanding in an extended manner; the urban form tends to be scattered, and land use efficiency is low. The new urban areas mainly come from cultivated land and ecological land. Full article
Figures

Figure 1

Open AccessArticle
A Comparison Between Major Artificial Intelligence Models for Crop Yield Prediction: Case Study of the Midwestern United States, 2006–2015
ISPRS Int. J. Geo-Inf. 2019, 8(5), 240; https://doi.org/10.3390/ijgi8050240
Received: 10 April 2019 / Revised: 11 May 2019 / Accepted: 17 May 2019 / Published: 21 May 2019
Viewed by 90 | PDF Full-text (4691 KB) | HTML Full-text | XML Full-text
Abstract
This paper compares different artificial intelligence (AI) models in order to develop the best crop yield prediction model for the Midwestern United States (US). Through experiments to examine the effects of phenology using three different periods, we selected the July–August (JA) database as [...] Read more.
This paper compares different artificial intelligence (AI) models in order to develop the best crop yield prediction model for the Midwestern United States (US). Through experiments to examine the effects of phenology using three different periods, we selected the July–August (JA) database as the best months to predict corn and soybean yields. Six different AI models for crop yield prediction are tested in this research. Then, a comprehensive and objective comparison is conducted between the AI models. Particularly for the deep neural network (DNN) model, we performed an optimization process to ensure the best configurations for the layer structure, cost function, optimizer, activation function, and drop-out ratio. In terms of mean absolute error (MAE), our DNN model with the JA database was approximately 21–33% and 17–22% more accurate for corn and soybean yields, respectively, than the other five AI models. This indicates that corn and soybean yields for a given year can be forecasted in advance, at the beginning of September, approximately a month or more ahead of harvesting time. A combination of the optimized DNN model and spatial statistical methods should be investigated in future work, to mitigate partly clustered errors in some regions. Full article
Figures

Figure 1

Open AccessArticle
Heuristic Bike Optimization Algorithm to Improve Usage Efficiency of the Station-Free Bike Sharing System in Shenzhen, China
ISPRS Int. J. Geo-Inf. 2019, 8(5), 239; https://doi.org/10.3390/ijgi8050239
Received: 8 April 2019 / Revised: 8 May 2019 / Accepted: 17 May 2019 / Published: 21 May 2019
Viewed by 87 | PDF Full-text (8484 KB) | HTML Full-text | XML Full-text
Abstract
Station-free bike sharing systems (BSSs) are a new type of public bike system that has been widely deployed in China since 2017. However, rapid growth has vastly outpaced the immediate demand and overwhelmed many cities around the world. This paper proposes a heuristic [...] Read more.
Station-free bike sharing systems (BSSs) are a new type of public bike system that has been widely deployed in China since 2017. However, rapid growth has vastly outpaced the immediate demand and overwhelmed many cities around the world. This paper proposes a heuristic bike optimization algorithm (HBOA) to determine the optimal supply and distribution of bikes considering the effect of bicycle cycling. In this approach, the different bike trips with separate bikes can be connected in space and time and converted into a continuous trip chain for a single bike. To improve this cycling efficiency, it is important to properly design the bicycle distribution. Taking Shenzhen as an example, we implement the algorithm with OD matrix data from Mobike and Ofo, the two large bike sharing companies which account for 80% of the shared bike market in Shenzhen, over two days. The HBOA results are as follows. 1) Only one-fifth of the bike supply is needed to meet the current usage demand if the bikes are used efficiently, which means a large number of shared bikes in Shenzhen remain in an idle state for long periods. 2) Although the cycling demand is high in many areas, it does not mean that large numbers of bikes are needed because the continuous inflow caused by the cycling effect of bikes will meet most of the demand by itself. 3) The areas with the highest demands for optimal bikes are residential, followed by industrial, public transportation, official and commercial areas, on both working and non-working days. This algorithm can be an objective basis for city related departments to manage station-free BSSs and be applied to design the layout of bikes in small-scale spatial units to help station-free BSSs operate efficiently and minimize the need to relocate the bikes without reducing the level of user satisfaction. Full article
Figures

Figure 1

Open AccessArticle
Extracting Main Center Pattern from Road Networks Using Density-Based Clustering with Fuzzy Neighborhood
ISPRS Int. J. Geo-Inf. 2019, 8(5), 238; https://doi.org/10.3390/ijgi8050238
Received: 8 April 2019 / Revised: 6 May 2019 / Accepted: 17 May 2019 / Published: 21 May 2019
Viewed by 95 | PDF Full-text (7041 KB) | HTML Full-text | XML Full-text
Abstract
The spatial pattern is a kind of typical structural knowledge that reflects the distribution characteristics of object groups. As an important semantic pattern of road networks, the city center is significant to urban analysis, cartographic generalization and spatial data matching. Previous studies mainly [...] Read more.
The spatial pattern is a kind of typical structural knowledge that reflects the distribution characteristics of object groups. As an important semantic pattern of road networks, the city center is significant to urban analysis, cartographic generalization and spatial data matching. Previous studies mainly focus on the topological centrality calculation of road network graphs, and pay less attention to the delineation of main centers. Therefore, this study proposes an automatic recognition method of main center pattern in road networks. We firstly extract the main clusters from road nodes by improving the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) with fuzzy set theory. Moreover, the center area is generated with road meshes according to the area ratio with the covering discs of the main clusters. This proposed algorithm is applied to the road networks of a monocentric city and polycentric city respectively. The results show that our method is effective for identifying the main center pattern in the road networks. Furthermore, the contrast experiments demonstrate our method’s higher accuracy. Full article
Figures

Figure 1

Open AccessArticle
A Hybrid of Differential Evolution and Genetic Algorithm for the Multiple Geographical Feature Label Placement Problem
ISPRS Int. J. Geo-Inf. 2019, 8(5), 237; https://doi.org/10.3390/ijgi8050237
Received: 12 March 2019 / Revised: 15 May 2019 / Accepted: 18 May 2019 / Published: 21 May 2019
Viewed by 99 | PDF Full-text (2065 KB) | HTML Full-text | XML Full-text
Abstract
Label placement is a difficult problem in automated map production. Many methods have been proposed to automatically place labels for various types of maps. While the methods are designed to automatically and effectively generate labels for the point, line and area features, less [...] Read more.
Label placement is a difficult problem in automated map production. Many methods have been proposed to automatically place labels for various types of maps. While the methods are designed to automatically and effectively generate labels for the point, line and area features, less attention has been paid to the problem of jointly labeling all the different types of geographical features. In this paper, we refer to the labeling of all the graphic features as the multiple geographical feature label placement (MGFLP) problem. In the MGFLP problem, the overlapping and occlusion among labels and corresponding features produces poorly arranged labels, and results in a low-quality map. To solve the problem, a hybrid algorithm combining discrete differential evolution and the genetic algorithm (DDEGA) is proposed to search for an optimized placement that resolves the MGFLP problem. The quality of the proposed solution was evaluated using a weighted metric regarding a number of cartographical rules. Experiments were carried out to validate the performance of the proposed method in a set of cartographic tasks. The resulting label placement demonstrates the feasibility and the effectiveness of our method. Full article
(This article belongs to the Special Issue Smart Cartography for Big Data Solutions)
Figures

Figure 1

Open AccessArticle
Multi-Mode Two-Step Floating Catchment Area (2SFCA) Method to Measure the Potential Spatial Accessibility of Healthcare Services
ISPRS Int. J. Geo-Inf. 2019, 8(5), 236; https://doi.org/10.3390/ijgi8050236
Received: 22 April 2019 / Revised: 10 May 2019 / Accepted: 15 May 2019 / Published: 21 May 2019
Viewed by 99 | PDF Full-text (3360 KB) | HTML Full-text | XML Full-text
Abstract
While great progress in the development of a methodological approach to measure the accessibility of healthcare services has been made, the exclusion of the complex multi-mode travel behavior of urban residents and a rough calculation of travel costs from the origin to the [...] Read more.
While great progress in the development of a methodological approach to measure the accessibility of healthcare services has been made, the exclusion of the complex multi-mode travel behavior of urban residents and a rough calculation of travel costs from the origin to the destination limit its potential for making a detailed assessment, especially in urban areas. In this paper, we aim to describe and implement an enhanced method that enables the integration of multiple transportation modes into a two-step floating catchment area (2SFCA) method to estimate accessibility. We used a travel-mode choice survey, based on distance sections, to determine the complex multi-mode travel behavior of urban residents. Taking Nanjing as a study area, we proposed complete door-to-door approaches to determine every aspect of basic transportation modes. Additionally, we processed open data to implement an accurate computing of the origin-destination (OD) time cost. We applied the enhanced method to estimate the accessibility of residents to hospitals and compared it with three single-mode 2SFCA methods. The results showed that the proposed method effectively identified more accessibility details and provided more realistic accessibility values. Full article
Figures

Figure 1

Open AccessArticle
Analyzing Newspaper Maps for Earthquake News through Cartographic Approach
ISPRS Int. J. Geo-Inf. 2019, 8(5), 235; https://doi.org/10.3390/ijgi8050235
Received: 14 November 2018 / Revised: 10 April 2019 / Accepted: 5 May 2019 / Published: 21 May 2019
Viewed by 93 | PDF Full-text (12149 KB) | HTML Full-text | XML Full-text
Abstract
This study focuses on newspaper maps, which have an important role in conveying spatial information to newspaper readers. Maps and map-like items in the main Turkish newspapers within a certain period were evaluated in regard to the scope of the study. A database [...] Read more.
This study focuses on newspaper maps, which have an important role in conveying spatial information to newspaper readers. Maps and map-like items in the main Turkish newspapers within a certain period were evaluated in regard to the scope of the study. A database was constructed to organize the collected data and conduct the analysis. In addition to cartographic and thematic analyses, the database allows “georeferencing” to be conducted as well. However, the current study focused on the cartographic and thematic properties of these maps. Their deficiencies were identified from a cartographic perspective and with that, the parts of newspapers that maps are mostly included in were investigated, and we aimed to identify the topics and events that increase map usage in newspapers. For this purpose, maps of earthquake-related news were evaluated as a case study to show some spatial and thematic determinations. Thus, the contribution of newspapers to spatial thinking abilities and geographic knowledge of the readers was evaluated by cartographers. The study proves the importance of cartography in spreading knowledge through maps in newspapers. This opens up new possibilities for future studies to develop a different cartographic perspective on map usage and improve the geographic knowledge of newspaper readers. Full article
(This article belongs to the Special Issue Human-Centered Geovisual Analytics and Visuospatial Display Design)
Figures

Figure 1

Open AccessArticle
Anisotropic Diffusion for Improved Crime Prediction in Urban China
ISPRS Int. J. Geo-Inf. 2019, 8(5), 234; https://doi.org/10.3390/ijgi8050234
Received: 20 March 2019 / Revised: 5 May 2019 / Accepted: 14 May 2019 / Published: 20 May 2019
Viewed by 129 | PDF Full-text (12379 KB) | HTML Full-text | XML Full-text
Abstract
As a major social issue during urban development, crime is closely related to socioeconomic, geographic, and environmental factors. Traditional crime prediction models reveal the spatiotemporal dynamics of crime risks, but usually ignore the environmental context of the geographic areas where crimes occur. Therefore, [...] Read more.
As a major social issue during urban development, crime is closely related to socioeconomic, geographic, and environmental factors. Traditional crime prediction models reveal the spatiotemporal dynamics of crime risks, but usually ignore the environmental context of the geographic areas where crimes occur. Therefore, it is difficult to enhance the spatial accuracy of crime prediction. We propose the use of anisotropic diffusion to include environmental factors of the evaluated geographic area in the traditional crime prediction model, thereby aiming to predict crime occurrence at a finer scale regarding spatiotemporal aspects and environmental similarity. Under different evaluation criteria, the average prediction accuracy of the proposed method is 28.8%, improving prediction accuracy by 77.5%, as compared to the traditional methods. The proposed method can provide strong policing support in terms of conducting targeted hotspot policing and fostering sustainable community development. Full article
(This article belongs to the Special Issue Urban Crime Mapping and Analysis Using GIS)
Figures

Figure 1

Open AccessArticle
Obstacle-Aware Indoor Pathfinding Using Point Clouds
ISPRS Int. J. Geo-Inf. 2019, 8(5), 233; https://doi.org/10.3390/ijgi8050233
Received: 27 April 2019 / Revised: 13 May 2019 / Accepted: 15 May 2019 / Published: 19 May 2019
Viewed by 169 | PDF Full-text (9463 KB) | HTML Full-text | XML Full-text
Abstract
With the rise of urban population, updated spatial information of indoor environments is needed in a growing number of applications. Navigational assistance for disabled or aged people, guidance for robots, augmented reality for gaming, and tourism or training emergency assistance units are just [...] Read more.
With the rise of urban population, updated spatial information of indoor environments is needed in a growing number of applications. Navigational assistance for disabled or aged people, guidance for robots, augmented reality for gaming, and tourism or training emergency assistance units are just a few examples of the emerging applications requiring real three-dimensional (3D) spatial data of indoor scenes. This work proposes the use of point clouds for obstacle-aware indoor pathfinding. Point clouds are firstly used for reconstructing semantically rich 3D models of building structural elements in order to extract initial navigational information. Potential obstacles to navigation are classified in the point cloud and directly used to correct the path according to the mobility skills of different users. The methodology is tested in several real case studies for wheelchair and ordinary users. Experiments show that, after several iterations, paths are readapted to avoid obstacles. Full article
(This article belongs to the Special Issue Multidimensional and Multiscale GIS)
Figures

Figure 1

Open AccessArticle
Corporate Editors in the Evolving Landscape of OpenStreetMap
ISPRS Int. J. Geo-Inf. 2019, 8(5), 232; https://doi.org/10.3390/ijgi8050232
Received: 18 April 2019 / Revised: 8 May 2019 / Accepted: 14 May 2019 / Published: 18 May 2019
Viewed by 256 | PDF Full-text (2812 KB) | HTML Full-text | XML Full-text
Abstract
OpenStreetMap (OSM), the largest Volunteered Geographic Information project in the world, is characterized both by its map as well as the active community of the millions of mappers who produce it. The discourse about participation in the OSM community largely focuses on the [...] Read more.
OpenStreetMap (OSM), the largest Volunteered Geographic Information project in the world, is characterized both by its map as well as the active community of the millions of mappers who produce it. The discourse about participation in the OSM community largely focuses on the motivations for why members contribute map data and the resulting data quality. Recently, large corporations including Apple, Microsoft, and Facebook have been hiring editors to contribute to the OSM database. In this article, we explore the influence these corporate editors are having on the map by first considering the history of corporate involvement in the community and then analyzing historical quarterly-snapshot OSM-QA-Tiles to show where and what these corporate editors are mapping. Cumulatively, millions of corporate edits have a global footprint, but corporations vary in geographic reach, edit types, and quantity. While corporations currently have a major impact on road networks, non-corporate mappers edit more buildings and points-of-interest: representing the majority of all edits, on average. Since corporate editing represents the latest stage in the evolution of corporate involvement, we raise questions about how the OSM community—and researchers—might proceed as corporate editing grows and evolves as a mechanism for expanding the map for multiple uses. Full article
Figures

Graphical abstract

Open AccessArticle
Combining Water Fraction and DEM-Based Methods to Create a Coastal Flood Map: A Case Study of Hurricane Harvey
ISPRS Int. J. Geo-Inf. 2019, 8(5), 231; https://doi.org/10.3390/ijgi8050231
Received: 8 March 2019 / Revised: 27 April 2019 / Accepted: 14 May 2019 / Published: 18 May 2019
Viewed by 177 | PDF Full-text (4065 KB) | Supplementary Files
Abstract
Tropical cyclones are incredibly destructive and deadly, inflicting immense losses to coastal properties and infrastructure. Hurricane-induced coastal floods are often the biggest threat to life and the coastal environment. A quick and accurate estimation of coastal flood extent is urgently required for disaster [...] Read more.
Tropical cyclones are incredibly destructive and deadly, inflicting immense losses to coastal properties and infrastructure. Hurricane-induced coastal floods are often the biggest threat to life and the coastal environment. A quick and accurate estimation of coastal flood extent is urgently required for disaster rescue and emergency response. In this study, a combined Digital Elevation Model (DEM) based water fraction (DWF) method was implemented to simulate coastal floods during Hurricane Harvey on the South Texas coast. Water fraction values were calculated to create a 15 km flood map from multiple channels of the Advanced Technology Microwave Sound dataset. Based on hydrological inundation mechanism and topographic information, the coarse-resolution flood map derived from water fraction values was then downscaled to a high spatial resolution of 10 m. To evaluate the DWF result, Storm Surge Hindcast product and flood-reported high-water-mark observations were used. The results indicated a high overlapping area between the DWF map and buffered flood-reported high-water-marks (HWMs), with a percentage of more than 85%. Furthermore, the correlation coefficient between the DWF map and CERA SSH product was 0.91, which demonstrates a strong linear relationship between these two maps. The DWF model has a promising capacity to create high-resolution flood maps over large areas that can aid in emergency response. The result generated here can also be useful for flood risk management, especially through risk communication. Full article
Open AccessArticle
Recommendation of Heterogeneous Cultural Heritage Objects for the Promotion of Tourism
ISPRS Int. J. Geo-Inf. 2019, 8(5), 230; https://doi.org/10.3390/ijgi8050230
Received: 12 March 2019 / Revised: 6 April 2019 / Accepted: 5 May 2019 / Published: 17 May 2019
Viewed by 140 | PDF Full-text (1849 KB) | HTML Full-text | XML Full-text
Abstract
The cultural heritage of a region, be it a highly visited one or not, is a formidable asset for the promotion of its tourism. In many places around the world, an important part of this cultural heritage has been catalogued by initiatives backed [...] Read more.
The cultural heritage of a region, be it a highly visited one or not, is a formidable asset for the promotion of its tourism. In many places around the world, an important part of this cultural heritage has been catalogued by initiatives backed by governments and organisations. However, as of today, most of this data has been mostly unknown, or of difficult access, to the general public. In this paper, we present research that aims to leverage this data to promote tourism. Our first field of application focuses on the French Pyrenees. In order to achieve our goal, we worked on two fronts: (i) the ability to export this data from their original databases and data models to well-known open data platforms; and (ii) the proposition of an open-source algorithm and framework capable of recommending a sequence of cultural heritage points of interests (POIs) to be visited by tourists. This itinerary recommendation approach is original in many aspects: it not only considers the user preferences and popularity of POIs, but it also integrates different contextual information about the user as well as the relevance of specific sequences of POIs (strong links between POIs). The ability to export the cultural heritage data as open data and to recommend sequences of POIs are being integrated in a first prototype. Full article
(This article belongs to the Special Issue Open Science in the Geospatial Domain)
Figures

Figure 1

Open AccessArticle
Generating Different Urban Land Configurations Based on Heterogeneous Decisions of Private Land Developers: An Agent-Based Approach in a Developing Country Context
ISPRS Int. J. Geo-Inf. 2019, 8(5), 229; https://doi.org/10.3390/ijgi8050229
Received: 19 March 2019 / Revised: 30 April 2019 / Accepted: 8 May 2019 / Published: 16 May 2019
Viewed by 142 | PDF Full-text (10591 KB) | HTML Full-text | XML Full-text
Abstract
In the provision of urban residential areas, private land developers play critical roles in nearly all stages of the land development process. Despite their important role little is known about how the spatial decisions of individual developers collectively influence urban growth. This paper [...] Read more.
In the provision of urban residential areas, private land developers play critical roles in nearly all stages of the land development process. Despite their important role little is known about how the spatial decisions of individual developers collectively influence urban growth. This paper employs an agent-based modelling approach to capture the spatial decisions of private land developers in shaping new urban forms. By drawing on microeconomic theory, the model simulates urban growth in the Jakarta Metropolitan Area, Indonesia, under different scenarios that reflect the decision behaviours of different types of developers. Results reveal that larger developers favour sites that are more proximate to the city centre whilst smaller developers prefer sites that are located further away from the city, that drive a more sprawled urban form. Our findings show that new urban areas are generated by different developers through different processes. The profit maximisation behaviour by developers with large capital reserves is more predictable than those with small capital funds. The imbalance in capital holdings by different types of developers interacts with one another to exert adverse impacts on the urban development process. Our study provides supporting evidence highlighting the need for urban policy to regulate urban expansion and achieve more sustainable urban development outcomes in a developing world context. Full article
Figures

Graphical abstract

Open AccessArticle
A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam
ISPRS Int. J. Geo-Inf. 2019, 8(5), 228; https://doi.org/10.3390/ijgi8050228
Received: 22 February 2019 / Revised: 11 April 2019 / Accepted: 5 May 2019 / Published: 10 May 2019
Viewed by 313 | PDF Full-text (1564 KB)
Abstract
The early-warning model for flash floods is based on a hydrological and geomorphological concept connected to the river basin, with the principle that flash floods will only occur where there is a high potential risk and when rainfall exceeds the threshold. In the [...] Read more.
The early-warning model for flash floods is based on a hydrological and geomorphological concept connected to the river basin, with the principle that flash floods will only occur where there is a high potential risk and when rainfall exceeds the threshold. In the model used to build flash-floods risk maps, the parameters of the basin are analyzed and evaluated and the weight is determined using Thomas Saaty’s analytic hierarchy process (AHP). The flash-floods early-warning software is built using open source programming tools. With the spatial module and online processing, a predicted precipitation of one to six days in advance for iMETOS (AgriMedia—Vietnam) automatic meteorological stations is interpolated and then processed with the potential risk maps (iMETOS is a weather-environment monitoring system comprising a wide range of equipment and an online platform and can be used in various fields such as agriculture, tourism and services). The results determine the locations of flash floods at several risk levels corresponding to the predicted rainfall values at the meteorological stations. The system was constructed and applied to flash floods disaster early warning for Thuan Chau in Son La province when the rainfall exceeded the 150 mm/d threshold. The system initially supported positive decision-making to prevent and minimize damage caused by flash floods. Full article
(This article belongs to the Special Issue Natural Hazards and Geospatial Information)
Open AccessArticle
Prototype of the 3D Cadastral System Based on a NoSQL Database and a JavaScript Visualization Application
ISPRS Int. J. Geo-Inf. 2019, 8(5), 227; https://doi.org/10.3390/ijgi8050227
Received: 3 April 2019 / Revised: 4 May 2019 / Accepted: 8 May 2019 / Published: 10 May 2019
Viewed by 284 | PDF Full-text (4736 KB) | HTML Full-text | XML Full-text
Abstract
3D cadastral systems are more complex than traditional cadastral systems and they require more complex technical solutions and innovative use of developing technologies. Regarding data integrity and data consistency, 3D cadastral data should be maintained by a Database Management System (DBMS). Furthermore, there [...] Read more.
3D cadastral systems are more complex than traditional cadastral systems and they require more complex technical solutions and innovative use of developing technologies. Regarding data integrity and data consistency, 3D cadastral data should be maintained by a Database Management System (DBMS). Furthermore, there are still challenges regarding visualization of 3D cadastral data. A prototype of the 3D cadastral system based on a NoSQL database and a JavaScript application for 3D visualization is designed and tested in order to investigate the possibilities of using new technical solutions. It is assumed that this approach, with further development, could be a good basis for the development of a modern 3D cadastral system. MongoDB database is used for storing data and Cesium JavaScript library is used for 3D visualization. The system uses an LADM (Land Administration Domain Model) based data model. Additionally, script languages, libraries, application programming interfaces (APIs), software and data formats are used for the system development. The case study is based on the real cadastral data. The underground object and building units located below and above the ground level are used to test the proposed data model and the system’s functionality. The proposed system needs further development in order to provide full support to a modern 3D cadastral system. However, it allows maintenance of 3D cadastral data and basic 3D visualization with the interactive approach. Full article
(This article belongs to the Special Issue Applications of GIScience for Land Administration)
Figures

Figure 1

Open AccessArticle
GIS Mapping of Driving Behavior Based on Naturalistic Driving Data
ISPRS Int. J. Geo-Inf. 2019, 8(5), 226; https://doi.org/10.3390/ijgi8050226
Received: 14 March 2019 / Revised: 25 April 2019 / Accepted: 4 May 2019 / Published: 9 May 2019
Viewed by 273 | PDF Full-text (3502 KB) | HTML Full-text | XML Full-text
Abstract
Naturalistic driving can generate huge datasets with great potential for research. However, to analyze the collected data in naturalistic driving trials is quite complex and difficult, especially if we consider that these studies are commonly conducted by research groups with somewhat limited resources. [...] Read more.
Naturalistic driving can generate huge datasets with great potential for research. However, to analyze the collected data in naturalistic driving trials is quite complex and difficult, especially if we consider that these studies are commonly conducted by research groups with somewhat limited resources. It is quite common that these studies implement strategies for thinning and/or reducing the data volumes that have been initially collected. Thus, and unfortunately, the great potential of these datasets is significantly constrained to specific situations, events, and contexts. For this, to implement appropriate strategies for the visualization of these data is becoming increasingly necessary, at any scale. Mapping naturalistic driving data with Geographic Information Systems (GIS) allows for a deeper understanding of our driving behavior, achieving a smarter and broader perspective of the whole datasets. GIS mapping allows for many of the existing drawbacks of the traditional methodologies for the analysis of naturalistic driving data to be overcome. In this article, we analyze which are the main assets related to GIS mapping of such data. These assets are dominated by the powerful interface graphics and the great operational capacity of GIS software. Full article
(This article belongs to the Special Issue Smart Cartography for Big Data Solutions)
Figures

Figure 1

Open AccessArticle
A Convenient Tool for District Heating Route Optimization Based on Parallel Ant Colony System Algorithm and 3D WebGIS
ISPRS Int. J. Geo-Inf. 2019, 8(5), 225; https://doi.org/10.3390/ijgi8050225
Received: 6 March 2019 / Revised: 23 April 2019 / Accepted: 4 May 2019 / Published: 9 May 2019
Viewed by 181 | PDF Full-text (9315 KB) | HTML Full-text | XML Full-text
Abstract
In a district heating engineering project, the design of the heating route is an indispensable but laborious process. This paper proposes a planning indicator to measure the suitability of a candidate heating route, and provides an intelligent method and a convenient tool for [...] Read more.
In a district heating engineering project, the design of the heating route is an indispensable but laborious process. This paper proposes a planning indicator to measure the suitability of a candidate heating route, and provides an intelligent method and a convenient tool for the preliminary design of the district heating route. The Fengrun heating engineering project was chosen as a case study. The remote sensing imagery and OpenStreetMap were used as the data sources. First, the remote sensing imagery was classified into five classes and converted into binary images. Second, the district heating route planning indicator was defined based on the cost function. The cost function and the updating strategy of the ant colony system algorithm were modified according to the heating route selection requirement. Additionally, the parallel computing technology was adopted to improve the efficiency. With the help of the open source Cesium engine and the three-dimensional (3D) WebGIS technology, an interactive route design platform that combined our algorithm was finally provided. The optimum routes by the platform were compared to the corresponding sequential algorithm, the route selected manually, as well as the commercial ArcGIS platform. The proposed algorithm can get 28 candidate routes with better indicator values than the manually selected route. Compared to the corresponding sequential algorithm, our algorithm improved the efficiency by 4.789 times. The proposed 3D WebGIS tool is more applicable and user-friendly for the heating route design. Full article
Figures

Figure 1

Open AccessArticle
Top-Bounded Spaces Formed by the Built Environment for Navigation Systems
ISPRS Int. J. Geo-Inf. 2019, 8(5), 224; https://doi.org/10.3390/ijgi8050224
Received: 3 March 2019 / Revised: 11 April 2019 / Accepted: 5 May 2019 / Published: 9 May 2019
Viewed by 201 | PDF Full-text (10321 KB) | HTML Full-text | XML Full-text
Abstract
Navigation systems help agents find the right (optimal) path from the origin to the desired destination. Current navigation systems mainly offer the shortest (distance or time) path as the default optimal path. However, under certain circumstances, having a least-top-exposed path can be more [...] Read more.
Navigation systems help agents find the right (optimal) path from the origin to the desired destination. Current navigation systems mainly offer the shortest (distance or time) path as the default optimal path. However, under certain circumstances, having a least-top-exposed path can be more interesting. For instance, on a rainy day, a path with as many places as possible covered by roofs/shelters is more attractive and pragmatic, since roofs/shelters can offer protection from rain. In this paper, we name environments that covered by roofs/shelters but not completely enclosed like indoors as “top-bounded environments/spaces” (e.g., porches), which are generally formed by built structures. This kind of space is completely missing in current navigation models and systems. Thus, we investigate how to use it for space-based navigation. After proposing a definition, a space model, and attributes of top-bounded spaces, we introduce a projection-based approach to generate them. Then, taking a pedestrian as an example agent, we select generated spaces considering whether the agent can visit/use the identified spaces. Finally, examples and a use case study demonstrate that our research can help to include top-bounded spaces in navigation systems/models. More navigation path types (e.g., least-top-exposed) can be offered for different agents (such as pedestrians, drones or robots). Full article
Figures

Figure 1

Open AccessArticle
The Spatial Equity of Nursing Homes in Changchun: A Multi-Trip Modes Analysis
ISPRS Int. J. Geo-Inf. 2019, 8(5), 223; https://doi.org/10.3390/ijgi8050223
Received: 25 January 2019 / Revised: 2 April 2019 / Accepted: 6 May 2019 / Published: 9 May 2019
Viewed by 218 | PDF Full-text (2578 KB) | HTML Full-text | XML Full-text
Abstract
Based on network analysis, different trip modes were integrated into an improved potential model, and the geography of the spatial equity of nursing homes in Changchun is explored in 5-min, 10-min and 15-min scenarios, respectively. Results show that: (1) trip modes have significant [...] Read more.
Based on network analysis, different trip modes were integrated into an improved potential model, and the geography of the spatial equity of nursing homes in Changchun is explored in 5-min, 10-min and 15-min scenarios, respectively. Results show that: (1) trip modes have significant influence on spatial equity and that the geography of spatial equity varied with trip modes; (2) the spatial equity value in Changchun is overall kept to a very low level. Most areas in urban fringes and urban core areas belong to underserved areas, and the capacity of nursing home, travel cost and the number of seniors, are the main influencing factors; (3) the geography of spatial equity in different scenarios show a very similar ring structure; namely, the spatial equity value within the urban core and at the most urban periphery is lower than that in intermediate areas. The hot spot analysis showed that the southwest urban fringes and east of the urban core are hot spot areas, while the urban core itself has cold spot areas. Full article
(This article belongs to the Special Issue Human-Centric Data Science for Urban Studies)
Figures

Figure 1

Open AccessArticle
Reliability Analysis of LandScan Gridded Population Data. The Case Study of Poland
ISPRS Int. J. Geo-Inf. 2019, 8(5), 222; https://doi.org/10.3390/ijgi8050222
Received: 22 March 2019 / Revised: 23 April 2019 / Accepted: 4 May 2019 / Published: 8 May 2019
Viewed by 179 | PDF Full-text (4879 KB) | HTML Full-text | XML Full-text
Abstract
The issue of population dataset reliability is of particular importance when it comes to broadening the understanding of spatial structure, pattern and configuration of humans’ geographical location. The aim of the paper was to estimate the reliability of LandScan based on the official [...] Read more.
The issue of population dataset reliability is of particular importance when it comes to broadening the understanding of spatial structure, pattern and configuration of humans’ geographical location. The aim of the paper was to estimate the reliability of LandScan based on the official Polish Population Grid. The adopted methodology was based on the change detection approach, spatial pattern and continuity analysis, as well as statistical analysis at the grid-cell level. Our results show that the LandScan data can estimate the Polish population very well. The number of grid cells with equal people counts in both datasets amounts to 10.5%. The most and highly reliable data cover 72% of the country territory, while less reliable ones cover only 4.3%. The LandScan algorithm tends to underestimate people counts, with a total value of 79,735 people (0.21%). The highest underestimation was noticed in densely populated areas as well as in the transition areas between urban and rural, while overestimation was observed in moderately populated regions, along main roads and in city centres. The underestimation results mainly from the spatial pattern and size of Polish rural settlements, namely a big number of shadowed single households dispersed over agricultural areas and in the vicinity of forests. An excessive assessment of the number of people may be a consequence of the well-known blooming effect. Full article
Figures

Figure 1

Open AccessArticle
Automated Multi-Sensor 3D Reconstruction for the Web
ISPRS Int. J. Geo-Inf. 2019, 8(5), 221; https://doi.org/10.3390/ijgi8050221
Received: 21 March 2019 / Revised: 12 April 2019 / Accepted: 4 May 2019 / Published: 8 May 2019
Viewed by 380 | PDF Full-text (5183 KB) | HTML Full-text | XML Full-text
Abstract
The Internet has become a major dissemination and sharing platform for 3D content. The utilization of 3D measurement methods can drastically increase the production efficiency of 3D content in an increasing number of use cases where 3D documentation of real-life objects or environments [...] Read more.
The Internet has become a major dissemination and sharing platform for 3D content. The utilization of 3D measurement methods can drastically increase the production efficiency of 3D content in an increasing number of use cases where 3D documentation of real-life objects or environments is required. We demonstrated a developed, highly automated and integrated content creation process of providing reality-based photorealistic 3D models for the web. Close-range photogrammetry, terrestrial laser scanning (TLS) and their combination are compared using available state-of-the-art tools in a real-life project setting with real-life limitations. Integrating photogrammetry and TLS is a good compromise for both geometric and texture quality. Compared to approaches using only photogrammetry or TLS, it is slower and more resource-heavy but combines complementary advantages of each method, such as direct scale determination from TLS or superior image quality typically used in photogrammetry. The integration is not only beneficial, but clearly productionally possible using available state-of-the-art tools that have become increasingly available also for non-expert users. Despite the high degree of automation, some manual editing steps are still required in practice to achieve satisfactory results in terms of adequate visual quality. This is mainly due to the current limitations of WebGL technology. Full article
Figures

Figure 1

Open AccessArticle
Spatial Interaction Modeling of OD Flow Data: Comparing Geographically Weighted Negative Binomial Regression (GWNBR) and OLS (GWOLSR)
ISPRS Int. J. Geo-Inf. 2019, 8(5), 220; https://doi.org/10.3390/ijgi8050220
Received: 7 February 2019 / Revised: 23 April 2019 / Accepted: 4 May 2019 / Published: 8 May 2019
Viewed by 212 | PDF Full-text (3864 KB) | HTML Full-text | XML Full-text
Abstract
Due to the emergence of new big data technology, mobility data such as flows between origin and destination areas have increasingly become more available, cheaper, and faster. These improvements to data infrastructure have boosted spatial and temporal modeling of OD (origin-destination) flows, which [...] Read more.
Due to the emergence of new big data technology, mobility data such as flows between origin and destination areas have increasingly become more available, cheaper, and faster. These improvements to data infrastructure have boosted spatial and temporal modeling of OD (origin-destination) flows, which require the consideration of spatial dependence and heterogeneity. Both ordinary least square (OLS) and negative binomial (NB) regression methods have been used extensively to calibrate OD flow models by processing flow data as different types of dependent variables. This paper aims to compare both global and local spatial interaction modeling of OD flows between traditional and geographically weighted OLS (GWOLSR) and NB (GWNBR) modeling methods. From this study with empirical data it is concluded that GWNBR outperforms GWOLSR in reducing spatial autocorrelation and in detecting spatial non-stationarity. Although, it is noted that both local modeling methods show improvement when compared against the equivalent global models. Full article
Figures

Figure 1

Open AccessArticle
Integrated UAV-Based Real-Time Mapping for Security Applications
ISPRS Int. J. Geo-Inf. 2019, 8(5), 219; https://doi.org/10.3390/ijgi8050219
Received: 17 February 2019 / Revised: 23 April 2019 / Accepted: 2 May 2019 / Published: 8 May 2019
Viewed by 218 | PDF Full-text (8046 KB) | HTML Full-text | XML Full-text
Abstract
Security applications such as management of natural disasters and man-made incidents crucially depend on the rapid availability of a situation picture of the affected area. UAV-based remote sensing systems may constitute an essential tool for capturing aerial imagery in such scenarios. While several [...] Read more.
Security applications such as management of natural disasters and man-made incidents crucially depend on the rapid availability of a situation picture of the affected area. UAV-based remote sensing systems may constitute an essential tool for capturing aerial imagery in such scenarios. While several commercial UAV solutions already provide acquisition of high quality photos or real-time video transmission via radio link, generating instant high-resolution aerial maps is still an open challenge. For this purpose, the article presents a real-time processing tool chain, enabling generation of interactive aerial maps during flight. Key element of this tool chain is the combination of the Terrain Aware Image Clipping (TAC) algorithm and 12-bit JPEG compression. As a result, the data size of a common scenery can be reduced to approximately 0.4% of the original size, while preserving full geometric and radiometric resolution. Particular attention was paid to minimize computational costs to reduce hardware requirements. The full workflow was demonstrated using the DLR Modular Airborne Camera System (MACS) operated on a conventional aircraft. In combination with a commercial radio link, the latency between image acquisition and visualization in the ground station was about 2 s. In addition, the integration of a miniaturized version of the camera system into a small fixed-wing UAV is presented. It is shown that the described workflow is efficient enough to instantly generate image maps even on small UAV hardware. Using a radio link, these maps can be broadcasted to on-site operation centers and are immediately available to the end-users. Full article
(This article belongs to the Special Issue Innovative Sensing - From Sensors to Methods and Applications)
Figures

Figure 1

Open AccessArticle
NS-DBSCAN: A Density-Based Clustering Algorithm in Network Space
ISPRS Int. J. Geo-Inf. 2019, 8(5), 218; https://doi.org/10.3390/ijgi8050218
Received: 27 March 2019 / Accepted: 5 May 2019 / Published: 8 May 2019
Viewed by 160 | PDF Full-text (4748 KB) | HTML Full-text | XML Full-text
Abstract
Spatial clustering analysis is an important spatial data mining technique. It divides objects into clusters according to their similarities in both location and attribute aspects. It plays an essential role in density distribution identification, hot-spot detection, and trend discovery. Spatial clustering algorithms in [...] Read more.
Spatial clustering analysis is an important spatial data mining technique. It divides objects into clusters according to their similarities in both location and attribute aspects. It plays an essential role in density distribution identification, hot-spot detection, and trend discovery. Spatial clustering algorithms in the Euclidean space are relatively mature, while those in the network space are less well researched. This study aimed to present a well-known clustering algorithm, named density-based spatial clustering of applications with noise (DBSCAN), to network space and proposed a new clustering algorithm named network space DBSCAN (NS-DBSCAN). Basically, the NS-DBSCAN algorithm used a strategy similar to the DBSCAN algorithm. Furthermore, it provided a new technique for visualizing the density distribution and indicating the intrinsic clustering structure. Tested by the points of interest (POI) in Hanyang district, Wuhan, China, the NS-DBSCAN algorithm was able to accurately detect the high-density regions. The NS-DBSCAN algorithm was compared with the classical hierarchical clustering algorithm and the recently proposed density-based clustering algorithm with network-constraint Delaunay triangulation (NC_DT) in terms of their effectiveness. The hierarchical clustering algorithm was effective only when the cluster number was well specified, otherwise it might separate a natural cluster into several parts. The NC_DT method excessively gathered most objects into a huge cluster. Quantitative evaluation using four indicators, including the silhouette, the R-squared index, the Davis–Bouldin index, and the clustering scheme quality index, indicated that the NS-DBSCAN algorithm was superior to the hierarchical clustering and NC_DT algorithms. Full article
(This article belongs to the Special Issue Spatial Databases: Design, Management, and Knowledge Discovery)
Figures

Figure 1

Open AccessArticle
Why Shape Matters—On the Inherent Qualities of Geometric Shapes for Cartographic Representations
ISPRS Int. J. Geo-Inf. 2019, 8(5), 217; https://doi.org/10.3390/ijgi8050217
Received: 15 November 2018 / Revised: 23 April 2019 / Accepted: 2 May 2019 / Published: 8 May 2019
Viewed by 259 | PDF Full-text (1328 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
All human communication involves the use of signs. By following a mutually shared set of signs and rules, meaning can be conveyed from one entity to another. Cartographic semiology provides such a theoretical framework, suggesting how to apply visual variables with respect to [...] Read more.
All human communication involves the use of signs. By following a mutually shared set of signs and rules, meaning can be conveyed from one entity to another. Cartographic semiology provides such a theoretical framework, suggesting how to apply visual variables with respect to thematic content. However, semiotics does not address how the choice and composition of such visual variables may lead to different connotations, interpretations, or judgments. The research herein aimed to identify perceived similarities between geometric shape symbols as well as strategies and processes underlying these similarity judgments. Based on a user study with 38 participants, the (dis)similarities of a set of 12 basic geometric shapes (e.g., circle, triangle, square) were examined. Findings from cluster analysis revealed a three-cluster configuration, while multidimensional scaling further quantified the proximities between the geometric shapes in a two-dimensional space. Qualitative and quantitative content analyses identified four strategies underlying the participants’ similarity judgments, namely visual, affective, associative, and behavioral strategies. With the findings combined, this research provides a differentiated perspective on shape proximities, cognitive relations, and the processes involved. Full article
(This article belongs to the Special Issue Human-Centered Geovisual Analytics and Visuospatial Display Design)
Figures

Figure 1

Open AccessArticle
Constructing Geographic Dictionary from Streaming Geotagged Tweets
ISPRS Int. J. Geo-Inf. 2019, 8(5), 216; https://doi.org/10.3390/ijgi8050216
Received: 28 March 2019 / Revised: 22 April 2019 / Accepted: 2 May 2019 / Published: 8 May 2019
Viewed by 184 | PDF Full-text (4092 KB) | HTML Full-text | XML Full-text
Abstract
Geographic information, such as place names with their latitude and longitude (lat/long), is useful to understand what belongs where. Traditionally, Gazetteers, which are constructed manually by experts, are used as dictionaries containing such geographic information. Recently, since people often post about their current [...] Read more.
Geographic information, such as place names with their latitude and longitude (lat/long), is useful to understand what belongs where. Traditionally, Gazetteers, which are constructed manually by experts, are used as dictionaries containing such geographic information. Recently, since people often post about their current experiences in a short text format to microblogs, their geotagged (tagged with lat/long information) posts are aggregated to automatically construct geographic dictionaries containing more diverse types of information, such as local products and events. Generally, the geotagged posts are collected within a certain time interval. Then, the spatial locality of every word used in the collected geotagged posts is examined to obtain the local words, representing places, events, etc., which are observed at specific locations by the users. However, focusing on a specific time interval limits the diversity and accuracy of the extracted local words. Further, bot accounts in microblogs can largely affect the spatial locality of the words used in their posts. In order to handle such problems, we propose an online method for continuously update the geographic dictionary by adaptively determining suitable time intervals for examining the spatial locality of each word. The proposed method further filters out the geotagged posts from bot accounts based on the content similarity among their posts to improve the quality of extracted local words. The constructed geographic dictionary is compared with different geographic dictionaries constructed by experts, crowdsourcing, and automatically by focusing on a specific time interval to evaluate its quality. Full article
Figures

Figure 1

Open AccessArticle
Online Map Services: Contemporary Cartography or a New Cartographic Culture?
ISPRS Int. J. Geo-Inf. 2019, 8(5), 215; https://doi.org/10.3390/ijgi8050215
Received: 28 March 2019 / Revised: 30 April 2019 / Accepted: 2 May 2019 / Published: 7 May 2019
Viewed by 214 | PDF Full-text (10372 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, online map services are reviewed from a cartographic point of view. The most popular online map services are selected based on worldwide website traffic data, provided by specialized sites, such as Similarweb, in terms of global coverage and popularity among [...] Read more.
In this paper, online map services are reviewed from a cartographic point of view. The most popular online map services are selected based on worldwide website traffic data, provided by specialized sites, such as Similarweb, in terms of global coverage and popularity among users. Online map services are commented based on cartographic principles, conventions and traditional practices addressing topics, such as: Cartographic projection, orientation, scale, marginalia, content (thematic layers), symbology, generalization, annotation, color use and overall map design. Color schemes utilized in web maps are discussed in more detail, since based on studies concerning the selection of the preferable map by experts and laymen, color is undisputedly the most frequently mentioned factor. It can be stated that online map services generally adopt well-known cartographic practices, which are not always applied as expected. Moreover, suggestions for the improvement of online map services are made regarding cartographic projection, legend, content, symbolization, color, etc. Full article
Figures

Graphical abstract

Open AccessArticle
Bicycle Level of Service for Route Choice—A GIS Evaluation of Four Existing Indicators with Empirical Data
ISPRS Int. J. Geo-Inf. 2019, 8(5), 214; https://doi.org/10.3390/ijgi8050214
Received: 3 March 2019 / Revised: 9 April 2019 / Accepted: 4 May 2019 / Published: 7 May 2019
Viewed by 219 | PDF Full-text (2067 KB)
Abstract
Bicycle Level of Service (BLOS) indicators are used to provide objective ratings of the bicycle suitability (or quality) of links or intersections in transport networks. This article uses empirical bicycle route choice data from 467 university students in Trondheim, Norway to test the [...] Read more.
Bicycle Level of Service (BLOS) indicators are used to provide objective ratings of the bicycle suitability (or quality) of links or intersections in transport networks. This article uses empirical bicycle route choice data from 467 university students in Trondheim, Norway to test the applicability of BLOS rating schemes for the estimation of whole-journey route choice. The methods evaluated share a common trait of being applicable for mixed traffic urban environments: Bicycle Compatibility Index (BCI), Bicycle Stress Level (BSL), Sixth Edition Highway Capacity Manual (HCM6), and Level of Traffic Stress (LTS). Routes are generated based on BLOS-weighted networks and the suitability of these routes is determined by finding the percentage overlap with empirical route choices. The results show that BCI provides the best match with empirical route data in all five origin–destination pairs, followed by HCM6. BSL and LTS which are not empirically founded have a lower match rate, although the differences between the four methods are relatively small. By iterating the detour rate that cyclists are assumed to be willing to make, it is found that the best match with modeled BLOS routes is achieved between 15 and 21% additional length. This falls within the range suggested by existing empirical research on willingness to deviate from the shortest path, however, it is uncertain whether the method will deliver the comparable findings in other cycling environments. Full article
(This article belongs to the Special Issue Human-Centric Data Science for Urban Studies)
Open AccessArticle
Voxel-based 3D Point Cloud Semantic Segmentation: Unsupervised Geometric and Relationship Featuring vs Deep Learning Methods
ISPRS Int. J. Geo-Inf. 2019, 8(5), 213; https://doi.org/10.3390/ijgi8050213
Received: 6 March 2019 / Revised: 11 April 2019 / Accepted: 3 May 2019 / Published: 7 May 2019
Viewed by 453 | PDF Full-text (16010 KB) | HTML Full-text | XML Full-text
Abstract
Automation in point cloud data processing is central in knowledge discovery within decision-making systems. The definition of relevant features is often key for segmentation and classification, with automated workflows presenting the main challenges. In this paper, we propose a voxel-based feature engineering that [...] Read more.
Automation in point cloud data processing is central in knowledge discovery within decision-making systems. The definition of relevant features is often key for segmentation and classification, with automated workflows presenting the main challenges. In this paper, we propose a voxel-based feature engineering that better characterize point clusters and provide strong support to supervised or unsupervised classification. We provide different feature generalization levels to permit interoperable frameworks. First, we recommend a shape-based feature set (SF1) that only leverages the raw X, Y, Z attributes of any point cloud. Afterwards, we derive relationship and topology between voxel entities to obtain a three-dimensional (3D) structural connectivity feature set (SF2). Finally, we provide a knowledge-based decision tree to permit infrastructure-related classification. We study SF1/SF2 synergy on a new semantic segmentation framework for the constitution of a higher semantic representation of point clouds in relevant clusters. Finally, we benchmark the approach against novel and best-performing deep-learning methods while using the full S3DIS dataset. We highlight good performances, easy-integration, and high F1-score (> 85%) for planar-dominant classes that are comparable to state-of-the-art deep learning. Full article
Figures

Graphical abstract

Open AccessArticle
An Occupancy Simulator for a Smart Parking System: Developmental Design and Experimental Considerations
ISPRS Int. J. Geo-Inf. 2019, 8(5), 212; https://doi.org/10.3390/ijgi8050212
Received: 2 April 2019 / Revised: 26 April 2019 / Accepted: 3 May 2019 / Published: 7 May 2019
Viewed by 205 | PDF Full-text (3121 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents the development of a parking occupancy simulator to support a smart parking system. The simulator uses an agent-based approach to model drivers who follow activity plans and who may or may not use the smart parking system. We illustrate how [...] Read more.
This paper presents the development of a parking occupancy simulator to support a smart parking system. The simulator uses an agent-based approach to model drivers who follow activity plans and who may or may not use the smart parking system. We illustrate how the process of developing our simulator helped in the design and implementation of the smart parking system components. The paper also shows how the simulator was used to study the possible usage of the smart parking system in a university campus, foreseeing (1) support for the smart parking system’s overall suitability, (2) reservation guarantee violation problems, and (3) the value of using total traveled distance as a metric for the smart parking evaluation. The experience presented in this paper may prove valuable to teams planning the development of a smart parking system for similar contexts. Full article
Figures

Figure 1

ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top