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Volume 9
Issue 3
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ISPRS Int. J. Geo-Inf., Volume 9, Issue 3 (March 2020) – 48 articles

Cover Story (view full-size image): The paper reviews the progress made over the past five years in two very active areas of research: geospatial semantic information modeling and elicitation. Information modeling refers to the development of ontologies at different levels of generality and formality, tailored to various needs and uses. Elicitation involves a set of processes that aim to draw out latent knowledge from unstructured or semistructured resources: semantic-based extraction, enrichment, search, and analysis. Modeling and elicitation may be used synergistically to enhance both: Extracted information is used to improve and enrich an ontology, which in turn is used to refine the information elicitation results. The paper discusses the challenges faced, highlights the methodologies and tools used, and identifies directions for future research.View this paper.
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18 pages, 5041 KiB  
Article
Recent Sea Level Change in the Black Sea from Satellite Altimetry and Tide Gauge Observations
by Nevin Betül Avşar and Şenol Hakan Kutoğlu
ISPRS Int. J. Geo-Inf. 2020, 9(3), 185; https://doi.org/10.3390/ijgi9030185 - 24 Mar 2020
Cited by 14 | Viewed by 6713
Abstract
Global mean sea level has been rising at an increasing rate, especially since the early 19th century in response to ocean thermal expansion and ice sheet melting. The possible consequences of sea level rise pose a significant threat to coastal cities, inhabitants, infrastructure, [...] Read more.
Global mean sea level has been rising at an increasing rate, especially since the early 19th century in response to ocean thermal expansion and ice sheet melting. The possible consequences of sea level rise pose a significant threat to coastal cities, inhabitants, infrastructure, wetlands, ecosystems, and beaches. Sea level changes are not geographically uniform. This study focuses on present-day sea level changes in the Black Sea using satellite altimetry and tide gauge data. The multi-mission gridded satellite altimetry data from January 1993 to May 2017 indicated a mean rate of sea level rise of 2.5 ± 0.5 mm/year over the entire Black Sea. However, when considering the dominant cycles of the Black Sea level time series, an apparent (significant) variation was seen until 2014, and the rise in the mean sea level has been estimated at about 3.2 ± 0.6 mm/year. Coastal sea level, which was assessed using the available data from 12 tide gauge stations, has generally risen (except for the Bourgas Station). For instance, from the western coast to the southern coast of the Black Sea, in Constantza, Sevastopol, Tuapse, Batumi, Trabzon, Amasra, Sile, and Igneada, the relative rise was 3.02, 1.56, 2.92, 3.52, 2.33, 3.43, 5.03, and 6.94 mm/year, respectively, for varying periods over 1922–2014. The highest and lowest rises in the mean level of the Black Sea were in Poti (7.01 mm/year) and in Varna (1.53 mm/year), respectively. Measurements from six Global Navigation Satellite System (GNSS) stations, which are very close to the tide gauges, also suggest that there were significant vertical land movements at some tide gauge locations. This study confirmed that according to the obtained average annual phase value of sea level observations, seasonal sea level variations in the Black Sea reach their maximum annual amplitude in May–June. Full article
(This article belongs to the Special Issue GI for Disaster Management)
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16 pages, 6507 KiB  
Article
Uber Movement Data: A Proxy for Average One-way Commuting Times by Car
by Yeran Sun, Yinming Ren and Xuan Sun
ISPRS Int. J. Geo-Inf. 2020, 9(3), 184; https://doi.org/10.3390/ijgi9030184 - 24 Mar 2020
Cited by 7 | Viewed by 4144
Abstract
Recently, Uber released datasets named Uber Movement to the public in support of urban planning and transportation planning. To prevent user privacy issues, Uber aggregates car GPS traces into small areas. After aggregating car GPS traces into small areas, Uber releases free data [...] Read more.
Recently, Uber released datasets named Uber Movement to the public in support of urban planning and transportation planning. To prevent user privacy issues, Uber aggregates car GPS traces into small areas. After aggregating car GPS traces into small areas, Uber releases free data products that indicate the average travel times of Uber cars between two small areas. The average travel times of Uber cars in the morning peak time periods on weekdays could be used as a proxy for average one-way car-based commuting times. In this study, to demonstrate usefulness of Uber Movement data, we use Uber Movement data as a proxy for commuting time data by which commuters’ average one-way commuting time across Greater Boston can be figured out. We propose a new approach to estimate the average car-based commuting times through combining commuting times from Uber Movement data and commuting flows from travel survey data. To further demonstrate the applicability of the commuting times estimated by Uber movement data, this study further measures the spatial accessibility of jobs by car by aggregating place-to-place commuting times to census tracts. The empirical results further uncover that 1) commuters’ average one-way commuting time is around 20 min across Greater Boston; 2) more than 75% of car-based commuters are likely to have a one-way commuting time of less than 30 min; 3) less than 1% of car-based commuters are likely to have a one-way commuting time of more than 60 min; and 4) the areas suffering a lower level of spatial accessibility of jobs by car are likely to be evenly distributed across Greater Boston. Full article
(This article belongs to the Special Issue Recent Trends in Location Based Services and Science)
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14 pages, 8590 KiB  
Article
Spatio-Temporal Analysis of Intense Convective Storms Tracks in a Densely Urbanized Italian Basin
by Matteo Sangiorgio and Stefano Barindelli
ISPRS Int. J. Geo-Inf. 2020, 9(3), 183; https://doi.org/10.3390/ijgi9030183 - 24 Mar 2020
Cited by 10 | Viewed by 9678
Abstract
Intense convective storms usually produce large rainfall volumes in short time periods, increasing the risk of floods and causing damages to population, buildings, and infrastructures. In this paper, we propose a framework to couple visual and statistical analyses of convective thunderstorms at the [...] Read more.
Intense convective storms usually produce large rainfall volumes in short time periods, increasing the risk of floods and causing damages to population, buildings, and infrastructures. In this paper, we propose a framework to couple visual and statistical analyses of convective thunderstorms at the basin scale, considering both the spatial and temporal dimensions of the process. The dataset analyzed in this paper contains intense convective events that occurred in seven years (2012–2018) in the Seveso-Olona-Lambro basin (North of Italy). The data has been acquired by MeteoSwiss using the Thunderstorm Radar Tracking (TRT) algorithm. The results show that the most favorable conditions for the formation of convective events occur in the early afternoon and during summertime, confirming the key role of the temperature in atmospheric convection. The orography emerged as a driver for convection, which takes place more frequently in mountain areas. The storm paths analysis shows that the predominant direction is from South-West to North-East. Considering storm duration, long-lasting events reach higher values of radar reflectivity and cover more extended areas than short-lasting ones. The results obtained can be exploited for many practical applications including nowcasting, alert systems, and sensors deployment. Full article
(This article belongs to the Special Issue Spatial Data Science)
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19 pages, 6569 KiB  
Article
Classification and Segmentation of Mining Area Objects in Large-Scale Spares Lidar Point Cloud Using a Novel Rotated Density Network
by Yueguan Yan, Haixu Yan, Junting Guo and Huayang Dai
ISPRS Int. J. Geo-Inf. 2020, 9(3), 182; https://doi.org/10.3390/ijgi9030182 - 24 Mar 2020
Cited by 12 | Viewed by 3997
Abstract
The classification and segmentation of large-scale, sparse, LiDAR point cloud with deep learning are widely used in engineering survey and geoscience. The loose structure and the non-uniform point density are the two major constraints to utilize the sparse point cloud. This paper proposes [...] Read more.
The classification and segmentation of large-scale, sparse, LiDAR point cloud with deep learning are widely used in engineering survey and geoscience. The loose structure and the non-uniform point density are the two major constraints to utilize the sparse point cloud. This paper proposes a lightweight auxiliary network, called the rotated density-based network (RD-Net), and a novel point cloud preprocessing method, Grid Trajectory Box (GT-Box), to solve these problems. The combination of RD-Net and PointNet was used to achieve high-precision 3D classification and segmentation of the sparse point cloud. It emphasizes the importance of the density feature of LiDAR points for 3D object recognition of sparse point cloud. Furthermore, RD-Net plus PointCNN, PointNet, PointCNN, and RD-Net were introduced as comparisons. Public datasets were used to evaluate the performance of the proposed method. The results showed that the RD-Net could significantly improve the performance of sparse point cloud recognition for the coordinate-based network and could improve the classification accuracy to 94% and the segmentation per-accuracy to 70%. Additionally, the results concluded that point-density information has an independent spatial–local correlation and plays an essential role in the process of sparse point cloud recognition. Full article
(This article belongs to the Special Issue Deep Learning and Computer Vision for GeoInformation Sciences)
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20 pages, 3887 KiB  
Article
Extended Classification Course Improves Road Intersection Detection from Low-Frequency GPS Trajectory Data
by Banqiao Chen, Chibiao Ding, Wenjuan Ren and Guangluan Xu
ISPRS Int. J. Geo-Inf. 2020, 9(3), 181; https://doi.org/10.3390/ijgi9030181 - 24 Mar 2020
Cited by 14 | Viewed by 2931
Abstract
The requirements of location-based services have generated an increasing need for up-to-date digital road maps. However, traditional methods are expensive and time-consuming, requiring many skilled operators. The feasibility of using massive GPS trajectory data provides a cheap and quick means for generating and [...] Read more.
The requirements of location-based services have generated an increasing need for up-to-date digital road maps. However, traditional methods are expensive and time-consuming, requiring many skilled operators. The feasibility of using massive GPS trajectory data provides a cheap and quick means for generating and updating road maps. The detection of road intersections, being the critical component of a road map, is a key problem in map generation. Unfortunately, low sampling rates and high disparities are ubiquitous among floating car data (FCD), making road intersection detection from such GPS trajectories very challenging. In this paper, we extend a point clustering-based road intersection detection framework to include a post-classification course, which utilizes the geometric features of road intersections. First, we propose a novel turn-point position compensation algorithm, in order to improve the concentration of selected turn-points under low sampling rates. The initial detection results given by the clustering algorithm are recall-focused. Then, we rule out false detections in an extended classification course based on an image thinning algorithm. The detection results of the proposed method are quantitatively evaluated by matching with intersections from OpenStreetMap using a variety of distance thresholds. Compared with other methods, our approach can achieve a much higher recall rate and better overall performance, thereby better supporting map generation and other similar applications. Full article
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19 pages, 5909 KiB  
Article
A GIS-Based Multi-Criteria Decision Analysis Model for Determining Glacier Vulnerability
by Mustafa Yalcin
ISPRS Int. J. Geo-Inf. 2020, 9(3), 180; https://doi.org/10.3390/ijgi9030180 - 23 Mar 2020
Cited by 8 | Viewed by 5059
Abstract
Investigating the causes of the spatial heterogeneity of glacial changes offers vital information about glacial behavior and provides forecasting ability to define where glacier retreat may occur in the future. This study was designed to determine the spatial distribution of Ağrı Mountain glacier [...] Read more.
Investigating the causes of the spatial heterogeneity of glacial changes offers vital information about glacial behavior and provides forecasting ability to define where glacier retreat may occur in the future. This study was designed to determine the spatial distribution of Ağrı Mountain glacier vulnerability. The main goal of the current study was to assess the forecasting capabilities of Geographical Information System (GIS)-based Multi-Criteria Decision Analysis (MCDA) for determining the location of the mountain glacier retreat. To estimate the glacier retreat, the following criteria were selected: elevation, aspect, slope, direction, and glacier surface temperature anomaly (GSTA). The entropy method was used for weighting the criteria for the evaluation of the vulnerable areas of the glacier. The results of this method clearly indicate a strong relationship between GSTA, direction, and elevation criteria and glacier retreat. The glacier vulnerability map was created by synthesizing criteria layers with their weights. The vulnerability map provided a consistency of 77.8% in the short term and 92.1% in the long term. In the study, the priority melting zones were determined and glacial retreat locations were forecasted in 10-year periods. Full article
(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)
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13 pages, 2425 KiB  
Article
Spatial Relationship between Natural Wetlands Changes and Associated Influencing Factors in Mainland China
by Ting Zhou, Anyi Niu, Zhanpeng Huang, Jiaojiao Ma and Songjun Xu
ISPRS Int. J. Geo-Inf. 2020, 9(3), 179; https://doi.org/10.3390/ijgi9030179 - 20 Mar 2020
Cited by 7 | Viewed by 2726
Abstract
Many studies have explored the dynamic change of wetlands distribution which play an important role in wetlands conservation and its sustainable management. However, given an uneven distribution of natural wetland resources in the context of global change, little is known about the spatial [...] Read more.
Many studies have explored the dynamic change of wetlands distribution which play an important role in wetlands conservation and its sustainable management. However, given an uneven distribution of natural wetland resources in the context of global change, little is known about the spatial relationship between natural wetlands changes and associated influencing factors in mainland China. In this study, Moran-based spatial statistics are an effective methodology to examine the spatial patterns of natural wetlands and associated influencing factors at the province level, and GIS mapping is applied to help visualize spatial patterns. Results show that 1) significant spatial agglomeration and regional differences of natural wetlands distribution have been captured by Moran’s I statistics, and the agglomeration level has increased over the past ten years; 2) Seven of the eight factors show significantly strong and positive spatial autocorrelation except for water consumption, and spatial patterns of them show significant spatial clusters or spatial outliers; 3) Spatial coordination between natural wetlands distribution and the associated influencing factors is higher in the western region than in east China and northeast China. Moreover, spatial coordination between a cultivated area or water consumption and natural wetlands distribution is weaker than that of other factors. Finally, the influences generated by neighboring provinces should not be neglected in the implementation of wetlands conservation. This study could provide a scientific basis for the policy making of wetlands conservation and sustainable management systems. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management)
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26 pages, 6959 KiB  
Article
Methodological Approach to Incorporate the Involve of Stakeholders in the Geodesign Workflow of Transmission Line Projects
by Francisco-Javier Moreno-Marimbaldo and Miguel-Ángel Manso-Callejo
ISPRS Int. J. Geo-Inf. 2020, 9(3), 178; https://doi.org/10.3390/ijgi9030178 - 20 Mar 2020
Cited by 3 | Viewed by 4691
Abstract
Any artificial infrastructure built in a territory causes changes in its environment, especially when it is a question of large or extensive infrastructures such as high-voltage transmission lines (HVTLs). Such changes are perceived unevenly by the different groups affected or involved. However, all [...] Read more.
Any artificial infrastructure built in a territory causes changes in its environment, especially when it is a question of large or extensive infrastructures such as high-voltage transmission lines (HVTLs). Such changes are perceived unevenly by the different groups affected or involved. However, all of them can obstruct the development of a project of this type of infrastructure. For this reason, it is increasingly necessary to manage the stakeholders in the different phases of the development of an HVTL project. This article presents the methodological proposal designed to add the management of stakeholders’ opinions by integrating it into the geodesign-based workflow for the development of HVTL projects, giving geographic meaning to each of their opinions, allowing their analysis together with the rest of the geospatial information of the project, reusing the “feedback-iteration-consensus” mechanisms, discovering interactions and synergies or incompatibilities, improving the understanding and finally facilitating the consensus of all parties. In this way, it is possible to manage the development of the projects with a single workflow, in which the results are obtained (development stages) and the decisions that are adopted are used both for the technical part and for the management of the project’s stakeholders. Full article
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13 pages, 6087 KiB  
Article
Information Fusion for Cultural Heritage Three-Dimensional Modeling of Malay Cities
by Norzailawati Mohd Noor, Illyani Ibrahim, Alias Abdullah and Ahmad Afiq Aiman Abdullah
ISPRS Int. J. Geo-Inf. 2020, 9(3), 177; https://doi.org/10.3390/ijgi9030177 - 17 Mar 2020
Cited by 23 | Viewed by 4285
Abstract
Malaysia’s heritage structures are facing challenges due to rapid local development and societal challenges that threaten their cultural and artistic values. Improving conservation approaches in this context is an urgent and crucial task. The application of geo-information technologies in laser scanning, photogrammetry, and [...] Read more.
Malaysia’s heritage structures are facing challenges due to rapid local development and societal challenges that threaten their cultural and artistic values. Improving conservation approaches in this context is an urgent and crucial task. The application of geo-information technologies in laser scanning, photogrammetry, and geographic information systems (GISs) has significantly improved these conservation approaches. In this study, we fused drone images and range data from a laser scanner to construct a high-resolution three-dimensional GIS city model for one traditional Malay settlement located in Malaysia. The results showed that fusing photogrammetry and laser scanning can effectively capture the architectural uniqueness of Malay buildings, including specific façade geometries on walls, roofs, and motifs. The findings show that the development of various geoinformation approaches can assist with the conservation of Malay city heritage in this region. Full article
(This article belongs to the Special Issue Information Fusion Based on GIS)
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19 pages, 1331 KiB  
Article
From Spatial Data Infrastructures to Data Spaces—A Technological Perspective on the Evolution of European SDIs
by Alexander Kotsev, Marco Minghini, Robert Tomas, Vlado Cetl and Michael Lutz
ISPRS Int. J. Geo-Inf. 2020, 9(3), 176; https://doi.org/10.3390/ijgi9030176 - 16 Mar 2020
Cited by 54 | Viewed by 10450
Abstract
The availability of timely, accessible and well documented data plays a central role in the process of digital transformation in our societies and businesses. Considering this, the European Commission has established an ambitious agenda that aims to leverage on the favourable technological and [...] Read more.
The availability of timely, accessible and well documented data plays a central role in the process of digital transformation in our societies and businesses. Considering this, the European Commission has established an ambitious agenda that aims to leverage on the favourable technological and political context and build a society that is empowered by data-driven innovation. Within this context, geospatial data remains critically important for many businesses and public services. The process of establishing Spatial Data Infrastructures (SDIs) in response to the legal provisions of the European Union INSPIRE Directive has a long history. While INSPIRE focuses mainly on ’unlocking’ data from the public sector, there is need to address emerging technological trends, and consider the role of other actors such as the private sector and citizen science initiatives. The objective of this paper, given those bounding conditions is twofold. Firstly, we position SDI-related developments in Europe within the broader context of the current political and technological scenery. In doing so, we pay particular attention to relevant technological developments and emerging trends that we see as enablers for the evolution of European SDIs. Secondly, we propose a high level concept of a pan-European (geo)data space with a 10-year horizon in mind. We do this by considering today’s technology while trying to adopt an evolutionary approach with developments that are incremental to contemporary SDIs. Full article
(This article belongs to the Special Issue SDI and the Revolutionary Technological Trends)
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12 pages, 7040 KiB  
Article
Online Education Program in Operational Meteorology and a Case Study about a Product for Decision Making
by Marcial Garbanzo-Salas and Diana Jimenez-Robles
ISPRS Int. J. Geo-Inf. 2020, 9(3), 175; https://doi.org/10.3390/ijgi9030175 - 16 Mar 2020
Cited by 1 | Viewed by 2597
Abstract
An online program developed at the University of Costa Rica provides the professionals working in meteorology a new way to pursue graduate level degrees. The focus of this graduate program is Operational Meteorology and the students need to complete the research and development [...] Read more.
An online program developed at the University of Costa Rica provides the professionals working in meteorology a new way to pursue graduate level degrees. The focus of this graduate program is Operational Meteorology and the students need to complete the research and development process of an operational product to graduate. The products created during the program are a solution to operational institutions in need of innovation and can later be incorporated into institutional activities including advisories, warnings and emergency management. A case study included here shows an example of the need that led to the product, the methodologies used for the development and the final operational product created. Full article
(This article belongs to the Special Issue Education and Training in Applied Remote Sensing)
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19 pages, 1019 KiB  
Article
Measuring Delays for Bicycles at Signalized Intersections Using Smartphone GPS Tracking Data
by Dominique Gillis, Sidharta Gautama, Casper Van Gheluwe, Ivana Semanjski, Angel J. Lopez and Dirk Lauwers
ISPRS Int. J. Geo-Inf. 2020, 9(3), 174; https://doi.org/10.3390/ijgi9030174 - 14 Mar 2020
Cited by 8 | Viewed by 2943
Abstract
The article describes an application of global positioning system (GPS) tracking data (floating bike data) for measuring delays for cyclists at signalized intersections. For selected intersections, we used trip data collected by smartphone tracking to calculate the average delay for cyclists by interpolation [...] Read more.
The article describes an application of global positioning system (GPS) tracking data (floating bike data) for measuring delays for cyclists at signalized intersections. For selected intersections, we used trip data collected by smartphone tracking to calculate the average delay for cyclists by interpolation between GPS locations before and after the intersection. The outcomes were proven to be stable for different strategies in selecting the GPS locations used for calculation, although GPS locations too close to the intersection tended to lead to an underestimation of the delay. Therefore, the sample frequency of the GPS tracking data is an important parameter to ensure that suitable GPS locations are available before and after the intersection. The calculated delays are realistic values, compared to the theoretically expected values, which are often applied because of the lack of observed data. For some of the analyzed intersections, however, the calculated delays lay outside of the expected range, possibly because the statistics assumed a random arrival rate of cyclists. This condition may not be met when, for example, bicycles arrive in platoons because of an upstream intersection. This justifies that GPS-based delays can form a valuable addition to the theoretically expected values. Full article
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18 pages, 8609 KiB  
Article
Estimation of Crop Water Deficit in Lower Bari Doab, Pakistan Using Reflection-Based Crop Coefficient
by Muhammad Asif Javed, Sajid Rashid Ahmad, Wakas Karim Awan and Bilal Ahmed Munir
ISPRS Int. J. Geo-Inf. 2020, 9(3), 173; https://doi.org/10.3390/ijgi9030173 - 13 Mar 2020
Cited by 9 | Viewed by 5203
Abstract
There is a global realization in all governmental setups of the need to provoke the efficient appraisal of crop water budgeting in order to manage water resources efficiently. This study aims to use the satellite remote sensing techniques to determine the water deficit [...] Read more.
There is a global realization in all governmental setups of the need to provoke the efficient appraisal of crop water budgeting in order to manage water resources efficiently. This study aims to use the satellite remote sensing techniques to determine the water deficit in the crop rich Lower Bari Doab Canal (LBDC) command area. Crop classification was performed using multi-temporal NDVI profiles of Landsat-8 imagery by distinguishing the crop cycles based on reflectance curves. The reflectance-based crop coefficients (Kc) were derived by linear regression between normalized difference vegetation index (NDVI) cycles of the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 and MYD13Q1 products and Food and Agriculture Organization (FAO) defined crop coefficients. A MODIS 250 m NDVI product of the last 10 years (2004-2013) was used to identify the best performing crop cycle using Fourier filter method. The meteorological parameters including rainfall and temperature substantiated the reference evapotranspiration (ET0) calculated using the Hargreaves method. The difference of potential ET and actual ET, derived from the reflectance-based Kc calculated using reference NDVI and current NDVI, generates the water deficit. Results depict the strong correlation between ET, temperature and rainfall, as the regions having maximum temperature resulted in high ET and low rainfall and vice versa. The derived Kc values were observed to be accurate when compared with the crop calendar. Results revealed maximum water deficit at middle stage of the crops, which were observed to be particularly higher at the tail of the canal command. Moreover, results also depicted that kharif (summer) crops suffer higher deficit in comparison to rabi (winter) crops due to higher ET demand caused by higher temperature. Results of the research can be utilized for rational allocation of canal supplies and guiding farmers towards usage of alternate sources to avoid crop water stress. Full article
(This article belongs to the Special Issue Geo-Spatial Analysis in Hydrology)
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23 pages, 2856 KiB  
Article
Study on the Level and Type Identification of Rural Development in Wuhan City’s New Urban Districts
by Liang Jiang, Jing Luo, Chunyan Zhang, Lingling Tian, Qingqing Liu, Guolei Chen and Ye Tian
ISPRS Int. J. Geo-Inf. 2020, 9(3), 172; https://doi.org/10.3390/ijgi9030172 - 13 Mar 2020
Cited by 13 | Viewed by 3489
Abstract
A quantitative analysis of rural development is required to comprehend the spatial differentiation of a rural area and promote rural sustainable development under the pressure of urbanization and industrialization, especially areas with dramatic changes in rural socioeconomic development of China and other developing [...] Read more.
A quantitative analysis of rural development is required to comprehend the spatial differentiation of a rural area and promote rural sustainable development under the pressure of urbanization and industrialization, especially areas with dramatic changes in rural socioeconomic development of China and other developing countries. Taking Wuhan as the case study, this paper developed an index system including rural settlement, land, industry and human settlement environment for evaluating the level of rural development. Then, using the exploratory spatial data analysis, the principal component analysis and the cluster analysis, this paper analyzes the spatial differentiation and correlation and categorizes the types of rural development. The results are as follows. (1) The spatial differentiation of the level of rural development in Wuhan City’s new urban districts is obvious and the areas with a high level of rural development are mainly distributed at the intersection of the new and central urban areas and gradually decrease outward. (2) There is a significant spatial agglomeration of the developed rural areas and the structure of the spatial change in these areas resembles a certain continuity, specifically a circle of “central heat surrounding cold”. (3) Rural development in the new urban areas can be divided into the following five types: the ecological leisure type, the traditional farming type, the balanced development type, the industrial-and-agricultural mixed type and the industrial promotion type. The corresponding development path is proposed in combination with different types of rural development to provide a theoretical basis and decision-making reference for rural revitalization. Full article
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20 pages, 6493 KiB  
Article
Indexing Mixed Aperture Icosahedral Hexagonal Discrete Global Grid Systems
by Rui Wang, Jin Ben, Jianbin Zhou and Mingyang Zheng
ISPRS Int. J. Geo-Inf. 2020, 9(3), 171; https://doi.org/10.3390/ijgi9030171 - 13 Mar 2020
Cited by 13 | Viewed by 4406
Abstract
Discrete global grid systems (DGGSs) are an emerging multiresolution 3D model used to integrate and analyze big earth data. The characteristic of multiresolution is usually realized by hierarchically subdividing cells on the sphere using certain refinement. This paper introduces mixed aperture three- and [...] Read more.
Discrete global grid systems (DGGSs) are an emerging multiresolution 3D model used to integrate and analyze big earth data. The characteristic of multiresolution is usually realized by hierarchically subdividing cells on the sphere using certain refinement. This paper introduces mixed aperture three- and four- icosahedral hexagonal DGGSs using two types of refinement, the various combinations of which can provide more resolutions compared with pure aperture hexagonal DGGSs and can flexibly design the aperture sequence according to the target resolutions. A general hierarchy-based indexing method is first designed, and related indexing arithmetics and algorithm are developed based on the indexing method. Then, the grid structure on the surface of the icosahedron is described and by projection spherical grids are obtained. Experiments show that the proposed scheme is superior to pure aperture schemes in choosing grid resolutions and can reduce the data volume by 38.5% in representing 1-km resolution raster dataset; using the proposed indexing arithmetics to replace spherical geometry operations in generating discrete spherical vector lines based on hexagonal cells can improve the generation efficiency. Full article
(This article belongs to the Special Issue Global Grid Systems)
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19 pages, 8199 KiB  
Article
Minecraft as a Tool for Engaging Children in Urban Planning: A Case Study in Tirol Town, Brazil
by Bruno de Andrade, Alenka Poplin and Ítalo Sousa de Sena
ISPRS Int. J. Geo-Inf. 2020, 9(3), 170; https://doi.org/10.3390/ijgi9030170 - 13 Mar 2020
Cited by 43 | Viewed by 12358
Abstract
The purpose of this paper is to explore the potential of Minecraft’s game environment for urban planning with older and younger children in a public school in Tirol town, Brazil. Minecraft is employed as an innovative tool to tackle the present lack of [...] Read more.
The purpose of this paper is to explore the potential of Minecraft’s game environment for urban planning with older and younger children in a public school in Tirol town, Brazil. Minecraft is employed as an innovative tool to tackle the present lack of engagement and involvement of key societal actors such as children and young people in urban planning. Thus, how can games support children to co-design their future city? Which heritage values do they represent graphically in the game environment? Geogames are games that provide a visualization of a real spatial context and in this study, Minecraft is the tool which we use to explore youth engagement. We designed two experiments, which tested Minecraft as a geogame environment for engaging young people in urban planning. These experiments were conducted with children, who emerged as active emancipated actors to bring their values to the planning practice. The playtesting results revealed the potential of Minecraft to keep children engaged in the design workshop, as well as their relevant ludic ability to co-create walkable, green, and interactive places. New research questions arose about the potential of creating a culture of planning among children in order to motivate other social actors to share responsibilities for sustainable development and management. Full article
(This article belongs to the Special Issue Gaming and Geospatial Information)
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21 pages, 2380 KiB  
Article
A Proposal for Modeling Indoor–Outdoor Spaces through IndoorGML, Open Location Code and OpenStreetMap
by Rubén Cantarero Navarro, Ana Rubio Ruiz, Javier Dorado Chaparro, Felix J. Villanueva Molina, Maria J. Santofimia Romero, David Villa Alises and Juan C. Lopez Lopez
ISPRS Int. J. Geo-Inf. 2020, 9(3), 169; https://doi.org/10.3390/ijgi9030169 - 12 Mar 2020
Cited by 8 | Viewed by 3718
Abstract
Traditionally, the standards of spatial modeling are oriented to represent the quantitative information of space. However, in recent years an increasingly common challenge is appearing: flexibly and appropriately integrating quantitative information that goes beyond the purely geometric. This problem has been aggravated due [...] Read more.
Traditionally, the standards of spatial modeling are oriented to represent the quantitative information of space. However, in recent years an increasingly common challenge is appearing: flexibly and appropriately integrating quantitative information that goes beyond the purely geometric. This problem has been aggravated due to the success of new paradigms such as the Internet of Things. This adds an additional challenge to the representation of this information due to the need to represent characteristic information of the space from different points of view in a model, such as WiFi coverage, dangerous surroundings, etc. While this problem has already been addressed in indoor spaces with the IndoorGML standard, it remains to be solved in outdoor and indoor–outdoor spaces. We propose to take the advantages proposed in IndoorGML, such as cellular space or multi-layered space model representation, to outdoor spaces in order to create indoor–outdoor models that enable the integration of heterogeneous information that represents different aspects of space. We also propose an approach that gives more flexibility in spatial representation through the integration of standards such as OpenLocationCode for the division of space. Further, we suggest a procedure to enrich the resulting model through the information available in OpenStreetMap. Full article
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16 pages, 7807 KiB  
Article
A Topology Preserving Gridding Method for Vector Features in Discrete Global Grid Systems
by Liangchen Zhou, Wenjie Lian, Yudi Zhang and Bingxian Lin
ISPRS Int. J. Geo-Inf. 2020, 9(3), 168; https://doi.org/10.3390/ijgi9030168 - 12 Mar 2020
Cited by 6 | Viewed by 3060
Abstract
Topological distortion seriously affects spatial cognition. To solve this problem caused by the integration of vector features in discrete global grid systems (DGGs), a topology-preserving gridding method for vector features is proposed. The method proposed determines the topological distortion according to the relationship [...] Read more.
Topological distortion seriously affects spatial cognition. To solve this problem caused by the integration of vector features in discrete global grid systems (DGGs), a topology-preserving gridding method for vector features is proposed. The method proposed determines the topological distortion according to the relationship between grid cells and then increases the local resolution of vector features by employing the multi-level resolution characteristic of DGGs, to repair three kinds of topological distortions. Experimental results show that the proposed method can effectively maintain the topological relationship between the original vector features, and the amount of data is stable, thus ensuring the correct integration of vector features in the DGGs. Full article
(This article belongs to the Special Issue Global Grid Systems)
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19 pages, 7773 KiB  
Article
Development and Application of an Intelligent Modeling Method for Ancient Wooden Architecture
by Yonghui Jiang, Aiqun Li, Linlin Xie, Miaole Hou, Ying Qi and Haoyu Liu
ISPRS Int. J. Geo-Inf. 2020, 9(3), 167; https://doi.org/10.3390/ijgi9030167 - 11 Mar 2020
Cited by 16 | Viewed by 6219
Abstract
Building-information-modeling for cultural heritage (HBIM), which is established using surveying data, can be used to conserve architectural heritage. The development of an HBIM model for ancient wooden architecture (AWA) structures requires interdisciplinary integration. A parametric model for the main components that intelligently integrates [...] Read more.
Building-information-modeling for cultural heritage (HBIM), which is established using surveying data, can be used to conserve architectural heritage. The development of an HBIM model for ancient wooden architecture (AWA) structures requires interdisciplinary integration. A parametric model for the main components that intelligently integrates the historical knowledge, as well as an intelligent modeling method for these components, are two critical issues required to bridge the existing gap and improve the application of HBIM. Taking an AWA structure constructed during the Liao and Song Dynasties as an example, the parametric model for the typical components, with emphasis on commonality and characteristics, were first proposed. Subsequently, an intelligent automated modeling method was developed and programmed using Dynamo, which can intelligently identify the component type and determine the invisible dimensions. A complicated dou-gong was successfully established with surveying data using the proposed method within five minutes, thereby validating the reliability and efficiency of this method. Furthermore, the proposed method was used to establish the HBIM model of Yingxian Wood Pagoda, which is the oldest and tallest AWA structure in China with a height of 65.88 m. The research findings will provide an essential reference for the conservation of wooden architectural heritage structures. Full article
(This article belongs to the Special Issue BIM for Cultural Heritage (HBIM))
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16 pages, 10950 KiB  
Article
Dynamic Online 3D Visualization Framework for Real-Time Energy Simulation Based on 3D Tiles
by Bo Mao, Yifang Ban and Björn Laumert
ISPRS Int. J. Geo-Inf. 2020, 9(3), 166; https://doi.org/10.3390/ijgi9030166 - 11 Mar 2020
Cited by 21 | Viewed by 5148
Abstract
Energy co-simulation can be used to analyze the dynamic energy consumption of a building or a region, which is essential for decision making in the planning and management of smart cities. To increase the accessibility of energy simulation results, a dynamic online 3D [...] Read more.
Energy co-simulation can be used to analyze the dynamic energy consumption of a building or a region, which is essential for decision making in the planning and management of smart cities. To increase the accessibility of energy simulation results, a dynamic online 3D city model visualization framework based on 3D Tiles is proposed in this paper. Two types of styling methods are studied, attribute-based and ID map-based. We first perform the energy co-simulation and save the results in CityGML format with EnergyADE. Then the 3D geometry data of these city objects are combined with its simulation results as attributes or just with object ID information to generate Batched 3D Models (B3DM) in 3D Tiles. Next, styling strategies are pre-defined and can be selected by end-users to show different scenarios. Finally, during the visualization process, dynamic interactions and data sources are integrated into the styling generation to support real-time visualization. This framework is implemented with Cesium. Compared with existing dynamic online 3D visualization framework such as directly styling or Cesium Language (CZML), a JSON format for describing a time-dynamic graphical scene, primarily for display in a web browser running Cesium, the proposed framework is more flexible and has higher performance in both data transmission and rendering which is essential for real-time GIS applications. Full article
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20 pages, 5011 KiB  
Article
Identifying Users’ Requirements for Emergency Mapping Team Operations in the Dominican Republic
by Gregorio Rosario Michel, Santiago Muñoz Tapia, Fernando Manzano Aybar, Vladimir Guzmán Javier and Joep Crompvoets
ISPRS Int. J. Geo-Inf. 2020, 9(3), 165; https://doi.org/10.3390/ijgi9030165 - 11 Mar 2020
Cited by 5 | Viewed by 3668
Abstract
In recent years, a growing number of stakeholders have been taking part in the generation and delivery of geospatial information and services to reduce the impact of severe natural disasters on the communities. This is mainly due to a huge demand for accurate, [...] Read more.
In recent years, a growing number of stakeholders have been taking part in the generation and delivery of geospatial information and services to reduce the impact of severe natural disasters on the communities. This is mainly due to a huge demand for accurate, current and relevant knowledge about the impacted areas for a wide range of applications in risk-informed decision makings. The aim of this paper is to identify users’ requirements for emergency mapping team (EMT) operations in the Dominican Republic (DR). An online survey was applied to collect data from key users involved in the Inter-Institutional Geospatial Information Team in DR. Our findings suggest a set of users’ requirements for EMT operations: (1) standardization; (2) establishing and maintaining a spatial data infrastructure; (3) partnership; (4) effective communication among stakeholders; and (5) capacity building. A better understanding of the users’ requirements and the associated information workflows will lead to a superior level of readiness for EMT operations in DR. This knowledge will support future studies/practices at the local and national levels in the Caribbean region, which share similar challenges in terms of natural hazards and development issues. Full article
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21 pages, 8772 KiB  
Article
Accuracy Assessment of a UAV Block by Different Software Packages, Processing Schemes and Validation Strategies
by Vittorio Casella, Filiberto Chiabrando, Marica Franzini and Ambrogio Maria Manzino
ISPRS Int. J. Geo-Inf. 2020, 9(3), 164; https://doi.org/10.3390/ijgi9030164 - 11 Mar 2020
Cited by 41 | Viewed by 6280
Abstract
Unmanned aerial vehicle (UAV) systems are heavily adopted nowadays to collect high-resolution imagery with the purpose of documenting and mapping environment and cultural heritage. Such data are currently processed by programs based on the Structure from Motion (SfM) concept, coming from the computer [...] Read more.
Unmanned aerial vehicle (UAV) systems are heavily adopted nowadays to collect high-resolution imagery with the purpose of documenting and mapping environment and cultural heritage. Such data are currently processed by programs based on the Structure from Motion (SfM) concept, coming from the computer vision community, rather than from classical photogrammetry. It is interesting to check whether some widely accepted rules coming from old-fashioned photogrammetry still holds: the relation between accuracy and ground sampling distance (GSD), the ratio between the vertical and horizontal accuracy, accuracy estimated on ground control points (GCPs) vs. that estimated with check points (CPs) also in relation to their ratio and distribution. To face the envisaged aspects, the paper adopts a comparative approach, as several programs are used and numerous configurations considered. The paper illustrates the dataset adopted, the carefully tuned processing strategies and bundle block adjustment (BBA) results in terms of accuracy for both GCPs and CPs. Finally, a leave-one-out (LOO) cross-validation strategy is proposed to assess the accuracy for one of the proposed configurations. Some of the reported results were previously presented in the 5th GISTAM Conference. Full article
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
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18 pages, 11398 KiB  
Article
FloodSim: Flood Simulation and Visualization Framework Using Position-Based Fluids
by I. Alihan Hadimlioglu, Scott A. King and Michael J. Starek
ISPRS Int. J. Geo-Inf. 2020, 9(3), 163; https://doi.org/10.3390/ijgi9030163 - 11 Mar 2020
Cited by 12 | Viewed by 5779
Abstract
Flood modeling and analysis has been a vital research area to reduce damages caused by flooding and to make urban environments resilient against such occurrences. This work focuses on building a framework to simulate and visualize flooding in 3D using position-based fluids for [...] Read more.
Flood modeling and analysis has been a vital research area to reduce damages caused by flooding and to make urban environments resilient against such occurrences. This work focuses on building a framework to simulate and visualize flooding in 3D using position-based fluids for real-time flood spread visualization and analysis. The framework incorporates geographical information and takes several parameters in the form of friction coefficients and storm drain information, and then uses mechanics such as precipitation and soil absorption for simulation. The preliminary results of the river flooding test case were satisfactory, as the flood extent was reproduced in 220 s with a difference of 7%. Consequently, the framework could be a useful tool for practitioners who have information about the study area and would like to visualize flooding using a particle-based approach for real-time particle tracking and flood path analysis, incorporating precipitation into their models. Full article
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13 pages, 4650 KiB  
Article
Urban Scene Vectorized Modeling Based on Contour Deformation
by Lingjie Zhu, Shuhan Shen, Xiang Gao and Zhanyi Hu
ISPRS Int. J. Geo-Inf. 2020, 9(3), 162; https://doi.org/10.3390/ijgi9030162 - 10 Mar 2020
Cited by 4 | Viewed by 3171
Abstract
Modeling urban scenes automatically is an important problem for both GIS and nonGIS specialists with applications like urban planning, autonomous driving, and virtual reality. In this paper, we present a novel contour deformation approach to generate regularized and vectorized 3D building models from [...] Read more.
Modeling urban scenes automatically is an important problem for both GIS and nonGIS specialists with applications like urban planning, autonomous driving, and virtual reality. In this paper, we present a novel contour deformation approach to generate regularized and vectorized 3D building models from the orthophoto and digital surface model (DSM).The proposed method has four major stages: dominant directions extraction, find target align direction, contour deformation, and model generation. To begin with, we extract dominant directions for each building contour in the orthophoto. Then every edge of the contour is assigned with one of the dominant directions via a Markov random field (MRF). Taking the assigned direction as target, we define a deformation energy with the Advanced Most-Isometric ParameterizationS (AMIPS) to align the contour to the dominant directions. Finally, the aligned contour is simplified and extruded to 3D models. Through the alignment deformation, we are able to straighten the contour while keeping the sharp turning corners. Our contour deformation based urban modeling approach is accurate and robust comparing with the state-of-the-arts as shown in experiments on the public dataset. Full article
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14 pages, 4799 KiB  
Article
Analyzing Road Coverage of Public Vehicles According to Number and Time Period for Installation of Road Inspection Systems
by Takehiro Kashiyama, Yoshihide Sekimoto, Toshikazu Seto and Ko Ko Lwin
ISPRS Int. J. Geo-Inf. 2020, 9(3), 161; https://doi.org/10.3390/ijgi9030161 - 10 Mar 2020
Cited by 3 | Viewed by 2737
Abstract
Shortages of engineers and financial resources have made it difficult for municipalities to identify and address problems with aging road infrastructures. To resolve these problems, numerous studies have focused on automating road inspection, including a study in which we developed a smartphone-based road [...] Read more.
Shortages of engineers and financial resources have made it difficult for municipalities to identify and address problems with aging road infrastructures. To resolve these problems, numerous studies have focused on automating road inspection, including a study in which we developed a smartphone-based road inspection system. For efficient operation of the system, it is necessary to understand the usage of vehicles in which the system will be installed. In this study, we analyzed the usage of public vehicles with long-term global positioning system (GPS) probe data collected from public vehicles operating in Kakogawa city and Fujisawa city in Japan. As a result, we discovered that local governments of the same size have similar tendencies in terms of road coverage. Moreover, we found that installing road inspection systems on only a few public vehicles can cover the entire road inspection area. We anticipate that these results will assist local governments in making informed decisions during the system introduction process and provide an indicator of the accuracy required for road inspection systems to future researchers. Full article
(This article belongs to the Special Issue Spatial Data Science)
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17 pages, 6711 KiB  
Article
A Novel Method of Spatiotemporal Dynamic Geo-Visualization of Criminal Data, Applied to Command and Control Centers for Public Safety
by Mayra Salcedo-Gonzalez, Julio Suarez-Paez, Manuel Esteve, Jon Ander Gómez and Carlos Enrique Palau
ISPRS Int. J. Geo-Inf. 2020, 9(3), 160; https://doi.org/10.3390/ijgi9030160 - 10 Mar 2020
Cited by 6 | Viewed by 3008
Abstract
This article shows a novel geo-visualization method of dynamic spatiotemporal data that allows mobility and concentration of criminal activity to be study. The method was developed using, only and significantly, real data of Santiago de Cali (Colombia), collected by the Colombian National Police [...] Read more.
This article shows a novel geo-visualization method of dynamic spatiotemporal data that allows mobility and concentration of criminal activity to be study. The method was developed using, only and significantly, real data of Santiago de Cali (Colombia), collected by the Colombian National Police (PONAL). This method constitutes a tool that allows criminal influx to be analyzed by concentration, zone, time slot and date. In addition to the field experience of police commanders, it allows patterns of criminal activity to be detected, thereby enabling a better distribution and management of police resources allocated to crime deterrence, prevention and control. Additionally, it may be applied to the concepts of safe city and smart city of the PONAL within the architecture of Command and Control System (C2S) of Command and Control Centers for Public Safety. Furthermore, it contributes to a better situational awareness and improves the future projection, agility, efficiency and decision-making processes of police officers, which are all essential for fulfillment of police missions against crime. Finally, this was developed using an open source software, it can be adapted to any other city, be used with real-time data and be implemented, if necessary, with the geographic software of any other C2S. Full article
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14 pages, 1348 KiB  
Article
Think Spatially With Game Engine
by Carlos Carbonell-Carrera, Peri Gunalp, Jose Luis Saorin and Stephany Hess-Medler
ISPRS Int. J. Geo-Inf. 2020, 9(3), 159; https://doi.org/10.3390/ijgi9030159 - 9 Mar 2020
Cited by 18 | Viewed by 4162
Abstract
Spatial thinking and spatial orientation skills are involved in tasks related to the recognition of landforms, mapping, spatial interpretation, and landscape analysis, and can be developed with specific training. Game engines can facilitate the creation of 3D virtual landforms and provide powerful rendering [...] Read more.
Spatial thinking and spatial orientation skills are involved in tasks related to the recognition of landforms, mapping, spatial interpretation, and landscape analysis, and can be developed with specific training. Game engines can facilitate the creation of 3D virtual landforms and provide powerful rendering engines for the graphical representation of landscapes from a first-person perspective. In the present research, 27 engineering students participated in a workshop in a first-person virtual environment using landforms created with a game engine. The Spatial Thinking Ability Test and the Perspective Taking-Spatial Orientation Test measured improvement in spatial thinking and spatial orientation as a result of this workshop. The gain in spatial thinking (8.31%) is within the range observed in previous research in the field of geography using a web-based GIS strategy (7.31%–10.00%). The gain in Spatial Orientation skill (15.76%) is comparable with previous research using both first-person strategies based in urban virtual environments (14.23%), and Spatial Data Infrastructures (gains between 21.17% and 21.34%). Participants with better self-reported sense of direction had better performance on the spatial orientation test. Full article
(This article belongs to the Special Issue Gaming and Geospatial Information)
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19 pages, 31497 KiB  
Article
Identification of Urban Functional Regions in Chengdu Based on Taxi Trajectory Time Series Data
by Xudong Liu, Yongzhong Tian, Xueqian Zhang and Zuyi Wan
ISPRS Int. J. Geo-Inf. 2020, 9(3), 158; https://doi.org/10.3390/ijgi9030158 - 9 Mar 2020
Cited by 50 | Viewed by 5017
Abstract
Overall scientific planning of urbanization layout is an important component of the new period of land spatial planning policies. Defining the main functions of different spaces and dividing urban functional areas are of great significance for optimizing the land development pattern. This article [...] Read more.
Overall scientific planning of urbanization layout is an important component of the new period of land spatial planning policies. Defining the main functions of different spaces and dividing urban functional areas are of great significance for optimizing the land development pattern. This article identifies and analyses urban functional areas from the perspective of data mining. The results of this method are consistent with the actual situation. In this paper, representative taxi trajectory data are selected as the research basis of urban functional areas. First, based on trajectory data from Didi Chuxing within the high-speed road surrounding Chengdu, we generated trajectory time sequence data and used the dynamic time warping (DTW) algorithm to generate a time series similarity matrix. Second, we utilized the K-medoid clustering algorithm to generate preliminary results of land clustering and selected the results with high classification accuracy as the training samples. Then, the k-nearest neighbour (KNN) classification algorithm based on DTW was performed to classify and identify the urban functional areas. Finally, with the help of point-of-interest (POI) auxiliary analysis, the final functional layout in Chengdu was obtained. The results show that the spatial structure of Chengdu is complex and that the urban functions are interlaced, but there are still rules that are followed. Moreover, traffic volume and inflow data can better reflect the travel rules of residents than simple taxi on–off data. The original DTW calculation method has high temporal complexity, which can be improved by normalization and the reduction of time series dimensionality. The semi-supervised learning classification method is also applicable to trajectory data, and it is best to select training samples from unsupervised learning. This method can provide a theoretical basis for urban land planning and has auxiliary and guiding value for urbanization layout in the context of land spatial planning policies in the new era. Full article
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17 pages, 647 KiB  
Review
Analysing the Police Patrol Routing Problem: A Review
by Maite Dewinter, Christophe Vandeviver, Tom Vander Beken and Frank Witlox
ISPRS Int. J. Geo-Inf. 2020, 9(3), 157; https://doi.org/10.3390/ijgi9030157 - 9 Mar 2020
Cited by 33 | Viewed by 18342
Abstract
Police patrol is a complex process. While on patrol, police officers must balance many intersecting responsibilities. Most notably, police must proactively patrol and prevent offenders from committing crimes but must also reactively respond to real-time incidents. Efficient patrol strategies are crucial to manage [...] Read more.
Police patrol is a complex process. While on patrol, police officers must balance many intersecting responsibilities. Most notably, police must proactively patrol and prevent offenders from committing crimes but must also reactively respond to real-time incidents. Efficient patrol strategies are crucial to manage scarce police resources and minimize emergency response times. The objective of this review paper is to discuss solution methods that can be used to solve the so-called police patrol routing problem (PPRP). The starting point of the review is the existing literature on the dynamic vehicle routing problem (DVRP). A keyword search resulted in 30 articles that focus on the DVRP with a link to police. Although the articles refer to policing, there is no specific focus on the PPRP; hence, there is a knowledge gap. A diversity of approaches is put forward ranging from more convenient solution methods such as a (hybrid) Genetic Algorithm (GA), linear programming and routing policies, to more complex Markov Decision Processes and Online Stochastic Combinatorial Optimization. Given the objectives, characteristics, advantages and limitations, the (hybrid) GA, routing policies and local search seem the most valuable solution methods for solving the PPRP. Full article
(This article belongs to the Special Issue Urban Crime Mapping and Analysis Using GIS)
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18 pages, 8232 KiB  
Article
Flow Modeling and Rendering to Support 3D River Shipping Based on Cross-Sectional Observation Data
by Xuequan Zhang, Jin Liu, Zihe Hu and Ming Zhong
ISPRS Int. J. Geo-Inf. 2020, 9(3), 156; https://doi.org/10.3390/ijgi9030156 - 9 Mar 2020
Cited by 3 | Viewed by 2725
Abstract
The flow in meandering rivers is characterized by rapid changes in flow velocity and water level, especially in flooded environments. Accurate cross-sectional observation data enable continuous monitoring of flow conditions, which is important for river navigation. In this paper, cross-sectional data based flow [...] Read more.
The flow in meandering rivers is characterized by rapid changes in flow velocity and water level, especially in flooded environments. Accurate cross-sectional observation data enable continuous monitoring of flow conditions, which is important for river navigation. In this paper, cross-sectional data based flow modeling and rendering methods are studied to build an interactive hybrid flow environment for three-dimensional river shipping. First, the sparse cross-sectional data are extrapolated and interpolated to provide dense sampling points. Then, the data are visualized separately by dynamic texture mapping, particle tracking, streamline rendering, and contour surface rendering. Finally, the rendering models are integrated with ship animation to build a comprehensive hybrid river navigation scenario. The proposed methods are tested by visualizing measured cross-sectional data in the Yangtze River using an open-source software, called World Wind. The experimental results demonstrate that the hybrid flow rendering achieves comprehensive visual effect and the rendering frame rate is greater than 30. The interactive hybrid flow visualization is beneficial to support river shipping analysis. Full article
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