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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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16 pages, 6387 KiB  
Article
Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets
by **g Yu, Shu Peng, Weiwei Zhang and Shun Kang
ISPRS Int. J. Geo-Inf. 2020, 9(8), 483; https://doi.org/10.3390/ijgi9080483 - 11 Aug 2020
Cited by 5 | Viewed by 5239
Abstract
Recognizing land cover heterogeneity is essential for the assessment of spatial patterns to guide conservation planning. One of the top research priorities is the quantification of land cover heterogeneity using effective landscape metrics. However, due to the diversity of land cover types and [...] Read more.
Recognizing land cover heterogeneity is essential for the assessment of spatial patterns to guide conservation planning. One of the top research priorities is the quantification of land cover heterogeneity using effective landscape metrics. However, due to the diversity of land cover types and their varied distribution, a consistent, larger-scale, and standardized framework for heterogeneity information extraction from this complex perspective is still lacking. Consequently, we developed a new Land Cover Complexity Index (LCCI), which is based on information-theory. The LCCI contains two foundational aspects of heterogeneity, composition and configuration, thereby capturing more comprehensive information on land cover patterns than any single metric approach. In this study, we compare the performance of the LCCI with that of other landscape metrics at two different scales, and the results show that our newly developed indicator more accurately characterizes and distinguishes different land cover patterns. LCCI provides an alternative way to measure the spatial variation of land cover distribution. Classification maps of land cover heterogeneity generated using the LCCI provide valuable insights and implications for regional conservation planning. Thus, the LCCI is shown to be a consistent indicator for the quantification of land cover heterogeneity that functions in an adaptive way by simultaneously considering both composition and configuration. Full article
(This article belongs to the Special Issue Geographic Complexity: Concepts, Theories, and Practices)
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26 pages, 6256 KiB  
Article
A Framework Uniting Ontology-Based Geodata Integration and Geovisual Analytics
by Linfang Ding, Guohui **ao, Diego Calvanese and Liqiu Meng
ISPRS Int. J. Geo-Inf. 2020, 9(8), 474; https://doi.org/10.3390/ijgi9080474 - 28 Jul 2020
Cited by 16 | Viewed by 5462
Abstract
In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making [...] Read more.
In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making sense out of the combined data via sophisticated analysis methods. To address this challenge we rely on two well-established research areas: data integration and geovisual analytics, and propose to adopt an ontology-based approach to decouple the challenges of data access and analytics. Our framework consists of two modules centered around an ontology: (1) an ontology-based data integration (OBDI) module, in which map**s specify the relationship between the underlying data and a domain ontology; (2) a geovisual analytics (GeoVA) module, designed for the exploration of the integrated data, by explicitly making use of standard ontologies. In this framework, ontologies play a central role by providing a coherent view over the heterogeneous data, and by acting as a mediator for visual analysis tasks. We test our framework in a scenario for the investigation of the spatiotemporal patterns of meteorological and traffic data from several open data sources. Initial studies show that our approach is feasible for the exploration and understanding of heterogeneous geospatial data. Full article
(This article belongs to the Special Issue On Denotation and Connotation in Web Semantics, Collaboration and Metadata)
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22 pages, 2838 KiB  
Article
Measuring Community Disaster Resilience in the Conterminous Coastal United States
by Shaikh Abdullah Al Rifat and Weibo Liu
ISPRS Int. J. Geo-Inf. 2020, 9(8), 469; https://doi.org/10.3390/ijgi9080469 - 23 Jul 2020
Cited by 44 | Viewed by 7279
Abstract
In recent years, building resilient communities to disasters has become one of the core objectives in the field of disaster management globally. Despite being frequently targeted and severely impacted by disasters, the geographical extent in studying disaster resilience of the coastal communities of [...] Read more.
In recent years, building resilient communities to disasters has become one of the core objectives in the field of disaster management globally. Despite being frequently targeted and severely impacted by disasters, the geographical extent in studying disaster resilience of the coastal communities of the United States (US) has been limited. In this study, we developed a composite community disaster resilience index (CCDRI) for the coastal communities of the conterminous US that considers different dimensions of disaster resilience. The resilience variables used to construct the CCDRI were justified by examining their influence on disaster losses using ordinary least squares (OLS) and geographically weighted regression (GWR) models. Results suggest that the CCDRI score ranges from −12.73 (least resilient) to 8.69 (most resilient), and northeastern communities are comparatively more resilient than southeastern communities in the study area. Additionally, resilience components used in this study have statistically significant impact on minimizing disaster losses. The GWR model performs much better in explaining the variances while regressing the disaster property damage against the resilience components (explains 72% variance) than the OLS (explains 32% variance) suggesting that spatial variations of resilience components should be accounted for an effective disaster management program. Moreover, findings from this study could provide local emergency managers and decision-makers with unique insights for enhancing overall community resilience to disasters and minimizing disaster impacts in the study area. Full article
(This article belongs to the Special Issue Geomatic Applications to Coastal Research: Challenges and New Developments)
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19 pages, 8220 KiB  
Article
An Open-Source Framework of Generating Network-Based Transit Catchment Areas by Walking
by Diao Lin, Ruoxin Zhu, Jian Yang and Liqiu Meng
ISPRS Int. J. Geo-Inf. 2020, 9(8), 467; https://doi.org/10.3390/ijgi9080467 - 22 Jul 2020
Cited by 4 | Viewed by 2826
Abstract
The transit catchment area is an important concept for public transport planning. This study proposes a methodological framework to generate network-based transit catchment areas by walking. Three components of the framework, namely subgraph construction, extended shortest path tree construction and contour generation are [...] Read more.
The transit catchment area is an important concept for public transport planning. This study proposes a methodological framework to generate network-based transit catchment areas by walking. Three components of the framework, namely subgraph construction, extended shortest path tree construction and contour generation are presented step by step. Methods on how to generalize the framework to the cases of the directed road network and non-point facilities are developed. The implementation of the framework is provided as an open-source project. Using metro stations in Shanghai as a case study, we illustrate the feasibility of the proposed framework. Experiments show that the proposed method generates catchment areas of high geospatial accuracy and significantly increases computational efficiency. The open-source program can be applied to support research related to transit catchment areas and has the potential to be extended to include more routing-related factors. Full article
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22 pages, 11839 KiB  
Article
Post-Earthquake Recovery Phase Monitoring and Map** Based on UAS Data
by Nikolaos Soulakellis, Christos Vasilakos, Stamatis Chatzistamatis, Dimitris Kavroudakis, Georgios Tataris, Ermioni-Eirini Papadopoulou, Apostolos Papakonstantinou, Olga Roussou and Themistoklis Kontos
ISPRS Int. J. Geo-Inf. 2020, 9(7), 447; https://doi.org/10.3390/ijgi9070447 - 17 Jul 2020
Cited by 10 | Viewed by 3302
Abstract
Geoinformatics plays an essential role during the recovery phase of a post-earthquake situation. The aim of this paper is to present the methodology followed and the results obtained by the utilization of Unmanned Aircraft Systems (UASs) 4K-video footage processing and the automation of [...] Read more.
Geoinformatics plays an essential role during the recovery phase of a post-earthquake situation. The aim of this paper is to present the methodology followed and the results obtained by the utilization of Unmanned Aircraft Systems (UASs) 4K-video footage processing and the automation of geo-information methods targeted at both monitoring the demolition process and map** the demolished buildings. The field campaigns took place on the traditional settlement of Vrisa (Lesvos, Greece), which was heavily damaged by a strong earthquake (Mw=6.3) on June 12th, 2017. For this purpose, a flight campaign took place on 3rd February 2019 for collecting aerial 4K video footage using an Unmanned Aircraft. The Structure from Motion (SfM) method was applied on frames which derived from the 4K video footage, for producing accurate and very detailed 3D point clouds, as well as the Digital Surface Model (DSM) of the building stock of the Vrisa traditional settlement, twenty months after the earthquake. This dataset has been compared with the corresponding one which derived from 25th July 2017, a few days after the earthquake. Two algorithms have been developed for detecting the demolished buildings of the affected area, based on the DSMs and 3D point clouds, correspondingly. The results obtained have been tested through field studies and demonstrate that this methodology is feasible and effective in building demolition detection, giving very accurate results (97%) and, in parallel, is easily applicable and suit well for rapid demolition map** during the recovery phase of a post-earthquake scenario. The significant advantage of the proposed methodology is its ability to provide reliable results in a very low cost and time-efficient way and to serve all stakeholders and national and local organizations that are responsible for post-earthquake management. Full article
(This article belongs to the Special Issue Geomatics and Geo-Information in Earthquake Studies)
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17 pages, 5758 KiB  
Article
An Accurate Matching Method for Projecting Vector Data into Surveillance Video to Monitor and Protect Cultivated Land
by Zhenfeng Shao, Congmin Li, Deren Li, Orhan Altan, Lei Zhang and Lin Ding
ISPRS Int. J. Geo-Inf. 2020, 9(7), 448; https://doi.org/10.3390/ijgi9070448 - 17 Jul 2020
Cited by 50 | Viewed by 3528
Abstract
The integration of intelligent video surveillance and GIS (geograhical information system) data provides a new opportunity for monitoring and protecting cultivated land. For a GIS-based video monitoring system, the prerequisite is to align the GIS data with video image. However, existing methods or [...] Read more.
The integration of intelligent video surveillance and GIS (geograhical information system) data provides a new opportunity for monitoring and protecting cultivated land. For a GIS-based video monitoring system, the prerequisite is to align the GIS data with video image. However, existing methods or systems have their own shortcomings when implemented in monitoring cultivated land. To address this problem, this paper aims to propose an accurate matching method for projecting vector data into surveillance video, considering the topographic characteristics of cultivated land in plain area. Once an adequate number of control points are identified from 2D (two-dimensional) GIS data and the selected reference video image, the alignment of 2D GIS data and PTZ (pan-tilt-zoom) video frames can be realized by automatic feature matching method. Based on the alignment results, we can easily identify the occurrence of farmland destruction by visually inspecting the image content covering the 2D vector area. Furthermore, a prototype of intelligent surveillance video system for cultivated land is constructed and several experiments are conducted to validate the proposed approach. Experimental results show that the proposed alignment methods can achieve a high accuracy and satisfy the requirements of cultivated land monitoring. Full article
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21 pages, 5753 KiB  
Article
High Resolution Viewscape Modeling Evaluated Through Immersive Virtual Environments
by Payam Tabrizian, Anna Petrasova, Perver K. Baran, Jelena Vukomanovic, Helena Mitasova and Ross K. Meentemeyer
ISPRS Int. J. Geo-Inf. 2020, 9(7), 445; https://doi.org/10.3390/ijgi9070445 - 17 Jul 2020
Cited by 8 | Viewed by 3662
Abstract
Visual characteristics of urban environments influence human perception and behavior, including choices for living, recreation and modes of transportation. Although geospatial visualizations hold great potential to better inform urban planning and design, computational methods are lacking to realistically measure and model urban and [...] Read more.
Visual characteristics of urban environments influence human perception and behavior, including choices for living, recreation and modes of transportation. Although geospatial visualizations hold great potential to better inform urban planning and design, computational methods are lacking to realistically measure and model urban and parkland viewscapes at sufficiently fine-scale resolution. In this study, we develop and evaluate an integrative approach to measuring and modeling fine-scale viewscape characteristics of a mixed-use urban environment, a city park. Our viewscape approach improves the integration of geospatial and perception elicitation techniques by combining high-resolution lidar-based digital surface models, visual obstruction, and photorealistic immersive virtual environments (IVEs). We assessed the realism of our viewscape models by comparing metrics of viewscape composition and configuration to human subject evaluations of IVEs across multiple landscape settings. We found strongly significant correlations between viewscape metrics and participants’ perceptions of viewscape openness and naturalness, and moderately strong correlations with landscape complexity. These results suggest that lidar-enhanced viewscape models can adequately represent visual characteristics of fine-scale urban environments. Findings also indicate the existence of relationships between human perception and landscape pattern. Our approach allows urban planners and designers to model and virtually evaluate high-resolution viewscapes of urban parks and natural landscapes with fine-scale details never before demonstrated. Full article
(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)
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18 pages, 12046 KiB  
Article
A Machine Learning Approach to Delineating Neighborhoods from Geocoded Appraisal Data
by Rao Hamza Ali, Josh Graves, Stanley Wu, Jenny Lee and Erik Linstead
ISPRS Int. J. Geo-Inf. 2020, 9(7), 451; https://doi.org/10.3390/ijgi9070451 - 17 Jul 2020
Cited by 1 | Viewed by 3670
Abstract
Identification of neighborhoods is an important, financially-driven topic in real estate. It is known that the real estate industry uses ZIP (postal) codes and Census tracts as a source of land demarcation to categorize properties with respect to their price. These demarcated boundaries [...] Read more.
Identification of neighborhoods is an important, financially-driven topic in real estate. It is known that the real estate industry uses ZIP (postal) codes and Census tracts as a source of land demarcation to categorize properties with respect to their price. These demarcated boundaries are static and are inflexible to the shift in the real estate market and fail to represent its dynamics, such as in the case of an up-and-coming residential project. Delineated neighborhoods are also used in socioeconomic and demographic analyses where statistics are computed at a neighborhood level. Current practices of delineating neighborhoods have mostly ignored the information that can be extracted from property appraisals. This paper demonstrates the potential of using only the distance between subjects and their comparable properties, identified in an appraisal, to delineate neighborhoods that are composed of properties with similar prices and features. Using spatial filters, we first identify regions with the most appraisal activity, and through the application of a spatial clustering algorithm, generate neighborhoods composed of properties sharing similar characteristics. Through an application of bootstrapped linear regression, we find that delineating neighborhoods using geolocation of subjects and comparable properties explains more variation in a property’s features, such as valuation, square footage, and price per square foot, than ZIP codes or Census tracts. We also discuss the ability of the neighborhoods to grow and shrink over the years, due to shifts in each housing submarket. Full article
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36 pages, 7836 KiB  
Article
Measuring Accessibility to Various ASFs from Public Transit using Spatial Distance Measures in Indian Cities
by Pavan Teja Yenisetty and Pankaj Bahadure
ISPRS Int. J. Geo-Inf. 2020, 9(7), 446; https://doi.org/10.3390/ijgi9070446 - 17 Jul 2020
Cited by 10 | Viewed by 4247
Abstract
Nowadays, accessibility to facilities is one of the most discussed issues in sustainable urban planning. In the current research, two spatial distance accessibility measures were applied to evaluate the accessibility to amenities, services, and facilities (ASFs) from public transit (PT) by walking distance [...] Read more.
Nowadays, accessibility to facilities is one of the most discussed issues in sustainable urban planning. In the current research, two spatial distance accessibility measures were applied to evaluate the accessibility to amenities, services, and facilities (ASFs) from public transit (PT) by walking distance in six Indian cities. The first stage accounts for distance measures using the Euclidean distance with a new methodical approach derived from the built-up area with a spatial resolution of 30 m from Landsat data, and for the network distance method, the actual road distances using OpenStreetMap (OSM) for different threshold ranges of distances were derived. Meanwhile, in the second stage, indicators such as built-up area, network connectivity, and network density with the percentage of ASFs are evaluated and combined for normalization process for ranking the city. The present study assesses the accessibility to various ASFs from PT at city level and explores whether the actual road network access (by measuring distance) in Indian cities is contributing to a high level of accessibility. It adopts a unique approach using statistical tools while assessing both Euclidean and network distances. It models a framework for overall benchmarking in all six cities by ranking them for their accessibility. The results show various scenarios in terms of the rank of cities, which had been strongly affected by distance metrics (Euclidean vs. network) and thus emphasize the careful use of these measures as supporting tools for planning. This facilitates the identification of the local barriers and problems with network access that affect the actual distance. This unique approach can help policymakers to identify the gaps in PT coverage for reaching ASFs. Furthermore, it helps in crucial implementation by strategic planning that can be achieved using these distance criteria. Full article
(This article belongs to the Special Issue Measuring, Map**, Modeling, and Visualization of Cities)
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19 pages, 3164 KiB  
Article
Capacitated Refuge Assignment for Speedy and Reliable Evacuation
by Takanori Hara, Masahiro Sasabe, Taiki Matsuda and Shoji Kasahara
ISPRS Int. J. Geo-Inf. 2020, 9(7), 442; https://doi.org/10.3390/ijgi9070442 - 16 Jul 2020
Cited by 5 | Viewed by 2611
Abstract
When a large-scale disaster occurs, each evacuee should move to an appropriate refuge in a speedy and safe manner. Most of the existing studies on the refuge assignment consider the speediness of evacuation and refuge capacity while the safety of evacuation is not [...] Read more.
When a large-scale disaster occurs, each evacuee should move to an appropriate refuge in a speedy and safe manner. Most of the existing studies on the refuge assignment consider the speediness of evacuation and refuge capacity while the safety of evacuation is not taken into account. In this paper, we propose a refuge assignment scheme that considers both the speediness and safety of evacuation under the refuge capacity constraint. We first formulate the refuge assignment problem as a two-step integer linear program (ILP). Since the two-step ILP requires route candidates between evacuees and their possible refuges, we further propose a speedy and reliable route selection scheme as an extension of the existing route selection scheme. Through numerical results using the actual data of Arako district of Nagoya city in Japan, we show that the proposed scheme can improve the average route reliability among evacuees by 13.6% while suppressing the increase of the average route length among evacuees by 7.3%, compared with the distance-based route selection and refuge assignment. In addition, we also reveal that the current refuge capacity is not enough to support speedy and reliable evacuation for the residents. Full article
(This article belongs to the Special Issue Geomatics and Geo-Information in Earthquake Studies)
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22 pages, 4697 KiB  
Article
Analyzing Links between Spatio-Temporal Metrics of Built-Up Areas and Socio-Economic Indicators on a Semi-Global Scale
by Marta Sapena, Luis A. Ruiz and Hannes Taubenböck
ISPRS Int. J. Geo-Inf. 2020, 9(7), 436; https://doi.org/10.3390/ijgi9070436 - 11 Jul 2020
Cited by 9 | Viewed by 4112
Abstract
Manifold socio-economic processes shape the built and natural elements in urban areas. They thus influence both the living environment of urban dwellers and sustainability in many dimensions. Monitoring the development of the urban fabric and its relationships with socio-economic and environmental processes will [...] Read more.
Manifold socio-economic processes shape the built and natural elements in urban areas. They thus influence both the living environment of urban dwellers and sustainability in many dimensions. Monitoring the development of the urban fabric and its relationships with socio-economic and environmental processes will help to elucidate their linkages and, thus, aid in the development of new strategies for more sustainable development. In this study, we identified empirical and significant relationships between income, inequality, GDP, air pollution and employment indicators and their change over time with the spatial organization of the built and natural elements in functional urban areas. We were able to demonstrate this in 32 countries using spatio-temporal metrics, using geoinformation from databases available worldwide. We employed random forest regression, and we were able to explain 32% to 68% of the variability of socio-economic variables. This confirms that spatial patterns and their change are linked to socio-economic indicators. We also identified the spatio-temporal metrics that were more relevant in the models: we found that urban compactness, concentration degree, the dispersion index, the densification of built-up growth, accessibility and land-use/land-cover density and change could be used as proxies for some socio-economic indicators. This study is a first and fundamental step for the identification of such relationships at a global scale. The proposed methodology is highly versatile, the inclusion of new datasets is straightforward, and the increasing availability of multi-temporal geospatial and socio-economic databases is expected to empirically boost the study of these relationships from a multi-temporal perspective in the near future. Full article
(This article belongs to the Special Issue Geodata Science and Spatial Analysis in Urban Studies)
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25 pages, 50699 KiB  
Article
Multidimensional Visualization and Processing of Big Open Urban Geospatial Data on the Web
by Candan Eylül Kilsedar and Maria Antonia Brovelli
ISPRS Int. J. Geo-Inf. 2020, 9(7), 434; https://doi.org/10.3390/ijgi9070434 - 11 Jul 2020
Cited by 13 | Viewed by 11136
Abstract
The focus of this research is addressing a subset of the geovisualization (i.e., geographic visualization) challenges identified in the literature, namely multidimensional vector and raster geospatial data visualization. Moreover, the work implements an approach for multidimensional raster geospatial data processing. The results of [...] Read more.
The focus of this research is addressing a subset of the geovisualization (i.e., geographic visualization) challenges identified in the literature, namely multidimensional vector and raster geospatial data visualization. Moreover, the work implements an approach for multidimensional raster geospatial data processing. The results of this research are provided through a geoportal comprised of multiple applications that are related to 3D visualization of cities, ground deformation, land use and land cover and mobility. In a subset of the applications, the datasets handled are considered to be large in volume. The geospatial data were visualized on dynamic and interactive virtual globes to enable visual exploration. The geoportal is available on the web to enable cross-platform access to it. Furthermore, the geoportal was developed employing open standards, free and open source software (FOSS) and open data, most importantly to ensure interoperability and reduce the barriers to access it. The geoportal brings together various datasets, different both in terms of context and format employing numerous technologies. As a result, the existing web technologies for geovisualization and geospatial data processing were examined and exemplary and innovative software was developed to extend the state of the art. Full article
(This article belongs to the Special Issue Geodata Science and Spatial Analysis in Urban Studies)
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26 pages, 10737 KiB  
Article
Research on the Colors of Military Symbols in Digital Situation Maps Based on Event-Related Potential Technology
by Yafeng Niu, Guorui Ma, Wei Xue, Chengqi Xue, Tianyu Zhou, Yue Gao, Hongrui Zuo and Tao **
ISPRS Int. J. Geo-Inf. 2020, 9(7), 420; https://doi.org/10.3390/ijgi9070420 - 30 Jun 2020
Cited by 4 | Viewed by 5209
Abstract
Under the trend of increasingly informationalized military operations and the increasing maneuverability of combat units, military commanders have put forward higher requirements for the accuracy and promptness of information on battlefield situation maps. Based on the sea battlefield, this paper studies the pros [...] Read more.
Under the trend of increasingly informationalized military operations and the increasing maneuverability of combat units, military commanders have put forward higher requirements for the accuracy and promptness of information on battlefield situation maps. Based on the sea battlefield, this paper studies the pros and cons of the color matching of military symbols on sea situation maps. Fifteen colors, where each Hue had five colors, were chosen using the Munsell Color System according to Chroma axis and the Value axis on a span of 2 and 4. By collecting and analyzing the P300 EEG data, reaction time data, and accuracy data of 20 subjects, a better color matching selection of military symbols on pure color (L = 85, a = −10, and b = −23) sea situation maps is put forward, and the conclusions are as follows: (1) the different colors all cause the P300 component in EEG experiment. Among them, the P300 amplitude that is caused by military symbols with lower Chroma is smaller and the latency is shorter, indicating that the user experience and efficiency of low Chroma color symbols will be better than those with high Chroma color symbols. (2) High Value color map military symbols cause higher P300 amplitude and longer latency. According to the results above, this paper puts forward three optimized colors, namely, blue (L = 39, a = 20, and b = −49), green (L = 80, a = −72, and b = 72), and red (L = 20, a = 41, and b = 28). Additionally, three map interfaces were designed to confirm the validity of these colors. By means of applying the NASA-TLX (Task Load Index) scale to evaluate the task load of the confirmation interfaces, it can be concluded that these three optimized colors are preferred by users who are skilled in GIS and interface design. Therefore, the research conclusion of this paper can provide important reference values for military map design, which is helpful in shortening the identification and judgment time during the use of situation maps and it can improve users’ operation performance. Full article
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23 pages, 4154 KiB  
Article
Numbers on Thematic Maps: Helpful Simplicity or Too Raw to Be Useful for Map Reading?
by Jolanta Korycka-Skorupa and Izabela Małgorzata Gołębiowska
ISPRS Int. J. Geo-Inf. 2020, 9(7), 415; https://doi.org/10.3390/ijgi9070415 - 28 Jun 2020
Cited by 9 | Viewed by 3832
Abstract
As the development of small-scale thematic cartography continues, there is a growing interest in simple graphic solutions, e.g., in the form of numerical values presented on maps to replace or complement well-established quantitative cartographic methods of presentation. Numbers on maps are used as [...] Read more.
As the development of small-scale thematic cartography continues, there is a growing interest in simple graphic solutions, e.g., in the form of numerical values presented on maps to replace or complement well-established quantitative cartographic methods of presentation. Numbers on maps are used as an independent form of data presentation or function as a supplement to the cartographic presentation, becoming a legend placed directly on the map. Despite the frequent use of numbers on maps, this relatively simple form of presentation has not been extensively empirically evaluated. This article presents the results of an empirical study aimed at comparing the usability of numbers on maps for the presentation of quantitative information to frequently used proportional symbols, for simple map-reading tasks. The study showed that the use of numbers on single-variable and two-variable maps results in a greater number of correct answers and also often an improved response time compared to the use of proportional symbols. Interestingly, the introduction of different sizes of numbers did not significantly affect their usability. Thus, it has been proven that—for some tasks—map users accept this bare-bones version of data presentation, often demonstrating a higher level of preference for it than for proportional symbols. Full article
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20 pages, 4400 KiB  
Article
A Sightseeing Spot Recommendation System That Takes into Account the Visiting Frequency of Users
by Yudai Kato and Kayoko Yamamoto
ISPRS Int. J. Geo-Inf. 2020, 9(7), 411; https://doi.org/10.3390/ijgi9070411 - 27 Jun 2020
Cited by 14 | Viewed by 3094
Abstract
The present study aimed to design, develop, operate and evaluate a sightseeing spot recommendation system that can efficiently and usefully support tourists while considering their visiting frequencies. This system was developed by integrating social networking services (SNSs), Web-geographic information systems (GIS) and recommendation [...] Read more.
The present study aimed to design, develop, operate and evaluate a sightseeing spot recommendation system that can efficiently and usefully support tourists while considering their visiting frequencies. This system was developed by integrating social networking services (SNSs), Web-geographic information systems (GIS) and recommendation systems. The system recommends sightseeing spots to users with different visiting frequencies, adopting two recommendation methods (knowledge-based recommendation and collaborative recommendation methods). Additionally, the system was operated for six weeks in Kamakura City, Kanagawa Prefecture, Japan, and the total number of users was 61. Based on the results of the web questionnaire survey, the usefulness of the system when sightseeing was high, and the recommendation function of sightseeing spots, which is an original function, received mainly good ratings. From the results of the access analysis of users’ log data, the total number of sessions in this system was 329, 77% used mobile devices, and smartphones were used most frequently. Therefore, it is evident that the system was used by different types of devices just as it was designed for, and that the system was used according to the purpose of the present study, which is to support the sightseeing activities of users. Full article
(This article belongs to the Special Issue Multimedia Cartography)
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18 pages, 6859 KiB  
Article
A Simplified Method of Cartographic Visualisation of Buildings’ Interiors (2D+) for Navigation Applications
by Dariusz Gotlib, Michał Wyszomirski and Miłosz Gnat
ISPRS Int. J. Geo-Inf. 2020, 9(6), 407; https://doi.org/10.3390/ijgi9060407 - 26 Jun 2020
Cited by 7 | Viewed by 3243
Abstract
This article proposes an original method of a coherent and simplified cartographic presentation of the interior of buildings called 2D+, which can be used in geoinformation applications that do not support an extensive three-dimensional visualisation or do not have access to a 3D [...] Read more.
This article proposes an original method of a coherent and simplified cartographic presentation of the interior of buildings called 2D+, which can be used in geoinformation applications that do not support an extensive three-dimensional visualisation or do not have access to a 3D model of the building. A simplified way of cartographic visualisation can be used primarily in indoor navigation systems and other location-based services (LBS) applications. It can also be useful in systems supporting facility management (FM) and various kinds of geographic information systems (GIS). On the one hand, it may increase an application’s efficiency; on the other, it may unify the method of visualisation in the absence of a building’s 3D model. Thanks to the proposed method, it is possible to achieve the same effect regardless of the data source used: Building Information Modelling (BIM), a Computer-aided Design (CAD) model, or traditional architectural and construction drawings. Such a solution may be part of a broader concept of a multi-scale presentation of buildings’ interiors. The article discusses the issues of visualising data and converting data to the appropriate coordinate system, as well as the properties of the application model of data. Full article
(This article belongs to the Special Issue Geovisualization and Map Design)
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21 pages, 55347 KiB  
Article
Evaluating the Influence of Urban Morphology on Urban Wind Environment Based on Computational Fluid Dynamics Simulation
by Chia-An Ku and Hung-Kai Tsai
ISPRS Int. J. Geo-Inf. 2020, 9(6), 399; https://doi.org/10.3390/ijgi9060399 - 17 Jun 2020
Cited by 23 | Viewed by 4390
Abstract
Due to urbanization around the world, people living in urban areas have been suffering from a series of negative effects caused by changes in urban microclimate, especially when it comes to urban heat islands (UHIs). To mitigate UHIs, management of urban wind environments [...] Read more.
Due to urbanization around the world, people living in urban areas have been suffering from a series of negative effects caused by changes in urban microclimate, especially when it comes to urban heat islands (UHIs). To mitigate UHIs, management of urban wind environments is increasingly considered as a crucial part of the process. Computational fluid dynamics (CFD) simulation of wind fields has become a prevailing method to explore the relationship between morphological factors and wind environment. However, most studies are focused on building scale and fail to reflect the effects of comprehensive planning. In addition, the combined influence of different morphological factors on wind environment is rarely discussed. Therefore, this study tries to explore the relationship between urban morphology and wind environment in a new-town area. CFD method was applied to simulate the wind field, and 11 scenarios based on criteria according to existing literature, planning regulations and local characteristics were developed. The simulation results from different scenarios show that the impact of the five selected factors on wind speeds was non-linear, and the impact varied significantly among different areas of the study region. Simulation of the differences in regional wind speeds among different planning scenarios can provide strong decision-making support. Full article
(This article belongs to the Special Issue The Applications of 3D-City Models in Urban Studies)
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14 pages, 3900 KiB  
Communication
Terrain Analysis in Google Earth Engine: A Method Adapted for High-Performance Global-Scale Analysis
by José Lucas Safanelli, Raul Roberto Poppiel, Luis Fernando Chimelo Ruiz, Benito Roberto Bonfatti, Fellipe Alcantara de Oliveira Mello, Rodnei Rizzo and José A. M. Demattê
ISPRS Int. J. Geo-Inf. 2020, 9(6), 400; https://doi.org/10.3390/ijgi9060400 - 17 Jun 2020
Cited by 44 | Viewed by 8987
Abstract
Terrain analysis is an important tool for modeling environmental systems. Aiming to use the cloud-based computing capabilities of Google Earth Engine (GEE), we customized an algorithm for calculating terrain attributes, such as slope, aspect, and curvatures, for different resolution and geographical extents. The [...] Read more.
Terrain analysis is an important tool for modeling environmental systems. Aiming to use the cloud-based computing capabilities of Google Earth Engine (GEE), we customized an algorithm for calculating terrain attributes, such as slope, aspect, and curvatures, for different resolution and geographical extents. The calculation method is based on geometry and elevation values estimated within a 3 × 3 spheroidal window, and it does not rely on projected elevation data. Thus, partial derivatives of terrain are calculated considering the great circle distances of reference nodes of the topographic surface. The algorithm was developed using the JavaScript programming interface of the online code editor of GEE and can be loaded as a custom package. The algorithm also provides an additional feature for making the visualization of terrain maps with a dynamic legend scale, which is useful for map** different extents: from local to global. We compared the consistency of the proposed method with an available but limited terrain analysis tool of GEE, which resulted in a correlation of 0.89 and 0.96 for aspect and slope over a near-global scale, respectively. In addition to this, we compared the slope, aspect, horizontal, and vertical curvature of a reference site (Mount Ararat) to their equivalent attributes estimated on the System for Automated Geospatial Analysis (SAGA), which achieved a correlation between 0.96 and 0.98. The visual correspondence of TAGEE and SAGA confirms its potential for terrain analysis. The proposed algorithm can be useful for making terrain analysis scalable and adapted to customized needs, benefiting from the high-performance interface of GEE. Full article
(This article belongs to the Special Issue Big Data Computing for Geospatial Applications)
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29 pages, 10016 KiB  
Article
Measuring Accessibility of Healthcare Facilities for Populations with Multiple Transportation Modes Considering Residential Transportation Mode Choice
by **nxin Zhou, Zhaoyuan Yu, Linwang Yuan, Lei Wang and Changbin Wu
ISPRS Int. J. Geo-Inf. 2020, 9(6), 394; https://doi.org/10.3390/ijgi9060394 - 16 Jun 2020
Cited by 28 | Viewed by 4952
Abstract
Accessibility research of healthcare facilities is develo** towards multiple transportation modes (MTM), which are influenced by residential transportation choices and preferences. Due to differences in travel impact factors such as traffic conditions, origin location, distance to the destination, and economic cost, residents’ daily [...] Read more.
Accessibility research of healthcare facilities is develo** towards multiple transportation modes (MTM), which are influenced by residential transportation choices and preferences. Due to differences in travel impact factors such as traffic conditions, origin location, distance to the destination, and economic cost, residents’ daily travel presents different residential transportation mode choices (RTMC). The purpose of our study was to measure the spatial accessibility of healthcare facilities based on MTM considering RTMC (MTM-RTMC). We selected the gravity two-step floating catchment area method (G2SFCA) as a fundamental model. Through the single transportation mode (STM), MTM, and MTM-RTMC, three aspects used to illustrate and redesign the G2SFCA, we obtained the MTM-RTMC G2SFCA model that integrates RTMC probabilities and the travel friction coefficient. We selected Nan**g as the experimental area, used route planning data of four modes (including driving, walking, public transportation, and bicycling) from a web map** platform, and applied the three models to pediatric clinic services to measure accessibility. The results show that the MTM-RTMC mechanism is to make up for the traditional estimation of accessibility, which loses sight of the influence of residential transportation choices. The MTM-RTMC mechanism that provides a more realistic and reliable way can generalize to major accessibility models and offers preferable guidance for policymakers. Full article
(This article belongs to the Special Issue Measuring, Map**, Modeling, and Visualization of Cities)
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21 pages, 6006 KiB  
Article
National-Scale Landslide Susceptibility Map** in Austria Using Fuzzy Best-Worst Multi-Criteria Decision-Making
by Meisam Moharrami, Amin Naboureh, Thimmaiah Gudiyangada Nachappa, Omid Ghorbanzadeh, Xudong Guan and Thomas Blaschke
ISPRS Int. J. Geo-Inf. 2020, 9(6), 393; https://doi.org/10.3390/ijgi9060393 - 16 Jun 2020
Cited by 27 | Viewed by 3836
Abstract
Landslides are one of the most detrimental geological disasters that intimidate human lives along with severe damages to infrastructures and they mostly occur in the mountainous regions across the globe. Landslide susceptibility map** (LSM) serves as a key step in assessing potential areas [...] Read more.
Landslides are one of the most detrimental geological disasters that intimidate human lives along with severe damages to infrastructures and they mostly occur in the mountainous regions across the globe. Landslide susceptibility map** (LSM) serves as a key step in assessing potential areas that are prone to landslides and could have an impact on decreasing the possible damages. The application of the fuzzy best-worst multi-criteria decision-making (FBWM) method was applied for LSM in Austria. Further, the role of employing a few numbers of pairwise comparisons on LSM was investigated by comparing the FBWM and Fuzzy Analytical Hierarchical Process (FAHP). For this study, a wide range of data was sourced from the Geological Survey of Austria, the Austrian Land Information System, Humanitarian OpenStreetMap Team, and remotely sensed data were collected. We used nine conditioning factors that were based on the previous studies and geomorphological characteristics of Austria, such as elevation, slope, slope aspect, lithology, rainfall, land cover, distance to drainage, distance to roads, and distance to faults. Based on the evaluation of experts, the slope conditioning factor was chosen as the best criterion (highest impact on LSM) and the distance to roads was considered as the worst criterion (lowest impact on LSM). LSM was generated for the region based on the best and worst criterion. The findings show the robustness of FBWM in landslide susceptibility map**. Additionally, using fewer pairwise comparisons revealed that the FBWM can obtain higher accuracy as compared to FAHP. The finding of this research can help authorities and decision-makers to provide effective strategies and plans for landslide prevention and mitigation at the national level. Full article
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15 pages, 1708 KiB  
Article
A Map Is a Living Structure with the Recurring Notion of Far More Smalls than Larges
by Bin Jiang and Terry Slocum
ISPRS Int. J. Geo-Inf. 2020, 9(6), 388; https://doi.org/10.3390/ijgi9060388 - 11 Jun 2020
Cited by 5 | Viewed by 4327
Abstract
The Earth’s surface or any territory is a coherent whole or subwhole, in which the notion of “far more small things than large ones” recurs at different levels of scale ranging from the smallest of a couple of meters to the largest of [...] Read more.
The Earth’s surface or any territory is a coherent whole or subwhole, in which the notion of “far more small things than large ones” recurs at different levels of scale ranging from the smallest of a couple of meters to the largest of the Earth’s surface or that of the territory. The coherent whole has the underlying character called wholeness or living structure, which is a physical phenomenon pervasively existing in our environment and can be defined mathematically under the new third view of space conceived and advocated by Christopher Alexander: space is neither lifeless nor neutral, but a living structure capable of being more alive or less alive. This paper argues that both the map and the territory are a living structure, and that it is the inherent hierarchy of “far more smalls than larges” that constitutes the foundation of maps and map**. It is the underlying living structure of geographic space or geographic features that makes maps or map** possible, i.e., larges to be retained, while smalls to be omitted in a recursive manner (Note: larges and smalls should be understood broadly and wisely, in terms of not only sizes, but also topological connectivity and semantic meaning). Thus, map making is largely an objective undertaking governed by the underlying living structure, and maps portray the truth of the living structure. Based on the notion of living structure, a map can be considered to be an iterative system, which means that the map is the map of the map of the map, and so on endlessly. The word endlessly means continuous map scales between two discrete ones, just as there are endless real numbers between 1 and 2. The iterated map system implies that each of the subsequent small-scale maps is a subset of the single large-scale map, not a simple subset but with various constraints to make all geographic features topologically correct. Full article
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18 pages, 3242 KiB  
Article
Evaluating Temporal Approximation Methods Using Burglary Data
by Lukas Oswald and Michael Leitner
ISPRS Int. J. Geo-Inf. 2020, 9(6), 386; https://doi.org/10.3390/ijgi9060386 - 10 Jun 2020
Cited by 3 | Viewed by 3867
Abstract
Law enforcement is very interested in knowing when a crime has happened. Unfortunately, the occurrence time of a crime is often not exactly known. In such circumstances, estimating the most likely time that a crime has happened is crucial for spatio-temporal analysis. The [...] Read more.
Law enforcement is very interested in knowing when a crime has happened. Unfortunately, the occurrence time of a crime is often not exactly known. In such circumstances, estimating the most likely time that a crime has happened is crucial for spatio-temporal analysis. The main purpose of this research is to introduce two novel temporal approximation methods, termed retrospective temporal analysis (RTA) and extended retrospective temporal analysis (RTAext). Both methods are compared to six existing temporal approximation methods and subsequently evaluated in order to identify the method that can most accurately estimate the occurrence time of crimes. This research is conducted with 100,000+ burglary crimes from the city of Vienna, Austria provided by the Criminal Intelligence Service Austria, from 2009–2015. The RTA method assumes that crimes in the immediate past occur at very similar times as in the present and in the future. Historical crimes with accurately known time stamps can therefore be applied to estimate when crimes occur in the present/future. The RTAext method enhances one existing temporal approximation method, aoristicext, with probability values derived from historical crime data with accurately known time stamps. The results show that the RTA method performs superiorly to all other temporal approximation methods, including the novel RTAext method, in two out of the three crime types analyzed. Additionally, the RTAext method shows very good results that are similar to the best performing existing approximation methods. Full article
(This article belongs to the Special Issue Urban Crime Map** and Analysis Using GIS)
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25 pages, 10353 KiB  
Article
A Thematic Similarity Network Approach for Analysis of Places Using Volunteered Geographic Information
by **aoyi Yuan, Andrew Crooks and Andreas Züfle
ISPRS Int. J. Geo-Inf. 2020, 9(6), 385; https://doi.org/10.3390/ijgi9060385 - 10 Jun 2020
Cited by 4 | Viewed by 3956
Abstract
The research presented in this paper proposes a thematic network approach to explore rich relationships between places. We connect places in networks through their thematic similarities by applying topic modeling to the textual volunteered geographic information (VGI) pertaining to the places. The network [...] Read more.
The research presented in this paper proposes a thematic network approach to explore rich relationships between places. We connect places in networks through their thematic similarities by applying topic modeling to the textual volunteered geographic information (VGI) pertaining to the places. The network approach enhances previous research involving place clustering using geo-textual information, which often simplifies relationships between places to be either in-cluster or out-of-cluster. To demonstrate our approach, we use as a case study in Manhattan (New York) that compares networks constructed from three different geo-textural data sources—TripAdvisor attraction reviews, TripAdvisor restaurant reviews, and Twitter data. The results showcase how the thematic similarity network approach enables us to conduct clustering analysis as well as node-to-node and node-to-cluster analysis, which is fruitful for understanding how places are connected through individuals’ experiences. Furthermore, by enriching the networks with geodemographic information as node attributes, we discovered that some low-income communities in Manhattan have distinctive restaurant cultures. Even though geolocated tweets are not always related to place they are posted from, our case study demonstrates that topic modeling is an efficient method to filter out the place-irrelevant tweets and therefore refining how of places can be studied. Full article
(This article belongs to the Special Issue Geo-Enriched Data Modeling & Mining)
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19 pages, 8572 KiB  
Article
Machine Learning Generalisation across Different 3D Architectural Heritage
by Eleonora Grilli and Fabio Remondino
ISPRS Int. J. Geo-Inf. 2020, 9(6), 379; https://doi.org/10.3390/ijgi9060379 - 9 Jun 2020
Cited by 46 | Viewed by 7085
Abstract
The use of machine learning techniques for point cloud classification has been investigated extensively in the last decade in the geospatial community, while in the cultural heritage field it has only recently started to be explored. The high complexity and heterogeneity of 3D [...] Read more.
The use of machine learning techniques for point cloud classification has been investigated extensively in the last decade in the geospatial community, while in the cultural heritage field it has only recently started to be explored. The high complexity and heterogeneity of 3D heritage data, the diversity of the possible scenarios, and the different classification purposes that each case study might present, makes it difficult to realise a large training dataset for learning purposes. An important practical issue that has not been explored yet, is the application of a single machine learning model across large and different architectural datasets. This paper tackles this issue presenting a methodology able to successfully generalise to unseen scenarios a random forest model trained on a specific dataset. This is achieved looking for the best features suitable to identify the classes of interest (e.g., wall, windows, roof and columns). Full article
(This article belongs to the Special Issue Automatic Feature Recognition from Point Clouds)
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20 pages, 4725 KiB  
Article
Uncorrelated Geo-Text Inhibition Method Based on Voronoi K-Order and Spatial Correlations in Web Maps
by Yufeng He, Yehua Sheng, Yunqing **g, Yue Yin and Ahmad Hasnain
ISPRS Int. J. Geo-Inf. 2020, 9(6), 381; https://doi.org/10.3390/ijgi9060381 - 9 Jun 2020
Cited by 3 | Viewed by 2412
Abstract
Unstructured geo-text annotations volunteered by users of web map services enrich the basic geographic data. However, irrelevant geo-texts can be added to the web map, and these geo-texts reduce utility to users. Therefore, this study proposes a method to detect uncorrelated geo-text annotations [...] Read more.
Unstructured geo-text annotations volunteered by users of web map services enrich the basic geographic data. However, irrelevant geo-texts can be added to the web map, and these geo-texts reduce utility to users. Therefore, this study proposes a method to detect uncorrelated geo-text annotations based on Voronoi k-order neighborhood partition and auto-correlation statistical models. On the basis of the geo-text classification and semantic vector transformation, a quantitative description method for spatial autocorrelation was established by the Voronoi weighting method of inverse vicinity distance. The Voronoi k-order neighborhood self-growth strategy was used to detect the minimum convergence neighborhood for spatial autocorrelation. The Pearson method was used to calculate the correlation degree of the geo-text in the convergence region and then deduce the type of geo-text to be filtered. Experimental results showed that for given geo-text types in the study region, the proposed method effectively calculated the correlation between new geo-texts and the convergence region, providing an effective suggestion for preventing uncorrelated geo-text from uploading to the web map environment. Full article
(This article belongs to the Special Issue Advances in Computational Approaches for Spatial Analysis and Modeling)
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19 pages, 13149 KiB  
Article
Flight Planning for LiDAR-Based UAS Map** Applications
by Bashar Alsadik and Fabio Remondino
ISPRS Int. J. Geo-Inf. 2020, 9(6), 378; https://doi.org/10.3390/ijgi9060378 - 8 Jun 2020
Cited by 19 | Viewed by 7418
Abstract
In the last two decades, unmanned aircraft systems (UAS) were successfully used in different environments for diverse applications like territorial map**, heritage 3D documentation, as built surveys, construction monitoring, solar panel placement and assessment, road inspections, etc. These applications were correlated to the [...] Read more.
In the last two decades, unmanned aircraft systems (UAS) were successfully used in different environments for diverse applications like territorial map**, heritage 3D documentation, as built surveys, construction monitoring, solar panel placement and assessment, road inspections, etc. These applications were correlated to the onboard sensors like RGB cameras, multi-spectral cameras, thermal sensors, panoramic cameras, or LiDARs. According to the different onboard sensors, a different mission plan is required to satisfy the characteristics of the sensor and the project aims. For UAS LiDAR-based map** missions, requirements for the flight planning are different with respect to conventional UAS image-based flight plans because of different reasons related to the LiDAR scanning mechanism, scanning range, output scanning rate, field of view (FOV), rotation speed, etc. Although flight planning for image-based UAS missions is a well-known and solved problem, flight planning for a LiDAR-based UAS map** is still an open research topic that needs further investigations. The article presents the developments of a LiDAR-based UAS flight planning tool, tested with simulations in real scenarios. The flight planning simulations considered an UAS platform equipped, alternatively, with three low-cost multi-beam LiDARs, namely Quanergy M8, Velodyne VLP-16, and the Ouster OS-1-16. The specific characteristics of the three sensors were used to plan flights and acquired dense point clouds. Comparisons and analyses of the results showed clear relationships between point density, flying speeds, and flying heights. Full article
(This article belongs to the Special Issue UAV in Smart City and Smart Region)
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18 pages, 13389 KiB  
Article
A Change of Theme: The Role of Generalization in Thematic Map**
by Paulo Raposo, Guillaume Touya and Pia Bereuter
ISPRS Int. J. Geo-Inf. 2020, 9(6), 371; https://doi.org/10.3390/ijgi9060371 - 4 Jun 2020
Cited by 9 | Viewed by 5737
Abstract
Cartographic generalization research has focused almost exclusively in recent years on topographic map**, and has thereby gained an incorrect reputation for having to do only with reference or positional data. The generalization research community needs to broaden its scope to include thematic cartography [...] Read more.
Cartographic generalization research has focused almost exclusively in recent years on topographic map**, and has thereby gained an incorrect reputation for having to do only with reference or positional data. The generalization research community needs to broaden its scope to include thematic cartography and geovisualization. Generalization is not new to these areas of cartography, and has in fact always been involved in thematic geographic visualization, despite rarely being acknowledged. We illustrate this involvement with several examples of famous, public-audience thematic maps, noting the generalization procedures involved in drawing each, both across their basemap and thematic layers. We also consider, for each map example we note, which generalization operators were crucial to the formation of the map’s thematic message. The many incremental gains made by the cartographic generalization research community while treating reference data can be brought to bear on thematic cartography in the same way they were used implicitly on the well-known thematic maps we highlight here as examples. Full article
(This article belongs to the Special Issue Map Generalization)
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22 pages, 9411 KiB  
Article
Develo** Shop** and Dining Walking Indices Using POIs and Remote Sensing Data
by Yingbin Deng, Yingwei Yan, Yichun **e, Jianhui Xu, Hao Jiang, Renrong Chen and Runnan Tan
ISPRS Int. J. Geo-Inf. 2020, 9(6), 366; https://doi.org/10.3390/ijgi9060366 - 2 Jun 2020
Cited by 3 | Viewed by 3003
Abstract
Walking is one of the most commonly promoted traveling methods and is garnering increasing attention. Many indices/scores have been developed by scholars to measure the walkability in a local community. However, most existing walking indices/scores involve urban planning-oriented, local service-oriented, regional accessibility-oriented, and [...] Read more.
Walking is one of the most commonly promoted traveling methods and is garnering increasing attention. Many indices/scores have been developed by scholars to measure the walkability in a local community. However, most existing walking indices/scores involve urban planning-oriented, local service-oriented, regional accessibility-oriented, and physical activity-oriented walkability assessments. Since shop** and dining are two major leisure activities in our daily lives, more attention should be given to the shop** or dining-oriented walking environment. Therefore, we developed two additional walking indices that focus on shop** or dining. The point of interest (POI), vegetation coverage, water coverage, distance to bus/subway station, and land surface temperature were employed to construct walking indices based on 50-m street segments. Then, walking index values were categorized into seven recommendation levels. The field verification illustrates that the proposed walking indices can accurately represent the walking environment for shop** and dining. The results in this study could provide references for citizens seeking to engage in activities of shop** and dining with a good walking environment. Full article
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17 pages, 2780 KiB  
Article
Meet the Virtual Jeju Dol Harubang—The Mixed VR/AR Application for Cultural Immersion in Korea’s Main Heritage
by Kwanghee Jung, Vinh T. Nguyen, Diana Piscarac and Seung-Chul Yoo
ISPRS Int. J. Geo-Inf. 2020, 9(6), 367; https://doi.org/10.3390/ijgi9060367 - 2 Jun 2020
Cited by 49 | Viewed by 7085
Abstract
Jeju Island comes second to only Seoul as Korea’s most visited destination, yet most visitors do not have the chance to go beyond brief visits and immerse themselves in the island’s history and cultural heritage. This project introduces the cultural heritage of Jeju [...] Read more.
Jeju Island comes second to only Seoul as Korea’s most visited destination, yet most visitors do not have the chance to go beyond brief visits and immerse themselves in the island’s history and cultural heritage. This project introduces the cultural heritage of Jeju Island to visitors through virtual reality/augmented reality (VR/AR) model visualization technology, namely JejuView, which provides an intuitive way to experience cultural heritage sites on the island. The proposed VR/AR application is designed to introduce a series of heritage spots on Jeju Island through (i) a printed Jeju map with embedded QR code markers that enable viewers to experience the locations without being present at the site, (ii) a mobile device with WebGL supported browser which allows 3D content to be rendered, and (iii) an AR library (A-Frame.io) that enables enthusiasts to recreate similar work. To test the effectiveness of the proposed VR/AR application, the authors conducted an experiment with 251 participants to test the research model based on the technology acceptance model (TAM) and employed generalized structured component analysis (GSCA) for the analysis. Results show that when using sensory new media such as VR/AR, consumers are more focused on the hedonic value than on the utilitarian value of the information. In conclusion, the proposed VR/AR application is complementary to existing studies and provides significant support to researchers, engineers, and designers develo** VR/AR technologies for use in cultural education and tourism marketing. Full article
(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)
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23 pages, 17246 KiB  
Article
Constructing Geospatial Concept Graphs from Tagged Images for Geo-Aware Fine-Grained Image Recognition
by Naoko Nitta, Kazuaki Nakamura and Noboru Babaguchi
ISPRS Int. J. Geo-Inf. 2020, 9(6), 354; https://doi.org/10.3390/ijgi9060354 - 27 May 2020
Cited by 4 | Viewed by 2491
Abstract
While visual appearances play a main role in recognizing the concepts captured in images, additional information can provide complementary information for fine-grained image recognition, where concepts with similar visual appearances such as species of birds need to be distinguished. Especially for recognizing geospatial [...] Read more.
While visual appearances play a main role in recognizing the concepts captured in images, additional information can provide complementary information for fine-grained image recognition, where concepts with similar visual appearances such as species of birds need to be distinguished. Especially for recognizing geospatial concepts, which are observed only at specific places, geographical locations of the images can improve the recognition accuracy. However, such geo-aware fine-grained image recognition requires prior information about the visual and geospatial features of each concept or the training data composed of high-quality images for each concept associated with correct geographical locations. By using a large number of images photographed in various places and described with textual tags which can be collected from image sharing services such as Flickr, this paper proposes a method for constructing a geospatial concept graph which contains the necessary prior information for realizing the geo-aware fine-grained image recognition, such as a set of visually recognizable fine-grained geospatial concepts, their visual and geospatial features, and the coarse-grained representative visual concepts whose visual features can be transferred to several fine-grained geospatial concepts. Leveraging the information from the images captured by many people can automatically extract diverse types of geospatial concepts with proper features for realizing efficient and effective geo-aware fine-grained image recognition. Full article
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19 pages, 7753 KiB  
Article
Geovisualization and Geographical Analysis for Fire Prevention
by Nicklas Guldåker
ISPRS Int. J. Geo-Inf. 2020, 9(6), 355; https://doi.org/10.3390/ijgi9060355 - 27 May 2020
Cited by 2 | Viewed by 3148
Abstract
Swedish emergency services still have relatively limited resources and time for proactive fire prevention. As a result of this, there is an extensive need for strategic working methods and knowledge to take advantage of spatial analyses. In addition, decision-making based on visualizations and [...] Read more.
Swedish emergency services still have relatively limited resources and time for proactive fire prevention. As a result of this, there is an extensive need for strategic working methods and knowledge to take advantage of spatial analyses. In addition, decision-making based on visualizations and analyses of their own collected data has the potential to increase the validity of strategic decisions. The objective of this paper is to critically examine how some different geovisualization techniques—point data, kernel density and choropleth map**—actively can complement each other and be applied in fire preventive work. The results show that each technique itself has limitations, but that, in combination, they increase the scope for interpretation and the possibilities of targeting different forms of preventive measures. The investigated geovisualization techniques facilitate various forms of fire prevention such as identifying which areas to prioritize for outreach, home visits, identification and targeting of different risk groups and customized information campaigns about certain types of fires in risk-prone areas. Furthermore, fairly simple map** techniques can be utilized directly to evaluate incident reports and increase the quality of geocoded fire incidents. The study also shows how some of these techniques can be applied when analyzing residential fire incidents and their relation to underlying structural and socio-economic factors as well as spatio-temporal dimensions of fire incident data. The spatial analyses and supporting maps can help find and predict risk areas for residential fires or be used directly to formulate hypotheses on fire patterns. The generic functionality of the visualization methods makes them also useful for visual analysis of other types of incidents, such as reported crimes and accidents. Finally, the results are applicable to a work process adapted to the Swedish legislation on confidential data. Full article
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24 pages, 6068 KiB  
Review
Issues of Healthcare Planning and GIS: A Review
by Bandar Fuad Khashoggi and Abdulkader Murad
ISPRS Int. J. Geo-Inf. 2020, 9(6), 352; https://doi.org/10.3390/ijgi9060352 - 27 May 2020
Cited by 43 | Viewed by 13172
Abstract
Introduction: For the past 2400 years, the spatial relationship between health and location has been a concern for researchers. Studies have been conducted for decades to understand such a relationship, which has led to the identification of a number of healthcare planning issues. [...] Read more.
Introduction: For the past 2400 years, the spatial relationship between health and location has been a concern for researchers. Studies have been conducted for decades to understand such a relationship, which has led to the identification of a number of healthcare planning issues. Geographic Information Systems (GIS) technology has contributed to addressing such issues by applying analytical approaches at the level of epidemiological surveillance and evaluating the spatial inequality of access to healthcare. Consequently, the importance of reviewing healthcare planning issues and recognition of the role of GIS are integral to relevant studies. Such research will contribute to increasing the understanding of how to apply analytical approaches for dealing with healthcare planning issues using GIS. Methods: This paper aims to provide an examination of healthcare planning issues and focuses on reviewing the potential of GIS in dealing with such issues by applying analytical approaches. The method of a typical literature review was used through collecting data from various studies selected based on temporal and descriptive considerations. Results: Researchers have focused on develo** and applying analytical approaches using GIS to support two important aspects of healthcare planning: first, epidemic surveillance and modeling, despite a lack of health information and its management, and, second, evaluating the spatial inequality of access to healthcare in order to determine the optimum distribution of health resources. Conclusion: GIS is an effective tool to support spatial decision-making in public health through applying the evolving analytical approaches to dealing with healthcare planning issues. This requires a literature review before preparing relevant studies, particularly because of the continuous development of GIS technologies. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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20 pages, 8013 KiB  
Article
Modelling Housing Rents Using Spatial Autoregressive Geographically Weighted Regression: A Case Study in Cracow, Poland
by Mateusz Tomal
ISPRS Int. J. Geo-Inf. 2020, 9(6), 346; https://doi.org/10.3390/ijgi9060346 - 26 May 2020
Cited by 29 | Viewed by 5344
Abstract
The proportion of tenants will undoubtedly rise in Poland, where at present, the ownership housing model is very dominant. As a result, the rental housing market in Poland is currently under-researched in comparison with owner-occupancy. In order to narrow this research gap, this [...] Read more.
The proportion of tenants will undoubtedly rise in Poland, where at present, the ownership housing model is very dominant. As a result, the rental housing market in Poland is currently under-researched in comparison with owner-occupancy. In order to narrow this research gap, this study attempts to identify the determinants affecting rental prices in Cracow. The latter were obtained from the internet platform otodom.pl using the web scra** technique. To identify rent determinants, ordinary least squares (OLS) regression and spatial econometric methods were used. In particular, traditional spatial autoregressive model (SAR) and spatial autoregressive geographically weighted regression (GWR-SAR) were employed, which made it possible to take into account the spatial heterogeneity of the parameters of determinants and the spatially changing spatial autocorrelation of housing rents. In-depth analysis of rent determinants using the GWR-SAR model exposed the complexity of the rental market in Cracow. Estimates of the above model revealed that many local markets can be identified in Cracow, with different factors sha** housing rents. However, one can identify some determinants that are ubiquitous for almost the entire city. This concerns mainly the variables describing the area of the flat and the age of the building. Moreover, the Monte Carlo test indicated that the spatial autoregressive parameter also changes significantly over space. Full article
(This article belongs to the Special Issue Measuring, Map**, Modeling, and Visualization of Cities)
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20 pages, 13775 KiB  
Article
Time, Spatial, and Descriptive Features of Pedestrian Tracks on Set of Visualizations
by Łukasz Wielebski, Beata Medyńska-Gulij, Łukasz Halik and Frank Dickmann
ISPRS Int. J. Geo-Inf. 2020, 9(6), 348; https://doi.org/10.3390/ijgi9060348 - 26 May 2020
Cited by 10 | Viewed by 2830
Abstract
The aim of the paper is to elaborate on and evaluate a multiperspective cartographic visualization of the spatial behavior of pedestrians in urban space. The detailed objective is to indicate the level of usefulness of the proposed visualization methods for analyzing and interpreting [...] Read more.
The aim of the paper is to elaborate on and evaluate a multiperspective cartographic visualization of the spatial behavior of pedestrians in urban space. The detailed objective is to indicate the level of usefulness of the proposed visualization methods for analyzing and interpreting the following features: track shape (trajectory geometry), topographical truth, track length, track visibility, walking time, motivation for getting to the finish point, walking speed, stops, spatial context (spatial surroundings, street names, and so on), and trajectory similarity. Each of the elaborated visualization presents spatial data from a different perspective and visually strengthens other aspects of the behavior of participants of the experiment. Recording the movement of participants by means of global positioning system (GPS) receivers was the first method used in the research, with the other one being a questionnaire that made it possible to determine what kind of motivation pedestrians had when selecting a track leading to the finish point. The results demonstrate different levels of usefulness of the six presented visualizations for reading selected features of the spatial behavior of pedestrians. Full article
(This article belongs to the Special Issue Multimedia Cartography)
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22 pages, 6677 KiB  
Article
Crowdsourcing Street View Imagery: A Comparison of Mapillary and OpenStreetCam
by Ron Mahabir, Ross Schuchard, Andrew Crooks, Arie Croitoru and Anthony Stefanidis
ISPRS Int. J. Geo-Inf. 2020, 9(6), 341; https://doi.org/10.3390/ijgi9060341 - 26 May 2020
Cited by 24 | Viewed by 5983
Abstract
Over the last decade, Volunteered Geographic Information (VGI) has emerged as a viable source of information on cities. During this time, the nature of VGI has been evolving, with new types and sources of data continually being added. In light of this trend, [...] Read more.
Over the last decade, Volunteered Geographic Information (VGI) has emerged as a viable source of information on cities. During this time, the nature of VGI has been evolving, with new types and sources of data continually being added. In light of this trend, this paper explores one such type of VGI data: Volunteered Street View Imagery (VSVI). Two VSVI sources, Mapillary and OpenStreetCam, were extracted and analyzed to study road coverage and contribution patterns for four US metropolitan areas. Results show that coverage patterns vary across sites, with most contributions occurring along local roads and in populated areas. We also found that a few users contributed most of the data. Moreover, the results suggest that most data are being collected during three distinct times of day (i.e., morning, lunch and late afternoon). The paper concludes with a discussion that while VSVI data is still relatively new, it has the potential to be a rich source of spatial and temporal information for monitoring cities. Full article
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17 pages, 3408 KiB  
Article
Ambient Population and Larceny-Theft: A Spatial Analysis Using Mobile Phone Data
by Li He, Antonio Páez, Jianmin Jiao, ** An, Chuntian Lu, Wen Mao and Dong** Long
ISPRS Int. J. Geo-Inf. 2020, 9(6), 342; https://doi.org/10.3390/ijgi9060342 - 26 May 2020
Cited by 31 | Viewed by 4998
Abstract
In the spatial analysis of crime, the residential population has been a conventional measure of the population at risk. Recent studies suggest that the ambient population is a useful alternative measure of the population at risk that can better capture the activity patterns [...] Read more.
In the spatial analysis of crime, the residential population has been a conventional measure of the population at risk. Recent studies suggest that the ambient population is a useful alternative measure of the population at risk that can better capture the activity patterns of a population. However, current studies are limited by the availability of high precision demographic characteristics, such as social activities and the origins of residents. In this research, we use spatially referenced mobile phone data to measure the size and activity patterns of various types of ambient population, and further investigate the link between urban larceny-theft and population with multiple demographic and activity characteristics. A series of crime attractors, generators, and detractors are also considered in the analysis to account for the spatial variation of crime opportunities. The major findings based on a negative binomial model are three-fold. (1) The size of the non-local population and people’s social regularity calculated from mobile phone big data significantly correlate with the spatial variation of larceny-theft. (2) Crime attractors, generators, and detractors, measured by five types of Points of Interest (POIs), significantly depict the criminality of places and impact opportunities for crime. (3) Higher levels of nighttime light are associated with increased levels of larceny-theft. The results have practical implications for linking the ambient population to crime, and the insights are informative for several theories of crime and crime prevention efforts. Full article
(This article belongs to the Special Issue Using GIS to Improve (Public) Safety and Security)
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16 pages, 18121 KiB  
Article
Fine-Scale Dasymetric Population Map** with Mobile Phone and Building Use Data Based on Grid Voronoi Method
by Zhenghong Peng, Ru Wang, Lingbo Liu and Hao Wu
ISPRS Int. J. Geo-Inf. 2020, 9(6), 344; https://doi.org/10.3390/ijgi9060344 - 26 May 2020
Cited by 8 | Viewed by 2944
Abstract
Fine-scale population map** is of great significance for capturing the spatial and temporal distribution of the urban population. Compared with traditional census data, population data obtained from mobile phone data has high availability and high real-time performance. However, the spatial distribution of base [...] Read more.
Fine-scale population map** is of great significance for capturing the spatial and temporal distribution of the urban population. Compared with traditional census data, population data obtained from mobile phone data has high availability and high real-time performance. However, the spatial distribution of base stations is uneven, and the service boundaries remain uncertain, which brings significant challenges to the accuracy of dasymetric population map**. This paper proposes a Grid Voronoi method to provide reliable spatial boundaries for base stations and to build a subsequent regression based on mobile phone and building use data. The results show that the Grid Voronoi method gives high fitness in building use regression, and further comparison between the traditional ordinary least squares (OLS) regression model and geographically weighted regression (GWR) model indicates that the building use data can well reflect the heterogeneity of urban geographic space. This method provides a relatively convenient and reliable idea for capturing high-precision population distribution, based on mobile phone and building use data. Full article
(This article belongs to the Special Issue Geodata Science and Spatial Analysis in Urban Studies)
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40 pages, 21218 KiB  
Article
Automated Conflation of Digital Elevation Model with Reference Hydrographic Lines
by Timofey E. Samsonov
ISPRS Int. J. Geo-Inf. 2020, 9(5), 334; https://doi.org/10.3390/ijgi9050334 - 20 May 2020
Cited by 7 | Viewed by 6605
Abstract
Combining misaligned spatial data from different sources complicates spatial analysis and creation of maps. Conflation is a process that solves the misalignment problem through spatial adjustment or attribute transfer between similar features in two datasets. Even though a combination of digital elevation model [...] Read more.
Combining misaligned spatial data from different sources complicates spatial analysis and creation of maps. Conflation is a process that solves the misalignment problem through spatial adjustment or attribute transfer between similar features in two datasets. Even though a combination of digital elevation model (DEM) and vector hydrographic lines is a common practice in spatial analysis and map**, no method for automated conflation between these spatial data types has been developed so far. The problem of DEM and hydrography misalignment arises not only in map compilation, but also during the production of generalized datasets. There is a lack of automated solutions which can ensure that the drainage network represented in the surface of generalized DEM is spatially adjusted with independently generalized vector hydrography. We propose a new method that performs the conflation of DEM with linear hydrographic data and is embeddable into DEM generalization process. Given a set of reference hydrographic lines, our method automatically recognizes the most similar paths on DEM surface called counterpart streams. The elevation data extracted from DEM is then rubbersheeted locally using the links between counterpart streams and reference lines, and the conflated DEM is reconstructed from the rubbersheeted elevation data. The algorithm developed for extraction of counterpart streams ensures that the resulting set of lines comprises the network similar to the network of ordered reference lines. We also show how our approach can be seamlessly integrated into a TIN-based structural DEM generalization process with spatial adjustment to pre-generalized hydrographic lines as additional requirement. The combination of the GEBCO_2019 DEM and the Natural Earth 10M vector dataset is used to illustrate the effectiveness of DEM conflation both in map compilation and map generalization workflows. Resulting maps are geographically correct and are aesthetically more pleasing in comparison to a straightforward combination of misaligned DEM and hydrographic lines without conflation. Full article
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20 pages, 341 KiB  
Review
State-of-the-Art Geospatial Information Processing in NoSQL Databases
by Dongming Guo and Erling Onstein
ISPRS Int. J. Geo-Inf. 2020, 9(5), 331; https://doi.org/10.3390/ijgi9050331 - 19 May 2020
Cited by 32 | Viewed by 7207
Abstract
Geospatial information has been indispensable for many application fields, including traffic planning, urban planning, and energy management. Geospatial data are mainly stored in relational databases that have been developed over several decades, and most geographic information applications are desktop applications. With the arrival [...] Read more.
Geospatial information has been indispensable for many application fields, including traffic planning, urban planning, and energy management. Geospatial data are mainly stored in relational databases that have been developed over several decades, and most geographic information applications are desktop applications. With the arrival of big data, geospatial information applications are also being modified into, e.g., mobile platforms and Geospatial Web Services, which require changeable data schemas, faster query response times, and more flexible scalability than traditional spatial relational databases currently have. To respond to these new requirements, NoSQL (Not only SQL) databases are now being adopted for geospatial data storage, management, and queries. This paper reviews state-of-the-art geospatial data processing in the 10 most popular NoSQL databases. We summarize the supported geometry objects, main geometry functions, spatial indexes, query languages, and data formats of these 10 NoSQL databases. Moreover, the pros and cons of these NoSQL databases are analyzed in terms of geospatial data processing. A literature review and analysis showed that current document databases may be more suitable for massive geospatial data processing than are other NoSQL databases due to their comprehensive support for geometry objects and data formats and their performance, geospatial functions, index methods, and academic development. However, depending on the application scenarios, graph databases, key-value, and wide column databases have their own advantages. Full article
(This article belongs to the Special Issue State-of-the-Art in Spatial Information Science)
23 pages, 4073 KiB  
Article
Ranking of Assets with Respect to Their Exposure to the Landslide Hazard: A GIS Proposal
by Paolino Di Felice
ISPRS Int. J. Geo-Inf. 2020, 9(5), 326; https://doi.org/10.3390/ijgi9050326 - 17 May 2020
Cited by 1 | Viewed by 2139
Abstract
The need to protect critical infrastructures (for short called assets within this paper) arises because of the hazards they are exposed to. In this article, the hazard is represented by the landslides. The first part of the paper proposes a scientifically robust method [...] Read more.
The need to protect critical infrastructures (for short called assets within this paper) arises because of the hazards they are exposed to. In this article, the hazard is represented by the landslides. The first part of the paper proposes a scientifically robust method for the identification of the top-N assets that can be modeled as “points” (mainly buildings). The developed method takes into account the slope of the terrain, the runout distance of the landslide and its trajectory. The latter is roughly estimated through the notion of linear regression line. The method is applied to a real case to carry out a preliminary validation of it. In the second part of the paper, it is formalized the problem of computing the ranking of assets that can be modeled as “lines” (e.g., highways, power lines, pipelines, railway lines, and so on, that cross a given territory). The problem is solved in three steps: (a) Segmentation (it “cuts” each route in segments), (b) Sampling (it extracts points from each segment), and (c) Calculation (it associates an exposure value to each extracted point and, then, computes the exposure of the various segments composing the routes). The computation of the exposure for the points is carried out by applying the method of the first part of the paper. Both rankings can be used by the local administrators as a conceptual tool for narrowing down a global problem to smaller, higher exposure, geographic areas where the management of the hazard is crucial. Full article
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15 pages, 3866 KiB  
Article
An All-in-One Application for Temporal Coordinate Transformation in Geodesy and Geoinformatics
by Antonio Banko, Tedi Banković, Marko Pavasović and Almin Đapo
ISPRS Int. J. Geo-Inf. 2020, 9(5), 323; https://doi.org/10.3390/ijgi9050323 - 13 May 2020
Cited by 4 | Viewed by 3589
Abstract
Over the years, Global Navigation Satellite Systems (GNSS) have been established in the geosciences as a tool that determines the positions of discrete points (stations) on the Earth’s surface, on global to local spatial scales in a very simple and economical manner. Coordinates [...] Read more.
Over the years, Global Navigation Satellite Systems (GNSS) have been established in the geosciences as a tool that determines the positions of discrete points (stations) on the Earth’s surface, on global to local spatial scales in a very simple and economical manner. Coordinates obtained by space geodetic measurements ought to be processed, adjusted, and propagated in a given reference frame. As points on the Earth’s surface do not have a fixed position, but rather, are moving with associated velocities, it is inevitable to include those velocities in the coordinate transformation procedure. Station velocities can be obtained from kinematic models of tectonic plate motions. The development and realization of an all-in-one standalone desktop application is presented in this paper. The application unifies coordinate transformation between different realizations (reference frames) of the International Terrestrial Reference System (ITRS) and European Terrestrial Reference System 1989 (ETRS89) following European Reference Frame Technical Note (EUREF TN) recommendations with temporal shifts of discrete points on the Earth’s surface caused by plate tectonics by integrating no-net rotation (NNR) kinematic models of the Eurasian tectonic plate. Full article
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20 pages, 6776 KiB  
Article
Disdyakis Triacontahedron DGGS
by John Hall, Lakin Wecker, Benjamin Ulmer and Faramarz Samavati
ISPRS Int. J. Geo-Inf. 2020, 9(5), 315; https://doi.org/10.3390/ijgi9050315 - 8 May 2020
Cited by 16 | Viewed by 5229
Abstract
The amount of information collected about the Earth has become extremely large. With this information comes the demand for integration, processing, visualization and distribution of this data so that it can be leveraged to solve real-world problems. To address this issue, a carefully [...] Read more.
The amount of information collected about the Earth has become extremely large. With this information comes the demand for integration, processing, visualization and distribution of this data so that it can be leveraged to solve real-world problems. To address this issue, a carefully designed information structure is needed that stores all of the information about the Earth in a convenient format such that it can be easily used to solve a wide variety of problems. The idea which we explore is to create a Discrete Global Grid System (DGGS) using a Disdyakis Triacontahedron (DT) as the initial polyhedron. We have adapted a simple, closed-form, equal-area projection to reduce distortion and speed up queries. We have derived an efficient, closed-form inverse for this projection that can be used in important DGGS queries. The resulting construction is indexed using an atlas of connectivity maps. Using some simple modular arithmetic, we can then address point to cell, neighbourhood and hierarchical queries on the grid, allowing for these queries to be performed in constant time. We have evaluated the angular distortion created by our DGGS by comparing it to a traditional icosahedron DGGS using a similar projection. We demonstrate that our grid reduces angular distortion while allowing for real-time rendering of data across the globe. Full article
(This article belongs to the Special Issue Global Grid Systems)
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20 pages, 6891 KiB  
Article
Visualization of 3D Survey Data for Strata Titles
by Trias Aditya, Dany Laksono, Febrian F. Susanta, I. Istarno, D. Diyono and Didik Ariyanto
ISPRS Int. J. Geo-Inf. 2020, 9(5), 310; https://doi.org/10.3390/ijgi9050310 - 7 May 2020
Cited by 11 | Viewed by 4985
Abstract
Major cities and urban areas are beginning to develop and use 3D properties and public facilities. Consequently, 3D cadastral surveys are increasingly being employed for strata unit ownership registration as a part of land administration services. At present, most national land information systems [...] Read more.
Major cities and urban areas are beginning to develop and use 3D properties and public facilities. Consequently, 3D cadastral surveys are increasingly being employed for strata unit ownership registration as a part of land administration services. At present, most national land information systems do not support 2D and 3D cadastral visualizations. A field survey or validation survey is required to determine the geometry of 3D spatial units for property registration. However, the results of 3D surveys and map** are not stored in the land information system. This work aims to integrate 2D and 3D geospatial data of property units collected from cadastral surveys with their corresponding legal data. It reviews the workflow for the use of 3D survey data for first-titling of 3D properties in Indonesia. A scenario of use and a prototype were developed based on existing practices and the possibility of extending Indonesia’s Land Administration Domain Model (LADM) to represent 3D units. Data submitted to the prototype as 3D geometries was survey data from 3D cadastral surveys or validation surveys utilizing terrestrial survey methods. The prototype used PostGIS and Cesium Ion to store 3D geometries of data from six 3D surveys. Registrars in local land offices could use the prototype to undertake strata unit registration that establishes a relationship among geospatial features and their survey documents and legal documents. Cesium JS was used as a 3D browser, customized as a web application, to manage and visualize 3D survey data to support strata title registration. The results demonstrate that the first titling of 3D cadaster objects could be conducted and properly visualized in Indonesia by extending the existing LADM with more support for 3D spatial representations and survey documents. Full article
(This article belongs to the Special Issue Applications of GIScience for Land Administration)
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21 pages, 2963 KiB  
Article
Moving Towards a Single Smart Cadastral Platform in Victoria, Australia
by Hamed Olfat, Behnam Atazadeh, Abbas Rajabifard, Afshin Mesbah, Farshad Badiee, Yiqun Chen, Davood Shojaei and Mark Briffa
ISPRS Int. J. Geo-Inf. 2020, 9(5), 303; https://doi.org/10.3390/ijgi9050303 - 7 May 2020
Cited by 8 | Viewed by 3843
Abstract
Various jurisdictions are currently in the process of reforming their cadastral systems to achieve a smart and multidimensional system that provides a range of land administration services to the wider community. The state of Victoria in Australia has been actively modernizing its cadastral [...] Read more.
Various jurisdictions are currently in the process of reforming their cadastral systems to achieve a smart and multidimensional system that provides a range of land administration services to the wider community. The state of Victoria in Australia has been actively modernizing its cadastral system since the 1990s by develo** a digital cadastre database, an online digital cadastral plan lodgment portal named SPEAR, and smart cadastre services for validating and visualizing digital data in the ePlan (LandXML) format. However, due to challenges in the implementation of the smart cadastre lifecycle in Victoria, the uptake of ePlan is currently low across the surveying industry. This study aims to explore the feasibility of implementing a smart platform for managing ePlan lodgments in Victoria, which provides all required services within an integrated digital environment. To achieve this aim, the business and technical requirements for realizing a single smart cadastral platform are first explored. A proof of concept (PoC) is then developed to showcase a suitable approach for develo** this platform. The evaluation of the PoC confirmed that integration of smart cadastre services into a single environment could significantly streamline the digital cadastral data management processes in Victoria. Full article
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25 pages, 4262 KiB  
Article
Morphometric Prioritization, Fluvial Classification, and Hydrogeomorphological Quality in High Andean Livestock Micro-Watersheds in Northern Peru
by Nilton B. Rojas Briceño, Elgar Barboza Castillo, Oscar Andrés Gamarra Torres, Manuel Oliva, Damaris Leiva Tafur, Miguel Ángel Barrena Gurbillón, Fernando Corroto, Rolando Salas López and Jesús Rascón
ISPRS Int. J. Geo-Inf. 2020, 9(5), 305; https://doi.org/10.3390/ijgi9050305 - 7 May 2020
Cited by 12 | Viewed by 4302
Abstract
Anthropic activity affects the hydrogeomorphological quality of fluvial systems. River and valley classifications are fundamental preliminary steps in determining their ecological status, and their prioritization is essential for the proper planning and management of soil and water resources. Given the importance of the [...] Read more.
Anthropic activity affects the hydrogeomorphological quality of fluvial systems. River and valley classifications are fundamental preliminary steps in determining their ecological status, and their prioritization is essential for the proper planning and management of soil and water resources. Given the importance of the High Andean livestock micro-watershed (HAL-MWs) ecosystems in Peru, an integrated methodological framework is presented for morphometric prioritization that uses a Principal Component Analysis (PCA) and Weighted Sum Approach (WSA), geomorphological fluvial classifications (channel, slope, and valley), and hydrogeomorphological evaluations using the Hydrogeomorphological Index (IHG). Of six HAL-MWs studied in Leimebamba and Molinopampa (Amazonas region), the PCWSA hybrid model identified the San Antonio HAL-MW as a top priority, needing the rapid adoption of appropriate conservation practices. Thirty-nine types of river course were identified, by combining 13 types of valley and 11 types of riverbed. The total assessment of the IHG indicated that 7.6% (21.8 km), 14.5% (41.6 km), 27.9% (80.0 km), and 50.0% (143.2 km) of the basin lengths have “Poor”, “Moderate”, “Good”, and “Very good” quality rankings, respectively. The increase in the artificial use of river channels and flood plains is closely linked to the decrease in hydrogeomorphological quality. Full article
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23 pages, 9525 KiB  
Article
Methods for Inferring Route Choice of Commuting Trip From Mobile Phone Network Data
by Pitchaya Sakamanee, Santi Phithakkitnukoon, Zbigniew Smoreda and Carlo Ratti
ISPRS Int. J. Geo-Inf. 2020, 9(5), 306; https://doi.org/10.3390/ijgi9050306 - 7 May 2020
Cited by 12 | Viewed by 3498
Abstract
For billing purposes, telecom operators collect communication logs of our mobile phone usage activities. These communication logs or so called CDR has emerged as a valuable data source for human behavioral studies. This work builds on the transportation modeling literature by introducing a [...] Read more.
For billing purposes, telecom operators collect communication logs of our mobile phone usage activities. These communication logs or so called CDR has emerged as a valuable data source for human behavioral studies. This work builds on the transportation modeling literature by introducing a new approach of crowdsource-based route choice behavior data collection. We make use of CDR data to infer individual route choice for commuting trips. Based on one calendar year of CDR data collected from mobile users in Portugal, we proposed and examined methods for inferring the route choice. Our main methods are based on interpolation of route waypoints, shortest distance between a route choice and mobile usage locations, and Voronoi cells that assign a route choice into coverage zones. In addition, we further examined these methods coupled with a noise filtering using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and commuting radius. We believe that our proposed methods and their results are useful for transportation modeling as it provides a new, feasible, and inexpensive way for gathering route choice data, compared to costly and time-consuming traditional travel surveys. It also adds to the literature where a route choice inference based on CDR data at this detailed level—i.e., street level—has rarely been explored. Full article
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16 pages, 3746 KiB  
Article
Assessing Equity in the Accessibility to Urban Green Spaces According to Different Functional Levels
by Edorta Iraegui, Gabriela Augusto and Pedro Cabral
ISPRS Int. J. Geo-Inf. 2020, 9(5), 308; https://doi.org/10.3390/ijgi9050308 - 7 May 2020
Cited by 22 | Viewed by 5921
Abstract
Accessibility of urban residents to different services and amenities is a growing concern for policy makers. Urban green spaces (UGS) provide services and benefits that are particularly important for people having less mobility, such as children, the elderly or the poor. Practical experience [...] Read more.
Accessibility of urban residents to different services and amenities is a growing concern for policy makers. Urban green spaces (UGS) provide services and benefits that are particularly important for people having less mobility, such as children, the elderly or the poor. Practical experience has led to the classification of UGS in hierarchic systems reflecting the type and degree of benefits and services or functions they provide to users, which vary, primarily with their size. It is therefore necessary to ensure equity in the spatial distribution of different classes of UGS in the urban areas. In this work, we explore a methodology based in geographical information systems (GIS) to assess equity of access by different population groups to UGS according to its functional levels in the City of Barcelona, Spain, using a spatial clustering method. Results did not support the existence of overall inequalities in the access to UGS by the different groups of the population. However, indicators of spatial association revealed insufficiencies concerning accessibility to nearby UGS by seniors, children and the less wealthy in some parts of the city. This methodology may be used to inform urban planners dealing with the provision of UGS in an equitable manner to different socioeconomic groups of the resident population. Full article
(This article belongs to the Special Issue Geospatial Advances in Landscape Ecology)
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14 pages, 3166 KiB  
Article
Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands
by Tuomas Yrttimaa, Ninni Saarinen, Ville Kankare, Niko Viljanen, Jari Hynynen, Saija Huuskonen, Markus Holopainen, Juha Hyyppä, Eija Honkavaara and Mikko Vastaranta
ISPRS Int. J. Geo-Inf. 2020, 9(5), 309; https://doi.org/10.3390/ijgi9050309 - 7 May 2020
Cited by 16 | Viewed by 3678
Abstract
Terrestrial laser scanning (TLS) provides a detailed three-dimensional representation of surrounding forest structures. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees, and especially upper parts of forest canopy, is often limited. In this study, [...] Read more.
Terrestrial laser scanning (TLS) provides a detailed three-dimensional representation of surrounding forest structures. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees, and especially upper parts of forest canopy, is often limited. In this study, we investigated how much forest characterization capacity can be improved in managed Scots pine (Pinus sylvestris L.) stands if TLS point clouds are complemented with photogrammetric point clouds acquired from above the canopy using unmanned aerial vehicle (UAV). In this multisensorial (TLS+UAV) close-range sensing approach, the used UAV point cloud data were considered especially suitable for characterizing the vertical forest structure and improvements were obtained in estimation accuracy of tree height as well as plot-level basal-area weighted mean height (Hg) and mean stem volume (Vmean). Most notably, the root-mean-square-error (RMSE) in Hg improved from 0.8 to 0.58 m and the bias improved from −0.75 to −0.45 m with the multisensorial close-range sensing approach. However, in managed Scots pine stands, the mere TLS also captured the upper parts of the forest canopy rather well. Both approaches were capable of deriving stem number, basal area, Vmean, Hg, and basal area-weighted mean diameter with the relative RMSE less than 5.5% for all the sample plots. Although the multisensorial close-range sensing approach mainly enhanced the characterization of the forest vertical structure in single-species, single-layer forest conditions, representation of more complex forest structures may benefit more from point clouds collected with sensors of different measurement geometries. Full article
(This article belongs to the Special Issue UAV in Smart City and Smart Region)
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16 pages, 4845 KiB  
Article
Boosting Computational Effectiveness in Big Spatial Flow Data Analysis with Intelligent Data Reduction
by Ran Tao, Zhaoya Gong, Qiwei Ma and Jean-Claude Thill
ISPRS Int. J. Geo-Inf. 2020, 9(5), 299; https://doi.org/10.3390/ijgi9050299 - 6 May 2020
Cited by 9 | Viewed by 2599
Abstract
One of the enduring issues of spatial origin-destination (OD) flow data analysis is the computational inefficiency or even the impossibility to handle large datasets. Despite the recent advancements in high performance computing (HPC) and the ready availability of powerful computing infrastructure, we argue [...] Read more.
One of the enduring issues of spatial origin-destination (OD) flow data analysis is the computational inefficiency or even the impossibility to handle large datasets. Despite the recent advancements in high performance computing (HPC) and the ready availability of powerful computing infrastructure, we argue that the best solutions are based on a thorough understanding of the fundamental properties of the data. This paper focuses on overcoming the computational challenge through data reduction that intelligently takes advantage of the heavy-tailed distributional property of most flow datasets. We specifically propose the classification technique of head/tail breaks to this end. We test this approach with representative algorithms from three common method families, namely flowAMOEBA from flow clustering, Louvain from network community detection, and PageRank from network centrality algorithms. A variety of flow datasets are adopted for the experiments, including inter-city travel flows, cellphone call flows, and synthetic flows. We propose a standard evaluation framework to evaluate the applicability of not only the selected three algorithms, but any given method in a systematic way. The results prove that head/tail breaks can significantly improve the computational capability and efficiency of flow data analyses while preserving result quality, on condition that the analysis emphasizes the “head” part of the dataset or the flows with high absolute values. We recommend considering this easy-to-implement data reduction technique before analyzing a large flow dataset. Full article
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27 pages, 9231 KiB  
Article
Protected Areas from Space Map Browser with Fast Visualization and Analytical Operations on the Fly. Characterizing Statistical Uncertainties and Balancing Them with Visual Perception
by Joan Masό, Alaitz Zabala and Xavier Pons
ISPRS Int. J. Geo-Inf. 2020, 9(5), 300; https://doi.org/10.3390/ijgi9050300 - 6 May 2020
Cited by 2 | Viewed by 2561
Abstract
Despite huge progress in applying Earth Observation (EO) satellite data to protected areas, managers still lack the right tools or skills to analyze the data and extract the necessary knowledge. In this paper a set of EO products are organized in a visualization [...] Read more.
Despite huge progress in applying Earth Observation (EO) satellite data to protected areas, managers still lack the right tools or skills to analyze the data and extract the necessary knowledge. In this paper a set of EO products are organized in a visualization and analysis map browser that lowers usage barriers and provides functionalities comparable to raster-based GIS. Normally, web map servers provide maps as pictorial representations at screen resolution. The proposal is to use binary arrays with actual values, empowering the JavaScript web client to operate with the data in many ways. Thanks to this approach, the user can analyze big data by performing queries and spatial filters, changing image contrast or color palettes or creating histograms, time series profiles and complex calculations. Since the analysis is made at screen resolution, it minimizes bandwidth while maintaining visual quality. The paper explores the limitations of the approach and quantifies the statistical validity of some resampling methods that provide different visual perceptions. The results demonstrate that the methods known for having good visual perception, the mode for categorical values and the median for continuous values, have admissible statistical uncertainties. Full article
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