ISPRS International Journal of Geo-Information

Open AccessEditor’s ChoiceArticle

A Fine-Grain Batching-Based Task Allocation Algorithm for Spatial Crowdsourcing

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ISPRS Int. J. Geo-Inf. 2022, 11(3), 203; https://doi.org/10.3390/ijgi11030203 - 17 Mar 2022

Cited by 3 | Viewed by 2033

Abstract

Task allocation is a critical issue of spatial crowdsourcing. Although the batching strategy performs better than the real-time matching mode, it still has the following two drawbacks: (1) Because the granularity of the batch size set obtained by batching is too coarse, it [...] Read more.

Task allocation is a critical issue of spatial crowdsourcing. Although the batching strategy performs better than the real-time matching mode, it still has the following two drawbacks: (1) Because the granularity of the batch size set obtained by batching is too coarse, it will result in poor matching accuracy. However, roughly designing the batch size for all possible delays will result in a large computational overhead. (2) Ignoring non-stationary factors will lead to a change in optimal batch size that cannot be found as soon as possible. Therefore, this paper proposes a fine-grained, batching-based task allocation algorithm (FGBTA), considering non-stationary setting. In the batch method, the algorithm first uses variable step size to allow for fine-grained exploration within the predicted value given by the multi-armed bandit (MAB) algorithm and uses the results of pseudo-matching to calculate the batch utility. Then, the batch size with higher utility is selected, and the exact maximum weight matching algorithm is used to obtain the allocation result within the batch. In order to cope with the non-stationary changes, we use the sliding window (SW) method to retain the latest batch utility and discard the historical information that is too far away, so as to finally achieve refined batching and adapt to temporal changes. In addition, we also take into account the benefits of requesters, workers, and the platform. Experiments on real data and synthetic data show that this method can accomplish the task assignment of spatial crowdsourcing effectively and can adapt to the non-stationary setting as soon as possible. This paper mainly focuses on the spatial crowdsourcing task of ride-hailing. Full article

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Open AccessFeature PaperEditor’s ChoiceArticle

The Governance of INSPIRE: Evaluating and Exploring Governance Scenarios for the European Spatial Data Infrastructure

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ISPRS Int. J. Geo-Inf. 2022, 11(2), 141; https://doi.org/10.3390/ijgi11020141 - 15 Feb 2022

Cited by 1 | Viewed by 2766

Abstract

The development of a European Spatial Data Infrastructure (SDI) officially started with the entry into force of the INSPIRE Directive in 2007. INSPIRE’s implementation phase should be completed by the European Union (EU) and its member states at the end of 2021: a [...] Read more.

The development of a European Spatial Data Infrastructure (SDI) officially started with the entry into force of the INSPIRE Directive in 2007. INSPIRE’s implementation phase should be completed by the European Union (EU) and its member states at the end of 2021: a pivotal point to evaluate INSPIRE’s current governance and explore future scenarios. First, INSPIRE’s governing system is evaluated through an online survey by its involved stakeholders. Second, these results are applied in an agent-based model to explore potential governance scenarios and strategies. The results show that strong aspects of INSPIRE’s governing system are the supported vision and its formal structures, such as standards, technology and roles and responsibilities. Weak aspects are the access to resources, especially budget and time resources, and data use. The agent-based simulations show that INSPIRE is probably more constrained by its budget resources than its current dominant hierarchical interaction mix, although a combination of adaptive governance and continuous budget proved the most sustainable governance scenario. Full article

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Open AccessEditor’s ChoiceArticle

Where Maps Lie: Visualization of Perceptual Fallacy in Choropleth Maps at Different Levels of Aggregation

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ISPRS Int. J. Geo-Inf. 2022, 11(1), 64; https://doi.org/10.3390/ijgi11010064 - 14 Jan 2022

Cited by 1 | Viewed by 2743

Abstract

This paper proposes a method for quantitative evaluation of perception deviations due to generalization in choropleth maps. The method proposed is based on comparison of class values assigned to different aggregation units chosen for representing the same dataset. It is illustrated by the [...] Read more.

This paper proposes a method for quantitative evaluation of perception deviations due to generalization in choropleth maps. The method proposed is based on comparison of class values assigned to different aggregation units chosen for representing the same dataset. It is illustrated by the results of application of the method to population density maps of Lithuania. Three spatial aggregation levels were chosen for comparison: the 1 × 1 km statistical grid, elderships (NUTS3), and municipalities (NUTS2). Differences in density class values between the reference grid map and the other two maps were calculated. It is demonstrated that a perceptual fallacy on the municipality level population map of Lithuania leads to a misinterpretation of data that makes such maps frankly useless. The eldership level map is, moreover, also largely misleading, especially in sparsely populated areas. The method proposed is easy to use and transferable to any other field where spatially aggregated data are mapped. It can be used for visual analysis of the degree to which a generalized choropleth map is liable to mislead the user in particular areas. Full article

(This article belongs to the Special Issue Cartographic Communication of Big Data)

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Open AccessEditor’s ChoiceArticle

A Hierarchical Spatial Network Index for Arbitrarily Distributed Spatial Objects

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ISPRS Int. J. Geo-Inf. 2021, 10(12), 814; https://doi.org/10.3390/ijgi10120814 - 01 Dec 2021

Cited by 4 | Viewed by 1949

Abstract

The range query is one of the most important query types in spatial data processing. Geographic information systems use it to find spatial objects within a user-specified range, and it supports data mining tasks, such as density-based clustering. In many applications, ranges are [...] Read more.

The range query is one of the most important query types in spatial data processing. Geographic information systems use it to find spatial objects within a user-specified range, and it supports data mining tasks, such as density-based clustering. In many applications, ranges are not computed in unrestricted Euclidean space, but on a network. While the majority of access methods cannot trivially be extended to network space, existing network index structures partition the network space without considering the data distribution. This potentially results in inefficiency due to a very skewed node distribution. To improve range query processing on networks, this paper proposes a balanced Hierarchical Network index (HN-tree) to query spatial objects on networks. The main idea is to recursively partition the data on the network such that each partition has a similar number of spatial objects. Leveraging the HN-tree, we present an efficient range query algorithm, which is empirically evaluated using three different road networks and several baselines and state-of-the-art network indices. The experimental evaluation shows that the HN-tree substantially outperforms existing methods. Full article

(This article belongs to the Special Issue Geo-Enriched Data Modeling & Mining)

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Open AccessFeature PaperEditor’s ChoiceArticle

Interactive Maps for the Production of Knowledge and the Promotion of Participation from the Perspective of Communication, Journalism, and Digital Humanities

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Pedro Molina Rodríguez-Navas

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Johamna Muñoz Lalinde

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Narcisa Medranda Morales

ISPRS Int. J. Geo-Inf. 2021, 10(11), 722; https://doi.org/10.3390/ijgi10110722 - 26 Oct 2021

Viewed by 2332

Abstract

New technologies have allowed traditional map production criteria to be modified or even subverted. Starting from the communication sciences—journalism in particular—and digital humanities via the history of communication, we show how to use interactive digital maps for the production and publication of knowledge [...] Read more.

New technologies have allowed traditional map production criteria to be modified or even subverted. Starting from the communication sciences—journalism in particular—and digital humanities via the history of communication, we show how to use interactive digital maps for the production and publication of knowledge through and/or for participation. Firstly, we establish the theoretical-conceptual framework necessary to base the practices, dividing the elements into three areas: interactive maps and knowledge production (decentralization, pluralization, reticularization, and humanization), maps as instruments to promote political and social participation (egalitarianism, horizontality, and criticism), and maps as instruments for the visualization of data that favors the user experience (interactivity, multimediality, reticularity of reading, and participation). Next, we present two cases that we developed to put into practice the theoretical concepts that we established: the Mapa Infoparticipa (Infoparticipa Map), which shows the results of the evaluation of the transparency of public administrations, and the Ciutadania Plural (Plural Citizenship) web platform for the production of social knowledge about the past and the present. This theoretical and practical model shows the possibilities of interactive maps as tools to promote political participation and as instruments for the construction of social knowledge in a collaborative, participatory, networked way. Full article

(This article belongs to the Special Issue Public Participation in 2021: New Forms, New Modes, New Questions?)

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Open AccessEditor’s ChoiceArticle

Towards Managing Visual Pollution: A 3D Isovist and Voxel Approach to Advertisement Billboard Visual Impact Assessment

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Szymon Chmielewski

ISPRS Int. J. Geo-Inf. 2021, 10(10), 656; https://doi.org/10.3390/ijgi10100656 - 30 Sep 2021

Cited by 7 | Viewed by 2910

Abstract

Visual pollution (VP) is a visual landscape quality issue, and its most consistently recognized symptom is an excess of out of home advertising billboards (OOHb). However, the VP related research concerns landscape aesthetic and advertisement cultural context, leaving the impact of outdoor billboard [...] Read more.

Visual pollution (VP) is a visual landscape quality issue, and its most consistently recognized symptom is an excess of out of home advertising billboards (OOHb). However, the VP related research concerns landscape aesthetic and advertisement cultural context, leaving the impact of outdoor billboard infrastructure on landscape openness unanswered to date. This research aims to assess the visual impact of outdoor billboard infrastructure on landscape openness, precisely the visual volume—a key geometrical quality of a landscape. The method uses 3D isovists and voxels to calculate the visible and obstructed subsets of visible volume. Using two case studies (Lublin City, Poland) and 26 measurement points, it was found that OOHb decreased landscape openness by at least 4% of visible volume; however, the severe impact may concern up to 35% of visual volume. GIS scientists develop the proposed method for policy-makers, and urban planners end users. It is also the very first example of compiling 3D isovists and voxels in ArcGIS Pro software in an easy-to-replicate framework. The research results, accompanied by statistically significant proofs, explain the visual landscape’s fragility and contribute to understanding the VP phenomenon. Full article

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Open AccessEditor’s ChoiceArticle

Geospatial Data Utilisation in National Disaster Management Frameworks and the Priorities of Multilateral Disaster Management Frameworks: Case Studies of India and Bulgaria

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Tarun Ghawana

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Lyubka Pashova

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Sisi Zlatanova

ISPRS Int. J. Geo-Inf. 2021, 10(9), 610; https://doi.org/10.3390/ijgi10090610 - 15 Sep 2021

Cited by 5 | Viewed by 3723

Abstract

Facing the increased frequency of disasters and resulting in massive damages, many countries have developed their frameworks for Disaster Risk Management (DRM). However, these frameworks may differ concerning legal, policy, planning and organisational arrangements. We argue that geospatial data is a crucial binding [...] Read more.

Facing the increased frequency of disasters and resulting in massive damages, many countries have developed their frameworks for Disaster Risk Management (DRM). However, these frameworks may differ concerning legal, policy, planning and organisational arrangements. We argue that geospatial data is a crucial binding element in each national framework for different stages of the disaster management cycle. The multilateral DRM frameworks, like the Sendai Framework 2015–2030 and the United Nations Committee of Experts on Global Geospatial Information Management (UNGGIM) Strategic Framework on Geospatial Information and Services for Disasters, provide the strategic direction, but they are too generic to compare geospatial data in national DRM frameworks. This study investigates the two frameworks and suggests criteria for evaluating the utilisation of geospatial data for DRM. The derived criteria are validated for the comparative analysis of India and Bulgaria’s National Disaster Management Frameworks. The validation proves that the criteria can be used for a general comparison across national DRM. Full article

(This article belongs to the Special Issue Disaster Management and Geospatial Information)

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Open AccessEditor’s ChoiceArticle

Integration and Analysis of Multi-Modal Geospatial Secondary Data to Inform Management of at-Risk Archaeological Sites

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ISPRS Int. J. Geo-Inf. 2021, 10(9), 575; https://doi.org/10.3390/ijgi10090575 - 24 Aug 2021

Cited by 2 | Viewed by 3215

Abstract

Climate change poses an imminent physical risk to cultural heritage sites and their surrounding landscape through intensifying environmental processes such as damaging wetting and drying cycles that disrupt archaeological preservation conditions, and soil erosion which threatens to expose deposits and alter the archaeological [...] Read more.

Climate change poses an imminent physical risk to cultural heritage sites and their surrounding landscape through intensifying environmental processes such as damaging wetting and drying cycles that disrupt archaeological preservation conditions, and soil erosion which threatens to expose deposits and alter the archaeological context of sites. In the face of such threats, geospatial techniques such as GIS, remote sensing, and spatial modelling have proved invaluable tools for archaeological research and cultural heritage monitoring. This paper presents the application of secondary multi-source and multi-temporal geospatial data within a processing framework to provide a comprehensive assessment of geophysical risk to the Roman fort of Magna, Carvoran, UK. An investigation into the ancient hydraulic system at Magna was carried out with analysis of vegetation change over time, and spatio-temporal analysis of soil erosion risk at the site. Due to COVID-19 restrictions in place at the time of this study, these analyses were conducted using only secondary data with the aim to guide further archaeological research, and management and monitoring strategies for the stakeholders involved. Results guided inferences about the ancient hydraulic system, providing insights regarding how to better manage the site at Magna in the future. Analysis of soil erosion allowed the identification of hot spot areas, indicating a future increase in rates of erosion at Magna and suggesting a seasonal period of higher risk of degradation to the site. Results have proven that freely available multi-purpose national-scale datasets are sufficient to create meaningful insights into archaeological sites where physical access to the site is inhibited. This infers the potential to carry out preliminary risk assessment to inform future site management practices. Full article

(This article belongs to the Special Issue 3D Modeling and GIS for Historical Sites Reconstruction)

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Open AccessEditor’s ChoiceArticle

Heat Maps: Perfect Maps for Quick Reading? Comparing Usability of Heat Maps with Different Levels of Generalization

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Katarzyna Słomska-Przech

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Tomasz Panecki

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Wojciech Pokojski

ISPRS Int. J. Geo-Inf. 2021, 10(8), 562; https://doi.org/10.3390/ijgi10080562 - 18 Aug 2021

Cited by 3 | Viewed by 5091

Abstract

Recently, due to Web 2.0 and neocartography, heat maps have become a popular map type for quick reading. Heat maps are graphical representations of geographic data density in the form of raster maps, elaborated by applying kernel density estimation with a given radius [...] Read more.

Recently, due to Web 2.0 and neocartography, heat maps have become a popular map type for quick reading. Heat maps are graphical representations of geographic data density in the form of raster maps, elaborated by applying kernel density estimation with a given radius on point- or linear-input data. The aim of this study was to compare the usability of heat maps with different levels of generalization (defined by radii of 10, 20, 30, and 40 pixels) for basic map user tasks. A user study with 412 participants (16–20 years old, high school students) was carried out in order to compare heat maps that showed the same input data. The study was conducted in schools during geography or IT lessons. Objective (the correctness of the answer, response times) and subjective (response time self-assessment, task difficulty, preferences) metrics were measured. The results show that the smaller radius resulted in the higher correctness of the answers. A larger radius did not result in faster response times. The participants perceived the more generalized maps as easier to use, although this result did not match the performance metrics. Overall, we believe that heat maps, in given circumstances and appropriate design settings, can be considered an efficient method for spatial data presentation. Full article

(This article belongs to the Special Issue Geovisualization and Map Design)

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Open AccessEditor’s ChoiceArticle

The Role of Participatory Village Maps in Strengthening Public Participation Practice

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Aulia Akbar

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Johannes Flacke

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Javier Martinez

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Martin F. A. M. van Maarseveen

ISPRS Int. J. Geo-Inf. 2021, 10(8), 512; https://doi.org/10.3390/ijgi10080512 - 29 Jul 2021

Cited by 4 | Viewed by 2902

Abstract

This study investigated the role of participatory village maps in strengthening the Musrenbang, an annual multi-stakeholder public consultation forum to discuss development issues and plans in Indonesia. We evaluated the Musrenbang in five villages in Deli Serdang District after conducting participatory mapping workshops [...] Read more.

This study investigated the role of participatory village maps in strengthening the Musrenbang, an annual multi-stakeholder public consultation forum to discuss development issues and plans in Indonesia. We evaluated the Musrenbang in five villages in Deli Serdang District after conducting participatory mapping workshops to produce village maps to inform the Musrenbang process. Our results show that communication between Musrenbang participants improved because the maps provided a clear definition of the village administrative area, geospatial data as resources for participation, transparency, and a dynamic deliberative process. Collaboration was also evident as the maps enabled participants to exchange knowledge, experience social learning, and have greater influence on the decision-making process. Despite the benefits, some issues impeded the optimal use of the village maps to support the participatory process in the Musrenbang. The maps could not completely overcome the power disparities between Musrenbang participants. Certain actors still dominated the implementation of the Musrenbang, making the deliberative process inaccessible to and less inclusive of some local stakeholders. Several improvements are urgently needed to optimise the use of participatory village maps and enhance Musrenbang implementation. Full article

(This article belongs to the Special Issue Public Participation in 2021: New Forms, New Modes, New Questions?)

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Open AccessEditor’s ChoiceArticle

Efficient Interactive Tactile Maps: A Semi-Automated Workflow Using the TouchIt3D Technology and OpenStreetMap Data

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Radek Barvir

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Alena Vondrakova

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Jan Brus

ISPRS Int. J. Geo-Inf. 2021, 10(8), 505; https://doi.org/10.3390/ijgi10080505 - 27 Jul 2021

Cited by 6 | Viewed by 3083

Abstract

Despite the growing efficiency of the map-design process in general, tactile mapping has remained peripheral to mainstream cartography. For a specific group of people with visual impairment, however, tactile maps are the only effective way to obtain a complex idea about the geospatial [...] Read more.

Despite the growing efficiency of the map-design process in general, tactile mapping has remained peripheral to mainstream cartography. For a specific group of people with visual impairment, however, tactile maps are the only effective way to obtain a complex idea about the geospatial distribution of the surrounding world. As there are numerous specifics in creating these 3D maps and only a limited group of users, tactile products have usually been either very simple creations or, on the other hand, difficult and expensive to produce. Modern trends and progress in the availability of new technologies (e.g., 3D printing) bring new possibilities for keeping tactile map production both effective and up to date. Therefore, this paper aims to present a methodology to apply the TouchIt3D technology to link 3D-printed multi-material tactile maps with a mobile device. Utilizing this solution resulted in a set of interactive tactile maps following current trends of inclusive education. Using OpenStreetMap data together with a semi-automated workflow significantly lowered expenses compared to antecedent maps with similar functionality. A semi-automated workflow was designed, focusing on three use cases of independent movement: walking, using public transport, and tourism. Full article

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Open AccessEditor’s ChoiceArticle

Subjectively Measured Streetscape Perceptions to Inform Urban Design Strategies for Shanghai

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ISPRS Int. J. Geo-Inf. 2021, 10(8), 493; https://doi.org/10.3390/ijgi10080493 - 21 Jul 2021

Cited by 26 | Viewed by 4709

Abstract

Recently, many new studies applying computer vision (CV) to street view imagery (SVI) datasets to objectively extract the view indices of various streetscape features such as trees to proxy urban scene qualities have emerged. However, human perception (e.g., imageability) have a subtle relationship [...] Read more.

Recently, many new studies applying computer vision (CV) to street view imagery (SVI) datasets to objectively extract the view indices of various streetscape features such as trees to proxy urban scene qualities have emerged. However, human perception (e.g., imageability) have a subtle relationship to visual elements that cannot be fully captured using view indices. Conversely, subjective measures using survey and interview data explain human behaviors more. However, the effectiveness of integrating subjective measures with SVI datasets has been less discussed. To address this, we integrated crowdsourcing, CV, and machine learning (ML) to subjectively measure four important perceptions suggested by classical urban design theory. We first collected ratings from experts on sample SVIs regarding these four qualities, which became the training labels. CV segmentation was applied to SVI samples extracting streetscape view indices as the explanatory variables. We then trained ML models and achieved high accuracy in predicting scores. We found a strong correlation between the predicted complexity score and the density of urban amenities and services points of interest (POI), which validates the effectiveness of subjective measures. In addition, to test the generalizability of the proposed framework as well as to inform urban renewal strategies, we compared the measured qualities in Pudong to other five urban cores that are renowned worldwide. Rather than predicting perceptual scores directly from generic image features using a convolution neural network, our approach follows what urban design theory has suggested and confirmed as various streetscape features affecting multi-dimensional human perceptions. Therefore, the results provide more interpretable and actionable implications for policymakers and city planners. Full article

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Open AccessEditor’s ChoiceArticle

Automatic Road Extraction from Historical Maps Using Deep Learning Techniques: A Regional Case Study of Turkey in a German World War II Map

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Burak Ekim

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Elif Sertel

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M. Erdem Kabadayı

ISPRS Int. J. Geo-Inf. 2021, 10(8), 492; https://doi.org/10.3390/ijgi10080492 - 21 Jul 2021

Cited by 12 | Viewed by 3763

Abstract

Scanned historical maps are available from different sources in various scales and contents. Automatic geographical feature extraction from these historical maps is an essential task to derive valuable spatial information on the characteristics and distribution of transportation infrastructures and settlements and to conduct [...] Read more.

Scanned historical maps are available from different sources in various scales and contents. Automatic geographical feature extraction from these historical maps is an essential task to derive valuable spatial information on the characteristics and distribution of transportation infrastructures and settlements and to conduct quantitative and geometrical analysis. In this research, we used the Deutsche Heereskarte 1:200,000 Türkei (DHK 200 Turkey) maps as the base geoinformation source to construct the past transportation networks using the deep learning approach. Five different road types were digitized and labeled to be used as inputs for the proposed deep learning-based segmentation approach. We adapted U-Net++ and ResneXt50_32×4d architectures to produce multi-class segmentation masks and perform feature extraction to determine various road types accurately. We achieved remarkable results, with 98.73% overall accuracy, 41.99% intersection of union, and 46.61% F1 score values. The proposed method can be implemented in DHK maps of different countries to automatically extract different road types and used for transfer learning of different historical maps. Full article

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Open AccessEditor’s ChoiceArticle

User-Centred Design of Multidisciplinary Spatial Data Platforms for Human-History Research

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ISPRS Int. J. Geo-Inf. 2021, 10(7), 467; https://doi.org/10.3390/ijgi10070467 - 08 Jul 2021

Cited by 3 | Viewed by 3011

Abstract

The role of open spatial data is growing in human-history research. Spatiality can be utilized to bring together and seamlessly examine data describing multiple aspects of human beings and their environment. Web-based spatial data platforms can create equal opportunities to view and access [...] Read more.

The role of open spatial data is growing in human-history research. Spatiality can be utilized to bring together and seamlessly examine data describing multiple aspects of human beings and their environment. Web-based spatial data platforms can create equal opportunities to view and access these data. In this paper, we aim at advancing the development of user-friendly spatial data platforms for multidisciplinary research. We conceptualize the building process of such a platform by systematically reviewing a diverse sample of historical spatial data platforms and by piloting a user-centered design process of a multidisciplinary spatial data platform. We outline (1) the expertise needed in organizing multidisciplinary spatial data sharing, (2) data types that platforms should be able to handle, (3) the most useful platform functionalities, and (4) the design process itself. We recommend that the initiative and subject expertise should come from the end-users, i.e., scholars of human history, and all key end-user types should be involved in the design process. We also highlight the importance of geographic expertise in the process, an important link between subject, spatial and technical viewpoints, for reaching a common understanding and common terminology. Based on the analyses, we identify key development goals for spatial data platforms, including full layer management functionalities. Moreover, we identify the main roles in the user-centered design process, main user types and suggest good practices including a multimodal design workshop. Full article

(This article belongs to the Special Issue Geospatial Open Systems)

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Open AccessEditor’s ChoiceArticle

An “Animated Spatial Time Machine” in Co-Creation: Reconstructing History Using Gamification Integrated into 3D City Modelling, 4D Web and Transmedia Storytelling

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ISPRS Int. J. Geo-Inf. 2021, 10(7), 460; https://doi.org/10.3390/ijgi10070460 - 06 Jul 2021

Cited by 10 | Viewed by 6409

Abstract

More and more digital 3D city models might evolve into spatiotemporal instruments with time as the 4th dimension. For digitizing the current situation, 3D scanning and photography are suitable tools. The spatial future could be integrated using 3D drawings by public space designers [...] Read more.

More and more digital 3D city models might evolve into spatiotemporal instruments with time as the 4th dimension. For digitizing the current situation, 3D scanning and photography are suitable tools. The spatial future could be integrated using 3D drawings by public space designers and architects. The digital spatial reconstruction of lost historical environments is more complex, expensive and rarely done. Three-dimensional co-creative digital drawing with citizens’ collaboration could be a solution. In 2016, the City of Ghent (Belgium) launched the “3D city game Ghent” project with time as one of the topics, focusing on the reconstruction of disappeared environments. Ghent inhabitants modelled in open-source 3D software and added animated 3D gamification and Transmedia Storytelling, resulting in a 4D web environment and VR/AR/XR applications. This study analyses this low-cost interdisciplinary 3D co-creative process and offers a framework to enable other cities and municipalities to realise a parallel virtual universe (an animated digital twin bringing the past to life). The result of this co-creation is the start of an “Animated Spatial Time Machine” (AniSTMa), a term that was, to the best of our knowledge, never used before. This research ultimately introduces a conceptual 4D space–time diagram with a relation between the current physical situation and a growing number of 3D animated models over time. Full article

(This article belongs to the Special Issue Crowdsourced Geographic Information in Citizen Science)

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Open AccessEditor’s ChoiceArticle

Hydrological Modeling of Green Infrastructure to Quantify Its Effect on Flood Mitigation and Water Availability in the High School Watershed in Tucson, AZ

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Yoganand Korgaonkar

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David Phillip Guertin

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Thomas Meixner

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David C Goodrich

ISPRS Int. J. Geo-Inf. 2021, 10(7), 443; https://doi.org/10.3390/ijgi10070443 - 29 Jun 2021

Cited by 4 | Viewed by 2348

Abstract

Green Infrastructure (GI) practices are being implemented in numerous cities to tackle stormwater management issues and achieve co-benefits such as mitigating heat island effects and air pollution, as well as water augmentation, health, and economic benefits. Tucson, Arizona is a fast-growing city in [...] Read more.

Green Infrastructure (GI) practices are being implemented in numerous cities to tackle stormwater management issues and achieve co-benefits such as mitigating heat island effects and air pollution, as well as water augmentation, health, and economic benefits. Tucson, Arizona is a fast-growing city in the semiarid region of the southwest United States and provides a unique landscape in terms of urban hydrology and stormwater management, where stormwater is routed along the streets to the nearest ephemeral washes. Local organizations have implemented various GI practices, such as curb cuts, traffic chicanes, roof runoff harvesting, and retention basins, to capture the excess runoff and utilize it on-site. This study models the 3.31 km² High School watershed in central Tucson using the Automated Geospatial Watershed Assessment (AGWA) tool and the Kinematic Runoff and Erosion (KINEROS2) model. Each parcel in the watershed was individually represented using the KINEROS2 Urban element to simulate small-scale flow-on/flow-off processes. Seven different configurations of GI implementation were simulated using design storms, and we stochastically generated 20 years of precipitation data to understand the effects of GI implementation on flood mitigation and long-term water availability, respectively. The design storm analysis indicates that the configuration designed to mimic the current level of GI implementation, which includes 175 on-street basins and 37 roof runoff harvesting cisterns, has minimum (<2%) influence on runoff volume. Furthermore, the analysis showed that the current level of GI implementation caused an increase (<1%) in peak flows at the watershed outlet but predicted reduced on-street accumulated volumes (>25%) and increased water availability via GI capture and infiltration. When the GI implementation was increased by a factor of two and five, a larger reduction of peak flow (<8% and <22%, respectively) and volume (<3% and <8%, respectively) was simulated at the watershed outlet. The 20-year analysis showed that parcels with roof runoff harvesting cisterns were able to meet their landscape irrigation demands throughout the year, except for the dry months of May and June. Additionally, stormwater captured and infiltrated by the on-street basins could support xeric vegetation for most of the year, except June, where the water demand exceeded volume of water infiltrated in the basins. The current level of GI implementation in the High School watershed may not have significant large-scale impacts, but it provides numerous benefits at the parcel, street, and small neighborhood scales. Full article

(This article belongs to the Special Issue Advancements in Geospatial Planning and Assessment of Green Infrastructure in Cities of the Future)

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Open AccessEditor’s ChoiceArticle

Exploring Allometric Scaling Relations between Fractal Dimensions of Metro Networks and Economic, Environmental and Social Indicators: A Case Study of 26 Cities in China

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ISPRS Int. J. Geo-Inf. 2021, 10(7), 429; https://doi.org/10.3390/ijgi10070429 - 23 Jun 2021

Cited by 2 | Viewed by 1669

Abstract

Allometric scaling originates in biology, where it refers to scaling relations between the size of a body part and the size of the whole body when an organism grows. In cities, various allometric relations have also been discovered, such as those between the [...] Read more.

Allometric scaling originates in biology, where it refers to scaling relations between the size of a body part and the size of the whole body when an organism grows. In cities, various allometric relations have also been discovered, such as those between the complexity of traffic networks and urban quantities. Metro networks are typical traffic networks in cities. However, whether allometric relations with metro networks exist is still uncertain. In this study, “fractal dimension” was employed as the complexity measure of metro networks, and potential allometric relations between fractal dimensions and urban indicators in 26 main cities in China were explored. It was found that fractal dimensions of metro networks had positive allometric relations with gross domestic product (GDP), population, particulate matter with a diameter less than 2.5 microns (PM_2.5), the road congestion index and the average price of second-hand housing (with Spearman’s R of 0.789, 0.806, 0.273, 0.625 and 0.335, respectively) but inverse allometric relations with sulfur dioxide (SO₂) and residential satisfaction (with Spearman’s R of −0.270 and −0.419, respectively). Such discoveries imply that allometric relations do exist with metro networks, which is helpful in deepening our understanding of how metro systems interact with urban quantities in the self-organized evolution of cities. Full article

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Open AccessEditor’s ChoiceArticle

A Spatially Highly Resolved Ground Mounted and Rooftop Potential Analysis for Photovoltaics in Austria

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Christian Mikovits

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Thomas Schauppenlehner

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Robert Gennaro Sposato

ISPRS Int. J. Geo-Inf. 2021, 10(6), 418; https://doi.org/10.3390/ijgi10060418 - 16 Jun 2021

Cited by 7 | Viewed by 4693

Abstract

Austria aims to meet 100% of its electricity demand from domestic renewable sources by 2030 which means, that an additional 27

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of renewable electricity generation are required, thereof 11

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from photovoltaic. While some [...] Read more.

Austria aims to meet 100% of its electricity demand from domestic renewable sources by 2030 which means, that an additional 27

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from photovoltaic. While some federal states and municipalities released a solar rooftop cadastre, there is lacking knowledge on the estimation of the potential of both, ground mounted installations and rooftop modules, on a national level with a high spatial resolution. As a first, in this work data on agricultural land-use is combined with highly resolved data on buildings on a national level. Our results show significant differences between urban and rural areas, as well as between the Alpine regions and the Prealpine- and Easter Plain areas. Rooftop potential concentrates in the big urban areas, but also in densely populated areas in Lower- and Upper Austria, Styria and the Rhine valley of Vorarlberg. The ground mounted photovoltaic potential is highest in Eastern Austria. This potential is geographically consistent with the demand and allows for a production close to the consumer. In theory, the goal of meeting 11

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in 2030 can be achieved solely with the rooftop PV potential. However, considering the necessary installation efforts, the associated costs of small and dispersed production units and finally the inherent uncertainty with respect to the willingness of tens of thousands of individual households to install PV systems, installing the necessary solar PV on buildings alone is constrained. Full article

(This article belongs to the Collection Spatial and Temporal Modelling of Renewable Energy Systems)

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Open AccessEditor’s ChoiceArticle

Emojis as Contextual Indicants in Location-Based Social Media Posts

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Eva Hauthal

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Alexander Dunkel

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Dirk Burghardt

ISPRS Int. J. Geo-Inf. 2021, 10(6), 407; https://doi.org/10.3390/ijgi10060407 - 12 Jun 2021

Cited by 2 | Viewed by 2705

Abstract

The presented study aims to investigate the relationship between the use of emojis in location-based social media and the location of the corresponding post in terms of perceived objects and conducted activities connected to this place. The basis for this is not a [...] Read more.

The presented study aims to investigate the relationship between the use of emojis in location-based social media and the location of the corresponding post in terms of perceived objects and conducted activities connected to this place. The basis for this is not a purely frequency-based assessment, but a specifically introduced measure called typicality. To evaluate the typicality measure and examine the assumption that emojis are contextual indicants, a dataset of worldwide geotagged posts from Instagram relating to sunset and sunrise events is used, converted to a privacy-aware version based on a Hyperloglog approach. Results suggest that emojis can often provide more nuanced information about user activities and the surrounding environment than is possible with hashtags. Thus, emojis may be suitable for identifying less obvious characteristics and the sense of a place. Emojis are already explored in research, but mainly for sentiment analysis, for semantic studies or as part of emoji prediction. In contrast, this work provides novel insights into the user’s spatial or activity context by applying the typicality measure and therefore considers emojis contextual indicants. Full article

(This article belongs to the Special Issue Social Computing for Geographic Information Science)

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Open AccessEditor’s ChoiceArticle

Automatic Delineation of Urban Growth Boundaries Based on Topographic Data Using Germany as a Case Study

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ISPRS Int. J. Geo-Inf. 2021, 10(5), 353; https://doi.org/10.3390/ijgi10050353 - 20 May 2021

Cited by 12 | Viewed by 3331

Abstract

Urban Growth Boundary (UGB) is a growth management policy that designates specific areas where growth should be concentrated in order to avoid urban sprawl. The objective of such a boundary is to protect agricultural land, open spaces and the natural environment, as well [...] Read more.

Urban Growth Boundary (UGB) is a growth management policy that designates specific areas where growth should be concentrated in order to avoid urban sprawl. The objective of such a boundary is to protect agricultural land, open spaces and the natural environment, as well as to use existing infrastructure and public services more efficiently. Due to the inherent heterogeneity and complexity of settlements, UGBs in Germany are currently created manually by experts. Therefore, every dataset is linked to a specific area, investigation period and dedicated use. Clearly, up-to-date, homogeneous, meaningful and cost-efficient delineations created automatically are needed to avoid this reliance on manually or semi-automatically generated delineations. Here, we present an aggregative method to produce UGBs using building footprints and generally available topographic data as inputs. It was applied to study areas in Frankfurt/Main, the Hanover region and rural Brandenburg while taking full account of Germany’s planning and legal framework for spatial development. Our method is able to compensate for most of the weaknesses of available UGB data and to significantly raise the accuracy of UGBs in Germany. Therefore, it represents a valuable tool for generating basic data for future studies. Application elsewhere is also conceivable by regionalising the employed parameters. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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Open AccessEditor’s ChoiceArticle

Coupling Historical Maps and LiDAR Data to Identify Man-Made Landforms in Urban Areas

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ISPRS Int. J. Geo-Inf. 2021, 10(5), 349; https://doi.org/10.3390/ijgi10050349 - 18 May 2021

Cited by 13 | Viewed by 3026

Abstract

In recent years, there has been growing interest in urban geomorphology both for its applications in terms of landscape planning, and its historical, cultural, and scientific interest. Due to recent urban growth, the identification of landforms in cities is difficult, particularly in Mediterranean [...] Read more.

In recent years, there has been growing interest in urban geomorphology both for its applications in terms of landscape planning, and its historical, cultural, and scientific interest. Due to recent urban growth, the identification of landforms in cities is difficult, particularly in Mediterranean and central European cities, characterized by more than 1000 years of urban stratification. By comparing and overlapping 19th-century cartography and modern topography from remote sensing data, this research aims to assess the morphological evolution of the city of Genoa (Liguria, NW Italy). The analysis focuses on a highly detailed 1:2’000 scale map produced by Eng. Ignazio Porro in the mid-19th century. The methodology, developed in QGIS, was applied on five case studies of both hillside and valley floor areas of the city of Genoa. Through map overlay and digitalization of elevation data and contour lines, it was possible to identify with great accuracy the most significant morphological transformations that have occurred in the city since the mid-19th century. In addition, the results were validated by direct observation and by drills data of the regional database. The results allowed the identification and quantification of the main anthropic landforms. The paper suggests that the same methodology can be applied to other historical urban contexts characterized by urban and architectural stratification. Full article

(This article belongs to the Special Issue Geographic Information Science (GIScience) and Geospatial Approaches for the Analysis of Historical Visual Sources and Cartographic Material)

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Open AccessEditor’s ChoiceArticle

What Is the Shape of Geographical Time-Space? A Three-Dimensional Model Made of Curves and Cones

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Alain L’Hostis

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Farouk Abdou

ISPRS Int. J. Geo-Inf. 2021, 10(5), 340; https://doi.org/10.3390/ijgi10050340 - 17 May 2021

Cited by 2 | Viewed by 3171

Abstract

Geographical time-spaces exhibit a series of properties, including space inversion, that turns any representation effort into a complex task. In order to improve the legibility of the representation and leveraging the advances of three-dimensional computer graphics, the aim of the study is to [...] Read more.

Geographical time-spaces exhibit a series of properties, including space inversion, that turns any representation effort into a complex task. In order to improve the legibility of the representation and leveraging the advances of three-dimensional computer graphics, the aim of the study is to propose a new method extending time-space relief cartography introduced by Mathis and L’Hostis. The novelty of the model resides in the use of cones to describing the terrestrial surface instead of graph faces, and in the use of curves instead of broken segments for edges. We implement the model on the Chinese space. The Chinese geographical time-space of reference year 2006 is produced by the combination and the confrontation of the fast air transport system and of the 7.5-times slower road transport system. Slower, short range flights are represented as curved lines above the earth surface with longer length than the geodesic, in order to account for a slower speed. The very steep slope of cones expresses the relative difficulty of crossing terrestrial time-space, as well as the comparably extreme efficiency of long-range flights for moving between cities. Finally, the whole image proposes a coherent representation of the geographical time-space where fast city-to-city transport is combined with slow terrestrial systems that allow one to reach any location. Full article

(This article belongs to the Special Issue Spatio-Temporal Models and Geo-Technologies)

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Open AccessEditor’s ChoiceArticle

Vector Map Encryption Algorithm Based on Double Random Position Permutation Strategy

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Xiaolong Wang

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Haowen Yan

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Liming Zhang

ISPRS Int. J. Geo-Inf. 2021, 10(5), 311; https://doi.org/10.3390/ijgi10050311 - 07 May 2021

Cited by 6 | Viewed by 2402

Abstract

Encryption of vector maps, used for copyright protection, is of importance in the community of geographic information sciences. However, some studies adopt one-to-one mapping to scramble vertices and permutate the coordinates one by one according to the coordinate position in a plain map. [...] Read more.

Encryption of vector maps, used for copyright protection, is of importance in the community of geographic information sciences. However, some studies adopt one-to-one mapping to scramble vertices and permutate the coordinates one by one according to the coordinate position in a plain map. An attacker can easily obtain the key values by analyzing the relationship between the cipher vector map and the plain vector map, which will lead to the ineffectiveness of the scrambling operation. To solve the problem, a vector map encryption algorithm based on a double random position permutation strategy is proposed in this paper. First, the secret key sequence is generated using a four-dimensional quadratic autonomous hyperchaotic system. Then, all coordinates of the vector map are encrypted using the strategy of double random position permutation. Lastly, the encrypted coordinates are reorganized according to the vector map structure to obtain the cipher map. Experimental results show that: (1) one-to-one mapping between the plain vector map and cipher vector map is prevented from happening; (2) scrambling encryption between different map objects is achieved; (3) hackers cannot obtain the permutation key value by analyzing the pairs of the plain map and cipher map. Full article

(This article belongs to the Special Issue Cartographic Communication of Big Data)

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Open AccessEditor’s ChoiceArticle

Context-Specific Point-of-Interest Recommendation Based on Popularity-Weighted Random Sampling and Factorization Machine

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ISPRS Int. J. Geo-Inf. 2021, 10(4), 258; https://doi.org/10.3390/ijgi10040258 - 11 Apr 2021

Cited by 4 | Viewed by 1834

Abstract

Point-Of-Interest (POI) recommendation not only assists users to find their preferred places, but also helps businesses to attract potential customers. Recent studies have proposed many approaches to the POI recommendation. However, the lack of negative samples and the complexities of check-in contexts limit [...] Read more.

Point-Of-Interest (POI) recommendation not only assists users to find their preferred places, but also helps businesses to attract potential customers. Recent studies have proposed many approaches to the POI recommendation. However, the lack of negative samples and the complexities of check-in contexts limit their effectiveness significantly. This paper focuses on the problem of context-specific POI recommendation based on the check-in behaviors recorded by Location-Based Social Network (LBSN) services, which aims at recommending a list of POIs for a user to visit at a given context (such as time and weather). Specifically, a bidirectional influence correlativity metric is proposed to measure the semantic feature of user check-in behavior, and a contextual smoothing method to effectively alleviate the problem of data sparsity. In addition, the check-in probability is computed based on the geographical distance between the user’s home and the POI. Furthermore, to handle the problem of no negative feedback in LBSN, a weighted random sampling method is proposed based on contextual popularity. Finally, the recommendation results is obtained by utilizing Factorization Machine with Bayesian Personalized Ranking (BPR) loss. Experiments on a real dataset collected from Foursquare show that the proposed approach has better performance than others. Full article

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Open AccessEditor’s ChoiceArticle

On the Use of ‘Glyphmaps’ for Analysing the Scale and Temporal Spread of COVID-19 Reported Cases

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ISPRS Int. J. Geo-Inf. 2021, 10(4), 213; https://doi.org/10.3390/ijgi10040213 - 01 Apr 2021

Cited by 3 | Viewed by 2595

Abstract

Recent analysis of area-level COVID-19 cases data attempts to grapple with a challenge familiar to geovisualization: how to capture the development of the virus, whilst supporting analysis across geographic areas? We present several glyphmap designs for addressing this challenge applied to local authority [...] Read more.

Recent analysis of area-level COVID-19 cases data attempts to grapple with a challenge familiar to geovisualization: how to capture the development of the virus, whilst supporting analysis across geographic areas? We present several glyphmap designs for addressing this challenge applied to local authority data in England whereby charts displaying multiple aspects related to the pandemic are given a geographic arrangement. These graphics are visually complex, with clutter, occlusion and salience bias an inevitable consequence. We develop a framework for describing and validating the graphics against data and design requirements. Together with an observational data analysis, this framework is used to evaluate our designs, relating them to particular data analysis needs based on the usefulness of the structure they expose. Our designs, documented in an accompanying code repository, attend to common difficulties in geovisualization design and could transfer to contexts outside of the UK and to phenomena beyond the pandemic. Full article

(This article belongs to the Special Issue Geospatial Approaches for Understanding the Social, Economic and Environmental Impacts of COVID-19)

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Open AccessEditor’s ChoiceArticle

Comparing World City Networks by Language: A Complex-Network Approach

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Wenjia Zhang

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Jiancheng Zhu

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Pu Zhao

ISPRS Int. J. Geo-Inf. 2021, 10(4), 219; https://doi.org/10.3390/ijgi10040219 - 01 Apr 2021

Cited by 6 | Viewed by 2107

Abstract

City networks are multiplex and diverse rather than being regarded as part of a single universal model that is valid worldwide. This study contributes to the debate on multiple globalizations by distinguishing multiscale structures of world city networks (WCNs) reflected in the Internet [...] Read more.

City networks are multiplex and diverse rather than being regarded as part of a single universal model that is valid worldwide. This study contributes to the debate on multiple globalizations by distinguishing multiscale structures of world city networks (WCNs) reflected in the Internet webpage content in English, German, and French. Using big data sets from web crawling, we adopted a complex-network approach with both macroscale and mesoscale analyses to compare global and grouping properties in varying WCNs, by using novel methods such as the weighted stochastic block model (WSBM). The results suggest that at the macro scale, the rankings of city centralities vary across languages due to the uneven geographic distribution of languages and the variant levels of globalization of cities perceived in different languages. At the meso scale, the WSBMs infer different grouping patterns in the WCNs by language, and the specific roles of many world cities vary with language. The probability-based comparative analyses reveal that the English WCN looks more globalized, while the French and German worlds appear more territorial. Using the mesoscale structure detected in the English WCN to comprehend the city networks in other languages may be biased. These findings demonstrate the importance of scrutinizing multiplex WCNs in different cultures and languages as well as discussing mesoscale structures in comparative WCN studies. Full article

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Open AccessFeature PaperEditor’s ChoiceArticle

Empirical Insights from a Study on Outlier Preserving Value Generalization in Animated Choropleth Maps

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Christoph Traun

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Manuela Larissa Schreyer

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Gudrun Wallentin

ISPRS Int. J. Geo-Inf. 2021, 10(4), 208; https://doi.org/10.3390/ijgi10040208 - 01 Apr 2021

Cited by 4 | Viewed by 1991

Abstract

Time series animation of choropleth maps easily exceeds our perceptual limits. In this empirical research, we investigate the effect of local outlier preserving value generalization of animated choropleth maps on the ability to detect general trends and local deviations thereof. Comparing generalization in [...] Read more.

Time series animation of choropleth maps easily exceeds our perceptual limits. In this empirical research, we investigate the effect of local outlier preserving value generalization of animated choropleth maps on the ability to detect general trends and local deviations thereof. Comparing generalization in space, in time, and in a combination of both dimensions, value smoothing based on a first order spatial neighborhood facilitated the detection of local outliers best, followed by the spatiotemporal and temporal generalization variants. We did not find any evidence that value generalization helps in detecting global trends. Full article

(This article belongs to the Special Issue Multimedia Cartography)

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Open AccessEditor’s ChoiceArticle

Beyond Objects in Space-Time: Towards a Movement Analysis Framework with ‘How’ and ‘Why’ Elements

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Saeed Rahimi

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Antoni B. Moore

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Peter A. Whigham

ISPRS Int. J. Geo-Inf. 2021, 10(3), 190; https://doi.org/10.3390/ijgi10030190 - 22 Mar 2021

Cited by 2 | Viewed by 2172

Abstract

Current spatiotemporal data has facilitated movement studies to shift objectives from descriptive models to explanations of the underlying causes of movement. From both a practical and theoretical standpoint, progress in developing approaches for these explanations should be founded on a conceptual model. This [...] Read more.

Current spatiotemporal data has facilitated movement studies to shift objectives from descriptive models to explanations of the underlying causes of movement. From both a practical and theoretical standpoint, progress in developing approaches for these explanations should be founded on a conceptual model. This paper presents such a model in which three conceptual levels of abstraction are proposed to frame an agent-based representation of movement decision-making processes: ‘attribute,’ ‘actor,’ and ‘autonomous agent’. These in combination with three temporal, spatial, and spatiotemporal general forms of observations distinguish nine (3 × 3) representation typologies of movement data within the agent framework. Thirdly, there are three levels of cognitive reasoning: ‘association,’ ‘intervention,’ and ‘counterfactual’. This makes for 27 possible types of operation embedded in a conceptual cube with the level of abstraction, type of observation, and degree of cognitive reasoning forming the three axes. The conceptual model is an arena where movement queries and the statement of relevant objectives takes place. An example implementation of a tightly constrained spatiotemporal scenario to ground the agent-structure was summarised. The platform has been well-defined so as to accommodate different tools and techniques to drive causal inference in computational movement analysis as an immediate future step. Full article

(This article belongs to the Special Issue Innovations in Agent-Based Modelling of Spatial Systems)

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Open AccessEditor’s ChoiceArticle

Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models

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Cyril Carré

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Younes Hamdani

ISPRS Int. J. Geo-Inf. 2021, 10(3), 188; https://doi.org/10.3390/ijgi10030188 - 22 Mar 2021

Cited by 2 | Viewed by 3024

Abstract

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a [...] Read more.

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling. Full article

(This article belongs to the Special Issue Spatio-Temporal Models and Geo-Technologies)

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Open AccessEditor’s ChoiceArticle

A Decentralized Semantic Reasoning Approach for the Detection and Representation of Continuous Spatial Dynamic Phenomena in Wireless Sensor Networks

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Roger Cesarié Ntankouo Njila

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Mir Abolfazl Mostafavi

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Jean Brodeur

ISPRS Int. J. Geo-Inf. 2021, 10(3), 182; https://doi.org/10.3390/ijgi10030182 - 19 Mar 2021

Cited by 2 | Viewed by 1731

Abstract

In this paper, we propose a decentralized semantic reasoning approach for modeling vague spatial objects from sensor network data describing vague shape phenomena, such as forest fire, air pollution, traffic noise, etc. This is a challenging problem as it necessitates appropriate aggregation of [...] Read more.

In this paper, we propose a decentralized semantic reasoning approach for modeling vague spatial objects from sensor network data describing vague shape phenomena, such as forest fire, air pollution, traffic noise, etc. This is a challenging problem as it necessitates appropriate aggregation of sensor data and their update with respect to the evolution of the state of the phenomena to be represented. Sensor data are generally poorly provided in terms of semantic information. Hence, the proposed approach starts with building a knowledge base integrating sensor and domain ontologies and then uses fuzzy rules to extract three-valued spatial qualitative information expressing the relative position of each sensor with respect to the monitored phenomenon’s extent. The observed phenomena are modeled using a fuzzy-crisp type spatial object made of a kernel and a conjecture part, which is a more realistic spatial representation for such vague shape environmental phenomena. The second step of our approach uses decentralized computing techniques to infer boundary detection and vertices for the kernel and conjecture parts of spatial objects using fuzzy IF-THEN rules. Finally, we present a case study for urban noise pollution monitoring by a sensor network, which is implemented in Netlogo to illustrate the validity of the proposed approach. Full article

(This article belongs to the Special Issue Applications of Discrete and Computational Geometry to Geoprocessing)

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Open AccessFeature PaperEditor’s ChoiceReview

Synthesizing Vulnerability, Risk, Resilience, and Sustainability into VRRSability for Improving Geoinformation Decision Support Evaluations

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 179; https://doi.org/10.3390/ijgi10030179 - 18 Mar 2021

Cited by 1 | Viewed by 2188

Abstract

This paper synthesizes vulnerability, risk, resilience, and sustainability (VRRS) in a way that can be used for decision evaluations about sustainable systems, whether such systems are called coupled natural–human systems, social–ecological systems, coupled human–environment systems, and/or hazards influencing global environmental change, all considered [...] Read more.

This paper synthesizes vulnerability, risk, resilience, and sustainability (VRRS) in a way that can be used for decision evaluations about sustainable systems, whether such systems are called coupled natural–human systems, social–ecological systems, coupled human–environment systems, and/or hazards influencing global environmental change, all considered geospatial open systems. Evaluations of V-R-R-S as separate concepts for complex decision problems are important, but more insightful when synthesized for improving integrated decision priorities based on trade-offs of V-R-R-S objectives. A synthesis concept, called VRRSability, provides an overarching perspective that elucidates Tier 2 of a previously developed four-tier framework for organizing measurement-informed ontology and epistemology for sustainability information representation (MOESIR). The new synthesis deepens the MOESIR framework to address VRRSability information representation and clarifies the Tier 2 layer of abstraction. This VRRSability synthesis, composed of 13 components (several with sub-components), offers a controlled vocabulary as the basis of a conceptual framework for organizing workflow assessment and intervention strategies as part of geoinformation decision support software. Researchers, practitioners, and machine learning algorithms can use the vocabulary results for characterizing functional performance relationships between elements of geospatial open systems and the computing technology systems used for evaluating them within a context of complex sustainable systems. Full article

(This article belongs to the Special Issue Geospatial Open Systems)

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Open AccessEditor’s ChoiceArticle

Consideration of Uncertainty Information in Accessibility Analyses for an Effective Use of Urban Infrastructures

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Jochen Schiewe

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Martin Knura

ISPRS Int. J. Geo-Inf. 2021, 10(3), 171; https://doi.org/10.3390/ijgi10030171 - 16 Mar 2021

Cited by 1 | Viewed by 1793

Abstract

Accessibility analyses are an essential step in the evaluation and planning of urban infrastructures such as transport or pipeline networks. However, these studies generally produce sharply defined lines (called isovarones) or areas (called isovarone areas) that represent the same or similar accessibility. Uncertainties [...] Read more.

Accessibility analyses are an essential step in the evaluation and planning of urban infrastructures such as transport or pipeline networks. However, these studies generally produce sharply defined lines (called isovarones) or areas (called isovarone areas) that represent the same or similar accessibility. Uncertainties in the input data are usually not taken into account. The aim of this contribution is, therefore, to set up a structured framework that describes the integration of uncertainty information for accessibility analyses. This framework takes uncertainties in the input data, in the processing step, in the target variables, and in the final visualization into account. Particular attention is paid, on the one hand, to the impact of the uncertainties in the target values, as these are key factors for reasoning and decision making. On the other hand, the visualization component is emphasized by applying a dichotomous classification of uncertainty visualization methods. This framework leads to a large set of possible combinations of uncertainty categories. Five selected examples that have been generated with a new software tool and that cover important combinations are presented and discussed. Full article

(This article belongs to the Special Issue Geo-Information for Developing Urban Infrastructures)

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Open AccessEditor’s ChoiceArticle

Building a Large-Scale Micro-Simulation Transport Scenario Using Big Data

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 165; https://doi.org/10.3390/ijgi10030165 - 14 Mar 2021

Cited by 14 | Viewed by 3314

Abstract

A large-scale agent-based microsimulation scenario including the transport modes car, bus, bicycle, scooter, and pedestrian, is built and validated for the city of Bologna (Italy) during the morning peak hour. Large-scale microsimulations enable the evaluation of city-wide effects of novel and complex transport [...] Read more.

A large-scale agent-based microsimulation scenario including the transport modes car, bus, bicycle, scooter, and pedestrian, is built and validated for the city of Bologna (Italy) during the morning peak hour. Large-scale microsimulations enable the evaluation of city-wide effects of novel and complex transport technologies and services, such as intelligent traffic lights or shared autonomous vehicles. Large-scale microsimulations can be seen as an interdisciplinary project where transport planners and technology developers can work together on the same scenario; big data from OpenStreetMap, traffic surveys, GPS traces, traffic counts and transit details are merged into a unique transport scenario. The employed activity-based demand model is able to simulate and evaluate door-to-door trip times while testing different mobility strategies. Indeed, a utility-based mode choice model is calibrated that matches the official modal split. The scenario is implemented and analyzed with the software SUMOPy/SUMO which is an open source software, available on GitHub. The simulated traffic flows are compared with flows from traffic counters using different indicators. The determination coefficient has been 0.7 for larger roads (width greater than seven meters). The present work shows that it is possible to build realistic microsimulation scenarios for larger urban areas. A higher precision of the results could be achieved by using more coherent data and by merging different data sources. Full article

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Open AccessEditor’s ChoiceArticle

The Role of Spatio-Temporal Information to Govern the COVID-19 Pandemic: A European Perspective

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Hartmut Müller

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Marije Louwsma

ISPRS Int. J. Geo-Inf. 2021, 10(3), 166; https://doi.org/10.3390/ijgi10030166 - 14 Mar 2021

Cited by 4 | Viewed by 2399

Abstract

The Covid-19 pandemic put a heavy burden on member states in the European Union. To govern the pandemic, having access to reliable geo-information is key for monitoring the spatial distribution of the outbreak over time. This study aims to analyze the role of [...] Read more.

The Covid-19 pandemic put a heavy burden on member states in the European Union. To govern the pandemic, having access to reliable geo-information is key for monitoring the spatial distribution of the outbreak over time. This study aims to analyze the role of spatio-temporal information in governing the pandemic in the European Union and its member states. The European Nomenclature of Territorial Units for Statistics (NUTS) system and selected national dashboards from member states were assessed to analyze which spatio-temporal information was used, how the information was visualized and whether this changed over the course of the pandemic. Initially, member states focused on their own jurisdiction by creating national dashboards to monitor the pandemic. Information between member states was not aligned. Producing reliable data and timeliness reporting was problematic, just like selecting indictors to monitor the spatial distribution and intensity of the outbreak. Over the course of the pandemic, with more knowledge about the virus and its characteristics, interventions of member states to govern the outbreak were better aligned at the European level. However, further integration and alignment of public health data, statistical data and spatio-temporal data could provide even better information for governments and actors involved in managing the outbreak, both at national and supra-national level. The Infrastructure for Spatial Information in Europe (INSPIRE) initiative and the NUTS system provide a framework to guide future integration and extension of existing systems. Full article

(This article belongs to the Special Issue Spatio-Temporal Models and Geo-Technologies)

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Open AccessEditor’s ChoiceArticle

Effectiveness of Memorizing an Animated Route—Comparing Satellite and Road Map Differences in the Eye-Tracking Study

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Paweł Cybulski

ISPRS Int. J. Geo-Inf. 2021, 10(3), 159; https://doi.org/10.3390/ijgi10030159 - 12 Mar 2021

Cited by 7 | Viewed by 2235

Abstract

There is no consensus on the importance of satellite images in the process of memorizing a route from a map image, especially if the route is displayed on the Internet using dynamic (animated) cartographic visualization. In modern dynamic maps built with JavaScript APIs, [...] Read more.

There is no consensus on the importance of satellite images in the process of memorizing a route from a map image, especially if the route is displayed on the Internet using dynamic (animated) cartographic visualization. In modern dynamic maps built with JavaScript APIs, background layers can be easily altered by map users. The animation attracts people’s attention better than static images, but it causes some perceptual problems. This study examined the influence of the number of turns on the effectiveness (correctness) and efficiency of memorizing the animated route on different cartographic backgrounds. The routes of three difficulty levels, based on satellite and road background, were compared. The results show that the satellite background was not a significant factor influencing the efficiency and effectiveness of route memorizing. Recordings of the eye movement confirmed this. The study reveals that there were intergroup differences in participants’ visual behavior. Participants who described their spatial abilities as “very good” performed better (in terms of effectiveness and efficiency) in route memorizing tasks. For future research, there is a need to study route variability and its impact on participants’ performance. Moreover, future studies should involve differences in route visualization (e.g., without and with ephemeral or permanent trail). Full article

(This article belongs to the Special Issue Multimedia Cartography)

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Open AccessEditor’s ChoiceArticle

Development after Displacement: Evaluating the Utility of OpenStreetMap Data for Monitoring Sustainable Development Goal Progress in Refugee Settlements

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 153; https://doi.org/10.3390/ijgi10030153 - 10 Mar 2021

Cited by 11 | Viewed by 3801

Abstract

In 2015, 193 countries declared their commitment to “leave no one behind” in pursuit of 17 Sustainable Development Goals (SDGs). However, the world’s refugees have been routinely excluded from national censuses and representative surveys, and, as a result, have broadly been overlooked in [...] Read more.

In 2015, 193 countries declared their commitment to “leave no one behind” in pursuit of 17 Sustainable Development Goals (SDGs). However, the world’s refugees have been routinely excluded from national censuses and representative surveys, and, as a result, have broadly been overlooked in SDG evaluations. In this study, we examine the potential of OpenStreetMap (OSM) data for monitoring SDG progress in refugee settlements. We collected all available OSM data in 28 refugee and 26 nearby non-refugee settlements in the major refugee-hosting country of Uganda. We created a novel SDG-OSM data model, measured the spatial and temporal coverages of SDG-relevant OSM data across refugee settlements, and compared these results to non-refugee settlements. We found 11 different SDGs represented across 92% (21,950) of OSM data in refugee settlements, compared to 78% (1919 nodes) in non-refugee settlements. However, most data were created three years after refugee arrival, and 81% of OSM data in refugee settlements were never edited, both of which limit the potential for long-term monitoring of SDG progress. In light of our findings, we offer suggestions for improving OSM-driven SDG monitoring in refugee settlements that have relevance for development and humanitarian practitioners and research communities alike. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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Open AccessEditor’s ChoiceArticle

Simultaneous Extraction of Road and Centerline from Aerial Images Using a Deep Convolutional Neural Network

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Tamara Alshaikhli

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Wen Liu

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Yoshihisa Maruyama

ISPRS Int. J. Geo-Inf. 2021, 10(3), 147; https://doi.org/10.3390/ijgi10030147 - 08 Mar 2021

Cited by 1 | Viewed by 1382

Abstract

The extraction of roads and centerlines from aerial imagery is considered an important topic because it contributes to different fields, such as urban planning, transportation engineering, and disaster mitigation. Many researchers have studied this topic as a two-separated task that affects the quality [...] Read more.

The extraction of roads and centerlines from aerial imagery is considered an important topic because it contributes to different fields, such as urban planning, transportation engineering, and disaster mitigation. Many researchers have studied this topic as a two-separated task that affects the quality of extracted roads and centerlines because of the correlation between these two tasks. Accurate road extraction enhances accurate centerline extraction if these two tasks are processed simultaneously. This study proposes a multitask learning scheme using a gated deep convolutional neural network (DCNN) to extract roads and centerlines simultaneously. The DCNN is composed of one encoder and two decoders implemented on the U-Net backbone. The decoders are assigned to extract roads and centerlines from low-resolution feature maps. Before extraction, the images are processed within an encoder to extract the spatial information from a complex, high-resolution image. The encoder consists of the residual blocks (Res-Block) connected to a bridge represented by a Res-Block, and the bridge connects the two identical decoders, which consists of stacking convolutional layers (Conv.layer). Attention gates (AGs) are added to our model to enhance the selection process for the true pixels that represent road or centerline classes. Our model is trained on a dataset of high-resolution aerial images, which is open to the public. The model succeeds in efficiently extracting roads and centerlines compared with other multitask learning models. Full article

(This article belongs to the Special Issue Advanced Methodology for Developing an Inventory Database of Human-Made Structures in Urban Areas for Assessment of Risk and Vulnerability)

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Open AccessEditor’s ChoiceArticle

Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 148; https://doi.org/10.3390/ijgi10030148 - 08 Mar 2021

Cited by 9 | Viewed by 2129

Abstract

Interpersonal and intrapersonal variabilities are two important perspectives to understand daily travel behaviors, while only a small number of studies incorporate them for understanding human dynamics. This paper employed a network analysis approach to detecting daily activity-travel patterns of 680 Beijing’s residents within [...] Read more.

Interpersonal and intrapersonal variabilities are two important perspectives to understand daily travel behaviors, while only a small number of studies incorporate them for understanding human dynamics. This paper employed a network analysis approach to detecting daily activity-travel patterns of 680 Beijing’s residents within a week and then used a multilevel multinomial logit model to analyze the intrapersonal variability in patterns and the socioeconomic linkages behind them. Results suggest that most activity-travel patterns have significant day-to-day intrapersonal and interpersonal variabilities. This suggests that the application of a typical day of activity-travel behaviors to measure and represent a week’s or even longer-term behaviors may be biased, due to the existence of day-to-day intrapersonal variability. This study also provides a hint for the selection of days of a week to conduct a diary survey for activity pattern mining or travel demand modeling. Full article

(This article belongs to the Special Issue Geospatial Methods in Social and Behavioral Sciences)

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Open AccessEditor’s ChoiceArticle

Effects of Virtual Reality Locomotion Techniques on Distance Estimations

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 150; https://doi.org/10.3390/ijgi10030150 - 08 Mar 2021

Cited by 36 | Viewed by 4716

Abstract

Mental representations of geographic space are based on knowledge of spatial elements and the spatial relation between these elements. Acquiring such mental representations of space requires assessing distances between pairs of spatial elements. In virtual reality (VR) applications, locomotion techniques based on real-world [...] Read more.

Mental representations of geographic space are based on knowledge of spatial elements and the spatial relation between these elements. Acquiring such mental representations of space requires assessing distances between pairs of spatial elements. In virtual reality (VR) applications, locomotion techniques based on real-world movement are constrained by the size of the available room and the used room scale tracking system. Therefore, many VR applications use additional locomotion techniques such as artificial locomotion (continuous forward movement) or teleporting (“jumping” from one location to another). These locomotion techniques move the user through virtual space based on controller input. However, it has not yet been investigated how different established controller-based locomotion techniques affect distance estimations in VR. In an experiment, we compared distance estimations between artificial locomotion and teleportation before and after a training phase. The results showed that distance estimations in both locomotion conditions improved after the training. Additionally, distance estimations were found to be more accurate when teleportation locomotion was used. Full article

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Open AccessEditor’s ChoiceArticle

The Extended Concept of the Map in View of Modern Geoinformation Products

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Dariusz Gotlib

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Robert Olszewski

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Georg Gartner

ISPRS Int. J. Geo-Inf. 2021, 10(3), 142; https://doi.org/10.3390/ijgi10030142 - 05 Mar 2021

Cited by 3 | Viewed by 1595

Abstract

In the face of strikingly intense technological development, there have been significant discrepancies in the understanding of the concept of the map; an understanding that is fundamental to cartography and, more broadly, GIScience. The development of electronic products based on geoinformation has caused [...] Read more.

In the face of strikingly intense technological development, there have been significant discrepancies in the understanding of the concept of the map; an understanding that is fundamental to cartography and, more broadly, GIScience. The development of electronic products based on geoinformation has caused a growing need for the systematization of basic concepts, including defining what a map is. In particular, the modification of the idea of the map may profoundly influence the future development of cartography. The comprehensive and innovative use of maps, for example, in location-based service (LBS) applications, may contribute to more in-depth analyses in this area. This article examines how the concept of how the map is used in technological or scientific literature about the latest geoinformation applications, as well as analyzing the survey results that confirm the change in social perception of the concept of the map in cartography. The article also refers to the role of the map in the process of indirect cognition and understanding of geographical space—cognition realized through maps. A social understanding of mapping concepts is evolving and covers the entire spectrum of geoinformation products. It seems that the latest geoinformation solutions, such as navigation applications and, in particular, applications supporting the movement of autonomous vehicles (e.g., self-driving cars), have had a particular impact on the concept of the map. This is confirmed by the results of a survey conducted by the authors on a group of nearly 900 respondents from a variety of countries. The vast majority of users are convinced that the contemporary understanding of the concept of the map is a long way from the classic definition of this concept. Therefore, in the opinion of the authors of this article, it is worth undertaking research that will become a starting point for a discussion about the broader definition of the map in GIScience. Full article

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Open AccessEditor’s ChoiceArticle

Geospatial Queries on Data Collection Using a Common Provenance Model

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 139; https://doi.org/10.3390/ijgi10030139 - 05 Mar 2021

Cited by 3 | Viewed by 1645

Abstract

Lineage information is the part of the metadata that describes “what”, “when”, “who”, “how”, and “where” geospatial data were generated. If it is well-presented and queryable, lineage becomes very useful information for inferring data quality, tracing error sources and increasing trust in geospatial [...] Read more.

Lineage information is the part of the metadata that describes “what”, “when”, “who”, “how”, and “where” geospatial data were generated. If it is well-presented and queryable, lineage becomes very useful information for inferring data quality, tracing error sources and increasing trust in geospatial information. In addition, if the lineage of a collection of datasets can be related and presented together, datasets, process chains, and methodologies can be compared. This paper proposes extending process step lineage descriptions into four explicit levels of abstraction (process run, tool, algorithm and functionality). Including functionalities and algorithm descriptions as a part of lineage provides high-level information that is independent from the details of the software used. Therefore, it is possible to transform lineage metadata that is initially documenting specific processing steps into a reusable workflow that describes a set of operations as a processing chain. This paper presents a system that provides lineage information as a service in a distributed environment. The system is complemented by an integrated provenance web application that is capable of visualizing and querying a provenance graph that is composed by the lineage of a collection of datasets. The International Organization for Standardization (ISO) 19115 standards family with World Wide Web Consortium (W3C) provenance initiative (W3C PROV) were combined in order to integrate provenance of a collection of datasets. To represent lineage elements, the ISO 19115-2 lineage class names were chosen, because they express the names of the geospatial objects that are involved more precisely. The relationship naming conventions of W3C PROV are used to represent relationships among these elements. The elements and relationships are presented in a queryable graph. Full article

(This article belongs to the Special Issue Geospatial Metadata)

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Open AccessEditor’s ChoiceArticle

Near Real-Time Semantic View Analysis of 3D City Models in Web Browser

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 138; https://doi.org/10.3390/ijgi10030138 - 04 Mar 2021

Cited by 16 | Viewed by 4162

Abstract

3D city models and their browser-based applications have become an increasingly applied tool in the cities. One of their applications is the analysis views and visibility, applicable to property valuation and evaluation of urban green infrastructure. We present a near real-time semantic view [...] Read more.

3D city models and their browser-based applications have become an increasingly applied tool in the cities. One of their applications is the analysis views and visibility, applicable to property valuation and evaluation of urban green infrastructure. We present a near real-time semantic view analysis relying on a 3D city model, implemented in a web browser. The analysis is tested in two alternative use cases: property valuation and evaluation of the urban green infrastructure. The results describe the elements visible from a given location, and can also be applied to object type specific analysis, such as green view index estimation, with the main benefit being the freedom of choosing the point-of-view obtained with the 3D model. Several promising development directions can be identified based on the current implementation and experiment results, including the integration of the semantic view analysis with virtual reality immersive visualization or 3D city model application development platforms. Full article

(This article belongs to the Special Issue Virtual 3D City Models)

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Open AccessEditor’s ChoiceArticle

Transfer Learning of a Deep Learning Model for Exploring Tourists’ Urban Image Using Geotagged Photos

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 137; https://doi.org/10.3390/ijgi10030137 - 04 Mar 2021

Cited by 26 | Viewed by 3202

Abstract

Recently, as computer vision and image processing technologies have rapidly advanced in the artificial intelligence (AI) field, deep learning technologies have been applied in the field of urban and regional study through transfer learning. In the tourism field, studies are emerging to analyze [...] Read more.

Recently, as computer vision and image processing technologies have rapidly advanced in the artificial intelligence (AI) field, deep learning technologies have been applied in the field of urban and regional study through transfer learning. In the tourism field, studies are emerging to analyze the tourists’ urban image by identifying the visual content of photos. However, previous studies have limitations in properly reflecting unique landscape, cultural characteristics, and traditional elements of the region that are prominent in tourism. With the purpose of going beyond these limitations of previous studies, we crawled 168,216 Flickr photos, created 75 scenes and 13 categories as a tourist’ photo classification by analyzing the characteristics of photos posted by tourists and developed a deep learning model by continuously re-training the Inception-v3 model. The final model shows high accuracy of 85.77% for the Top 1 and 95.69% for the Top 5. The final model was applied to the entire dataset to analyze the regions of attraction and the tourists’ urban image in Seoul. We found that tourists feel attracted to Seoul where the modern features such as skyscrapers and uniquely designed architectures and traditional features such as palaces and cultural elements are mixed together in the city. This work demonstrates a tourist photo classification suitable for local characteristics and the process of re-training a deep learning model to effectively classify a large volume of tourists’ photos. Full article

(This article belongs to the Special Issue Geospatial Artificial Intelligence)

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Open AccessEditor’s ChoiceArticle

Evaluating Social Distancing Measures and Their Association with the Covid-19 Pandemic in South America

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Gisliany Lillian Alves de Oliveira

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Luciana Lima

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Ivanovitch Silva

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Marcel da Câmara Ribeiro-Dantas

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Kayo Henrique Monteiro

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Patricia Takako Endo

ISPRS Int. J. Geo-Inf. 2021, 10(3), 121; https://doi.org/10.3390/ijgi10030121 - 01 Mar 2021

Cited by 11 | Viewed by 4008

Abstract

Social distancing is a powerful non-pharmaceutical intervention used as a way to slow the spread of the SARS-CoV-2 virus around the world since the end of 2019 in China. Taking that into account, this work aimed to identify variations on population mobility in [...] Read more.

Social distancing is a powerful non-pharmaceutical intervention used as a way to slow the spread of the SARS-CoV-2 virus around the world since the end of 2019 in China. Taking that into account, this work aimed to identify variations on population mobility in South America during the pandemic (15 February to 27 October 2020). We used a data-driven approach to create a community mobility index from the Google Covid-19 Community Mobility and relate it to the Covid stringency index from Oxford Covid-19 Government Response Tracker (OxCGRT). Two hypotheses were established: countries which have adopted stricter social distancing measures have also a lower level of circulation (H1), and mobility is occurring randomly in space (H2). Considering a transient period, a low capacity of governments to respond to the pandemic with more stringent measures of social distancing was observed at the beginning of the crisis. In turn, considering a steady-state period, the results showed an inverse relationship between the Covid stringency index and the community mobility index for at least three countries (H1 rejected). Regarding the spatial analysis, global and local Moran indices revealed regional mobility patterns for Argentina, Brazil, and Chile (H1 rejected). In Brazil, the absence of coordinated policies between the federal government and states regarding social distancing may have played an important role for several and extensive clusters formation. On the other hand, the results for Argentina and Chile could be signals for the difficulties of governments in keeping their population under control, and for long periods, even under stricter decrees. Full article

(This article belongs to the Collection Spatial Components of COVID-19 Pandemic)

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Open AccessEditor’s ChoiceArticle

Twitter Use in Hurricane Isaac and Its Implications for Disaster Resilience

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 116; https://doi.org/10.3390/ijgi10030116 - 27 Feb 2021

Cited by 18 | Viewed by 2539

Abstract

Disaster resilience is the capacity of a community to “bounce back” from disastrous events. Most studies rely on traditional data such as census data to study community resilience. With increasing use of social media, new data sources such as Twitter could be utilized [...] Read more.

Disaster resilience is the capacity of a community to “bounce back” from disastrous events. Most studies rely on traditional data such as census data to study community resilience. With increasing use of social media, new data sources such as Twitter could be utilized to monitor human response during different phases of disasters to better understand resilience. An important research question is: Does Twitter use correlate with disaster resilience? Specifically, will communities with more disaster-related Twitter uses be more resilient to disasters, presumably because they have better situational awareness? The underlying issue is that if there are social and geographical disparities in Twitter use, how will such disparities affect communities’ resilience to disasters? This study examines the relationship between Twitter use and community resilience during Hurricane Isaac, which hit Louisiana and Mississippi in August 2012. First, we applied the resilience inference measurement (RIM) model to calculate the resilience indices of 146 affected counties. Second, we analyzed Twitter use and their sentiment patterns through the three phases of Hurricane Isaac—preparedness, response, and recovery. Third, we correlated Twitter use density and sentiment scores with the resilience scores and major social–environmental variables to test whether significant geographical and social disparities in Twitter use existed through the three phases of disaster management. Significant positive correlations were found between Twitter use density and resilience indicators, confirming that communities with higher resilience capacity, which are characterized by better social–environmental conditions, tend to have higher Twitter use. These results imply that Twitter use during disasters could be improved to increase the resilience of affected communities. On the other hand, no significant correlations were found between sentiment scores and resilience indicators, suggesting that further research on sentiment analysis may be needed. Full article

(This article belongs to the Special Issue Applications and Implications in Geosocial Media Monitoring)

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Open AccessEditor’s ChoiceArticle

A Unified Methodology for the Generalisation of the Geometry of Features

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ISPRS Int. J. Geo-Inf. 2021, 10(3), 107; https://doi.org/10.3390/ijgi10030107 - 25 Feb 2021

Cited by 1 | Viewed by 1925

Abstract

The development of generalisation (simplification) methods for the geometry of features in digital cartography in most cases involves the improvement of existing algorithms without their validation with respect to the similarity of feature geometry before and after the process. It also consists of [...] Read more.

The development of generalisation (simplification) methods for the geometry of features in digital cartography in most cases involves the improvement of existing algorithms without their validation with respect to the similarity of feature geometry before and after the process. It also consists of the assessment of results from the algorithms, i.e., characteristics that are indispensable for automatic generalisation. The preparation of a fully automatic generalisation for spatial data requires certain standards, as well as unique and verifiable algorithms for particular groups of features. This enables cartographers to draw features from these databases to be used directly on the maps. As a result, collected data and their generalised unique counterparts at various scales should constitute standardised sets, as well as their updating procedures. This paper proposes a solution which consists in contractive self-mapping (contractor for scale s = 1) that fulfils the assumptions of the Banach fixed-point theorem. The method of generalisation of feature geometry that uses the contractive self-mapping approach is well justified due to the fact that a single update of source data can be applied to all scales simultaneously. Feature data at every scale s < 1 are generalised through contractive mapping, which leads to a unique solution. Further generalisation of the feature is carried out on larger scale spatial data (not necessarily source data), which reduces the time and cost of the new elaboration. The main part of this article is the theoretical presentation of objectifying the complex process of the generalisation of the geometry of a feature. The use of the inherent characteristics of metric spaces, narrowing mappings, Lipschitz and Cauchy conditions, Salishchev measures, and Banach theorems ensure the uniqueness of the generalisation process. Their application to generalisation makes this process objective, as it ensures that there is a single solution for portraying the generalised features at each scale. The present study is dedicated to researchers concerned with the theory of cartography. Full article

(This article belongs to the Special Issue Spatial Optimization and GIS)

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Open AccessEditor’s ChoiceArticle

TouchTerrain—3D Printable Terrain Models

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Chris Harding

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Franek Hasiuk

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Aaron Wood

ISPRS Int. J. Geo-Inf. 2021, 10(3), 108; https://doi.org/10.3390/ijgi10030108 - 25 Feb 2021

Cited by 4 | Viewed by 4831

Abstract

TouchTerrain is a simple-to-use web application that makes creating 3D printable terrain models from anywhere on the globe accessible to a wide range of users, from people with no GIS expertise to power users. For coders, a Python-based standalone version is available from [...] Read more.

TouchTerrain is a simple-to-use web application that makes creating 3D printable terrain models from anywhere on the globe accessible to a wide range of users, from people with no GIS expertise to power users. For coders, a Python-based standalone version is available from the open-source project’s GitHub repository. Analyzing 18 months of web analytics gave us a preliminary look at who is using the TouchTerrain web application and what their models are used for; and to map out what terrains on the globe they chose to 3D print. From July 2019 to January 2021, more than 20,000 terrain models were downloaded. Models were created for many different use cases, including education, research, outdoor activities and crafting mementos. Most models were realized with 3D printers, but a sizable minority used CNC machines. Our own experiences with using 3D printed terrain in a university setting have been very positive so far. Anecdotal evidence points to the strong potential for 3D printed terrain models to provide significant help with specific map-related tasks. For the introductory geology laboratory, 3D printed models were used as a form of “training wheels” to aid beginning students in learning to read contour maps, which are still an important tool for geology. Full article

(This article belongs to the Special Issue Multimedia Cartography)

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Open AccessEditor’s ChoiceArticle

Practical Efficient Regional Land-Use Planning Using Constrained Multi-Objective Genetic Algorithm Optimization

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ISPRS Int. J. Geo-Inf. 2021, 10(2), 100; https://doi.org/10.3390/ijgi10020100 - 22 Feb 2021

Cited by 15 | Viewed by 2035

Abstract

Practical efficient regional land-use planning requires planners to balance competing uses, regional policies, spatial compatibilities, and priorities across the social, economic, and ecological domains. Genetic algorithm optimization has progressed complex planning, but challenges remain in developing practical alternatives to random initialization, genetic mutations, [...] Read more.

Practical efficient regional land-use planning requires planners to balance competing uses, regional policies, spatial compatibilities, and priorities across the social, economic, and ecological domains. Genetic algorithm optimization has progressed complex planning, but challenges remain in developing practical alternatives to random initialization, genetic mutations, and to pragmatically balance competing objectives. To meet these practical needs, we developed a Land use Intensity-restricted Multi-objective Spatial Optimization (LIr-MSO) model with more realistic patch size initialization, novel mutation, elite strategies, and objectives balanced via nominalizations and weightings. We tested the model for Dapeng, China where experiments compared comprehensive fitness (across conversion cost, Gross Domestic Product (GDP), ecosystem services value, compactness, and conflict degree) with three contrast experiments, in which changes were separately made in the initialization and mutation. The comprehensive model gave superior fitness compared to the contrast experiments. Iterations progressed rapidly to near-optimality, but final convergence involved much slower parent–offspring mutations. Tradeoffs between conversion cost and compactness were strongest, and conflict degree improved in part as an emergent property of the spatial social connectedness built into our algorithm. Observations of rapid iteration to near-optimality with our model can facilitate interactive simulations, not possible with current models, involving land-use planners and regional managers. Full article

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Open AccessFeature PaperEditor’s ChoiceReview

Geoinformation Technologies in Support of Environmental Hazards Monitoring under Climate Change: An Extensive Review

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Andreas Tsatsaris

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