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Mapping Local Climate Zones and Their Applications in European Urban Environments: A Systematic Literature Review and Future Development Trends -
On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness -
3D Visibility Analysis for Evaluating the Attractiveness of Tourism Routes Computed from Social Media Photos -
Assessing the Generalization of Machine Learning-Based Slope Failure Prediction to New Geographic Extents -
Geospatial Decision-Making Framework Based on the Concept of Satisficing
Journal Description
ISPRS International Journal of Geo-Information
ISPRS International Journal of Geo-Information
is an international, peer-reviewed, open access journal on geo-information. It is a journal of the ISPRS (International Society for Photogrammetry and Remote Sensing) and is published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), GeoRef, AGRICOLA, dblp, Astrophysics Data System, Inspec, and many other databases.
- Journal Rank: JCR - Q2 (Geography, Physical) / CiteScore - Q1 (Geography, Planning and Development)
- Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 25.3 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the first half of 2021).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.899 (2020)
;
5-Year Impact Factor:
2.971 (2020)
Latest Articles
Spatiotemporal Characteristics of Urban Land Expansion and Population Growth in Africa from 2001 to 2019: Evidence from Population Density Data
ISPRS Int. J. Geo-Inf. 2021, 10(9), 584; https://doi.org/10.3390/ijgi10090584 - 29 Aug 2021
Abstract
Africa has been undergoing a rapid urbanization process, which is critical to the achievement of the 11th Sustainable Development Goal (SDG11). Using population density data from LandScan, we proposed a population density-based thresholding method to generate urban land and urban population data in
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Africa has been undergoing a rapid urbanization process, which is critical to the achievement of the 11th Sustainable Development Goal (SDG11). Using population density data from LandScan, we proposed a population density-based thresholding method to generate urban land and urban population data in Africa from 2001 to 2019, which were further applied to detect the spatiotemporal characteristics of Africa’s urbanization. The results showed that urban land and urban population have both grown rapidly in Africa, which increased by about 5.92% and 4.91%, respectively. The top three countries with the most intense urbanization process in Africa are Nigeria, the Democratic Republic of the Congo, and Ethiopia. The coupling relationship index of urban land expansion and population growth was 0.76 in Africa during 2001–2019. Meanwhile, the total proportion of uncoordinated development types at the provincial level was getting higher, which indicated an uncoordinated relationship between urban land expansion and population growth in Africa. Cropland, grassland, rural land, and forests were the most land-use types occupied by urban expansion. The proportion of cropland, grassland, and forests occupied was getting higher and higher from 2001 to 2019. The extensive urban land use may have an impact on the environmental and economic benefits brought by urbanization, which needs further research.
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Open AccessArticle
An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach
ISPRS Int. J. Geo-Inf. 2021, 10(9), 583; https://doi.org/10.3390/ijgi10090583 - 28 Aug 2021
Abstract
Urbanization is leading us to a more chaotic state where healthy living becomes a prime concern. The high-rise buildings influence the urban setting with a high shadow rate on surroundings that can have no positive impact on the general neighborhood. Nevertheless, shadows are
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Urbanization is leading us to a more chaotic state where healthy living becomes a prime concern. The high-rise buildings influence the urban setting with a high shadow rate on surroundings that can have no positive impact on the general neighborhood. Nevertheless, shadows are the main factor of defeatist virtual settings, they are expensive to render in real-time. This paper investigates how the amount of sunlight varies by season and how seasons can indicate the time of year to understand how shadows vary in length at different times of the day and how they change over the seasons. We propose a novel efficient (fast and scalable) algorithm to calculate a 2.5D cast-shadow map from a given LiDAR-derived Digital Surface Model (DSM). We present a proof-of-concept demonstration to examine the technical practicability of the introduced algorithm. Tensor-based techniques such as singular value decomposition, tensor unfolding are examined and deployed to represent the multidimensional data. The proposed method exploits horizon mapping ideas and extends the method to a modern graphics algorithm (Bresenham’s line drawing algorithm) to account for the DSM’s underlying surface geometry. A proof-of-concept is developed utilizing Python’s TensorFlow library, exploring data flow graphs and the tensor data structure. The heavy computer graphics algorithm used in this paper is parallelized using PySpark. Results explicate significant enhancements in overall performance while preserving accuracy at negligible variations.
Full article
(This article belongs to the Special Issue Spatio-Temporal Models and Geo-Technologies)
Open AccessArticle
The Asymmetric Pattern of Population Mobility during the Spring Festival in the Yangtze River Delta Based on Complex Network Analysis: An Empirical Analysis of “Tencent Migration” Big Data
ISPRS Int. J. Geo-Inf. 2021, 10(9), 582; https://doi.org/10.3390/ijgi10090582 - 28 Aug 2021
Abstract
Population mobility patterns are an important reflection of the future distribution of migrant populations and the evolution trends of urbanization patterns. However, although research based on statistical data can reveal the pattern of population flow, it also shows a time lag. Most of
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Population mobility patterns are an important reflection of the future distribution of migrant populations and the evolution trends of urbanization patterns. However, although research based on statistical data can reveal the pattern of population flow, it also shows a time lag. Most of the population flow network research based on location services data has failed to fully discuss the symmetry of directional outflows and inflows in the same place and the two-way symmetrical connections between places. This paper creatively proposes and constructs the concept and analysis framework of population flow asymmetry. We used the Yangtze River Delta (YRD) as a typical case and the results of our analysis reveal the temporal and spatial asymmetry of the population flow using complex network analysis methods based on the Spring Festival (SF) population migration big data. We found that the timing asymmetry manifested in such a way that the closer it was to the festival, the greater the scale and intensity of the population movement. This is a feature of the lack of scale and regional differences within China. The spatial asymmetry was manifested in three aspects, network, node, and link, and the core cities with administrative and economic hierarchical advantages dominated the asymmetric pattern of regional population mobility. In addition, distance and administrative boundaries are factors that cannot be ignored in population movements, and they were implicated in the degree of asymmetry by distance enhancement and administrative boundary blocking. The conclusions of this study can not only provide policy decision-making guidelines for population management and resource allocation in the YRD, but they can also provide a reference value for achieving the goal of regional, high-quality, integrated development. Future research will further the discussion and management of socio-economic attributes in order to develop a more detailed and microscopic understanding of the mechanisms of population mobility patterns.
Full article
Open AccessArticle
The Use of PPGIS: Towards Reaching a Meaningful Public Participation in Spatial Planning
ISPRS Int. J. Geo-Inf. 2021, 10(9), 581; https://doi.org/10.3390/ijgi10090581 - 28 Aug 2021
Abstract
Together with technological innovations and the development of a digital society, PPGIS approaches have been rapidly growing popular in the last years, in Poland’s local administration. Local governments take significant interest in online tools; however the principles of public participation, which, in fact,
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Together with technological innovations and the development of a digital society, PPGIS approaches have been rapidly growing popular in the last years, in Poland’s local administration. Local governments take significant interest in online tools; however the principles of public participation, which, in fact, should also be applied to e-consultations, are still missing. One of the assumed roles of PPGIS is to support public participation—not just in terms of the number of stakeholders, but especially in terms of the impact on decision making. The present paper discusses the results of investigations into two decision-making processes, regarding local spatial planning in the Poznań agglomeration, Poland, conducted in 2015–2021. Its aim is to verify the hypothesis that the use of PPGIS facilitates more meaningful involvement of citizens in spatial planning. As a result of the case study analysis, in-depth interviews with local authorities and officials, and analysis of the planning documents and the role of PPGIS in public participation in decision making, was investigated. It was shown that in both processes there was no direct participation of society in decision making. However, the use of PPGIS, according to local authorities, had implications in the context of the wider process of local governance.
Full article
(This article belongs to the Special Issue GIS for Spatial/Political Participation in the Decision Making Processes of Local Administrations)
Open AccessArticle
Geospatial Analysis of the Non-Surveyed (Estimated) Coastlines in Inoh’s Map, 1821
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ISPRS Int. J. Geo-Inf. 2021, 10(9), 580; https://doi.org/10.3390/ijgi10090580 - 27 Aug 2021
Abstract
The history of modern maps in Japan began with Inoh’s map that was made by surveying the whole of Japan on foot 200 years ago. Inoh’s team investigated coastlines, major roads, and geographical features such as rivers, lakes, temples, forts, village names, etc.
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The history of modern maps in Japan began with Inoh’s map that was made by surveying the whole of Japan on foot 200 years ago. Inoh’s team investigated coastlines, major roads, and geographical features such as rivers, lakes, temples, forts, village names, etc. The survey was successively conducted ten times from 1800 to 1816. Inoh’s map is known as the first scientific map in Japan using a systematic method. However, the actual survey was conducted only for 75% of the coastlines in Japan and the remaining 25% was drawn by Inoh’s estimation (observation). This study investigated how the non-surveyed (estimated) coastlines were distributed in the map and why the actual survey was not conducted in these non-surveyed coastlines. Using GIS, we overlaid the geometrically corrected Inoh’s map (Digital Inoh’s Map Professional Edition) with the current map published by the Geospatial Information Authority (GSI) of Japan for examining the spatial difference. We found that the non-surveyed coastlines were in places where the practice of actual surveying was topographically difficult because of the limited surveying technology of those days. The analytical result shows that 38.6% of the non-surveyed coastlines were cliffs, 25.7% were rocky beaches, and 6.2% were wetlands and tidal lands (including rice fields and tidal flats).
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 AccessArticle
Influential Factor Detection for Tourism on the Qinghai-Tibet Plateau Based on Social Media Data
ISPRS Int. J. Geo-Inf. 2021, 10(9), 579; https://doi.org/10.3390/ijgi10090579 - 27 Aug 2021
Abstract
Tourism is playing an important role in the economic development of the Qinghai-Tibet Plateau (QTP). To better develop tourism in this region, the spatial heterogeneity of influencing factors on tourism needs to be studied. Using the spatial distribution of tourism potential from social
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Tourism is playing an important role in the economic development of the Qinghai-Tibet Plateau (QTP). To better develop tourism in this region, the spatial heterogeneity of influencing factors on tourism needs to be studied. Using the spatial distribution of tourism potential from social media data, this paper analyzes the influencing factors of tourism on the QTP from the perspective of spatial heterogeneity. We extract microblogs related to travel topics connected to the QTP in 2017 from Sina Weibo to capture tourism potential. Then, factors considered from six aspects (tourism resources, amenities, transportation, geography, population, and the economy) are selected, and a geographic detector (Geodetector) is employed to detect the explanatory power of these factors for tourism potential. The results indicate different influential tourism factors in Qinghai and Tibet. In Qinghai, the main factors are hotels, tourist attractions, and road network density, and the explanatory power of the factors mainly comes from eastern and western Qinghai. In Tibet, the main factors are road network density, regional GDP (Gross Domestic Product), and urban land. It is suggested that tourism in the central region of Qinghai can be improved by enhancing the publicity and utilization of tourism resources, and Tibet should enhance tourism resource utilization and improve tourism amenities and infrastructure.
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(This article belongs to the Special Issue Spatio-Temporal Models and Geo-Technologies)
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Open AccessArticle
GIS-Based Spatial and Multi-Criteria Assessment of Riverine Flood Potential: A Case Study of the Nitra River Basin, Slovakia
ISPRS Int. J. Geo-Inf. 2021, 10(9), 578; https://doi.org/10.3390/ijgi10090578 - 27 Aug 2021
Abstract
The aim of this study was to identify the areas with different levels of riverine flood potential (RFP) in the Nitra river basin, Slovakia, using multi-criteria evaluation (MCE)-analytical hierarchical process (AHP), geographic information systems (GIS), and seven flood conditioning factors. The RFP in
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The aim of this study was to identify the areas with different levels of riverine flood potential (RFP) in the Nitra river basin, Slovakia, using multi-criteria evaluation (MCE)-analytical hierarchical process (AHP), geographic information systems (GIS), and seven flood conditioning factors. The RFP in the Nitra river basin had not yet been assessed through MCE-AHP. Therefore, the methodology used can be useful, especially in terms of the preliminary flood risk assessment required by the EU Floods Directive. The results showed that classification techniques of natural breaks (Jenks), equal interval, quantile, and geometric interval classified 32.03%, 29.90%, 41.84%, and 53.52% of the basin, respectively, into high and very high RFP while 87.38%, 87.38%, 96.21%, and 98.73% of flood validation events, respectively, corresponded to high and very high RFP. A single-parameter sensitivity analysis of factor weights was performed in order to derive the effective weights, which were used to calculate the revised riverine flood potential (RRFP). In general, the differences between the RFP and RRFP can be interpreted as an underestimation of the share of high and very high RFP as well as the share of flood events in these classes within the RFP assessment. Therefore, the RRFP is recommended for the assessment of riverine flood potential in the Nitra river basin.
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(This article belongs to the Special Issue GIScience for Risk Management in Big Data Era)
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Open AccessArticle
The Use of Interactive Virtual BIM to Boost Virtual Tourism in Heritage Sites, Historic Jeddah
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ISPRS Int. J. Geo-Inf. 2021, 10(9), 577; https://doi.org/10.3390/ijgi10090577 - 26 Aug 2021
Abstract
Today, moving from a two-dimensional environment to a more advanced interactive three-dimensional (3D) environment in the industries of architecture, engineering, and construction has become one of the most significant topics of interest. This is due to several primary advantages that the 3D environment
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Today, moving from a two-dimensional environment to a more advanced interactive three-dimensional (3D) environment in the industries of architecture, engineering, and construction has become one of the most significant topics of interest. This is due to several primary advantages that the 3D environment can offer. Building information modeling (BIM) can be used as a highly advanced system to present a desired reality in a 3D interactive environment accompanied with 3D reality captured data, such as the point cloud data. As such, these 3D environments can be employed for more advanced uses, such as virtual reality and augmented reality technologies (VR and AR). Recently, BIM has been employed in the context of heritage (known as HBIM, or Heritage Building Information Modeling) for different purposes, such as to provide as-built information with the ability to interact with the end user and uploading information (e.g., historical photographs, documents about materials, or any past restoration projects) into the BIM model. This research will focus on providing an interactive rich virtual 3D model for heritage management. This virtual environment can be employed in cultural tourism and used for the abovementioned purposes. The research project has been adopted in the case of the Zainal Historical House (Bayt Zainal) located in the Historic District of Jeddah, Saudi Arabia. This house is described as one of the significant historical buildings in the historic district. The key aim for selecting this case study is to bridge the gap in architectural knowledge regarding these heritage buildings and their hybrid structural systems (i.e., integration of steel or concrete with the traditional “Mangbi” stone technique).
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(This article belongs to the Special Issue Multi-Resolution Data Fusion for Heritage Building Information Modeling (HBIM) and CityGML Organization)
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Open AccessArticle
Searching for an Optimal Hexagonal Shaped Enumeration Unit Size for Effective Spatial Pattern Recognition in Choropleth Maps
ISPRS Int. J. Geo-Inf. 2021, 10(9), 576; https://doi.org/10.3390/ijgi10090576 - 25 Aug 2021
Abstract
Thoughtful consideration of the enumeration unit size in choropleth map design is important to ensure the correct communication of spatial information. However, the enumeration unit size and its influence on pattern conveying in choropleth maps have not yet been the subject of in-depth
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Thoughtful consideration of the enumeration unit size in choropleth map design is important to ensure the correct communication of spatial information. However, the enumeration unit size and its influence on pattern conveying in choropleth maps have not yet been the subject of in-depth empirical studies. This research aims to address this gap. We focused on the issue concerning whether the ability to recognize spatial patterns on an Equal Area Unit Map is related to the hexagonal enumeration unit size, defined by the number of pixels. The aim is to indicate the range of the enumeration unit sizes, namely, at what point the upper and lower borders of the range where the spatial patterns start, and where the end is visible and recognizable by users. To address this problem, we conducted an empirical study with 488 users. The results show that the enumeration unit size has an impact on the users’ spatial pattern recognition abilities. Choropleth maps with enumeration unit sizes of 26, 52, and 104 pixels were, in the majority, indicated by participants as those most suitable for indicating spatial patterns. This was in contrast to choropleth maps with enumeration unit sizes of 1664 and 3328 pixels, which users indicated as not being useful. However, there were some exceptions to this general finding. Thus, determining the optimal enumeration unit size is a challenging task, and requires further insightful investigations.
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Open AccessArticle
Integration and Analysis of Multi-Modal Geospatial Secondary Data to Inform Management of At-Risk Archaeological Sites
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, , , , , , and
ISPRS Int. J. Geo-Inf. 2021, 10(9), 575; https://doi.org/10.3390/ijgi10090575 - 24 Aug 2021
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
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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.
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(This article belongs to the Special Issue 3D Modeling and GIS for Historical Sites Reconstruction)
Open AccessArticle
Gaussian Process Regression-Based Structural Response Model and Its Application to Regional Damage Assessment
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ISPRS Int. J. Geo-Inf. 2021, 10(9), 574; https://doi.org/10.3390/ijgi10090574 - 24 Aug 2021
Abstract
Seismic activities are serious disasters that induce natural hazards resulting in an incalculable amount of damage to properties and millions of deaths. Typically, seismic risk assessment can be performed by means of structural damage information computed based on the maximum displacement of the
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Seismic activities are serious disasters that induce natural hazards resulting in an incalculable amount of damage to properties and millions of deaths. Typically, seismic risk assessment can be performed by means of structural damage information computed based on the maximum displacement of the structure. In this study, machine learning models based on GPR are developed in order to estimate the maximum displacement of the structures from seismic activities and then used to construct fragility curves as an application. During construction of the models, 13 features of seismic waves are considered, and six wave features are selected to establish the seismic models with the correlation analysis normalizing the variables with the peak ground acceleration. Two models for six-floor and 13-floor buildings are developed, and a sensitivity analysis is performed to identify the relationship between prediction accuracy and sampling size. A 10-fold cross-validation method is used to evaluate the model performance, using the R-squared, root mean squared error, Nash criterion, and mean bias. Results of the six-parameter-based model apparently indicate a similar performance to that of the 13-parameter-based model for the two types of buildings. The model for the six-floor building affords a steadily enhanced performance by increasing the sampling size, while the model for the 13-floor building shows a significantly improved performance with a sampling size of over 200. The results indicate that the heighted structure requires a larger sampling size because it has more degrees of freedom that can influence the model performance. Finally, the proposed models are successfully constructed to estimate the maximum displacement, and applied to obtain fragility curves with various performance levels. Then, the regional seismic damage is assessed in Gyeonjgu city of South Korea as an application of the developed models. The damage assessment with the fragility curve provides the structural response from the seismic activities, which can assist in minimizing damage.
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(This article belongs to the Special Issue Geomatics and Geo-Information in Earthquake Studies)
Open AccessArticle
Towards Resilient Critical Infrastructures: Understanding the Impact of Coastal Flooding on the Fuel Transportation Network in the San Francisco Bay
ISPRS Int. J. Geo-Inf. 2021, 10(9), 573; https://doi.org/10.3390/ijgi10090573 - 24 Aug 2021
Abstract
Sea level rise (SLR) and storm surge inundation are major concerns along the coast of the San Francisco Bay (the Bay Area), impacting both coastal communities and critical infrastructure networks. The oil industry comprises a complex and critical infrastructure network located in the
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Sea level rise (SLR) and storm surge inundation are major concerns along the coast of the San Francisco Bay (the Bay Area), impacting both coastal communities and critical infrastructure networks. The oil industry comprises a complex and critical infrastructure network located in the Bay Area. There is an urgent need to assess consequences and identify risk-based solutions to increase the resilience of this industrial network in the Bay Area to SLR and storm surge. In this study, a comprehensive multi-modal network model representing the fuel supply system was built. A total of 120 coastal flooding scenarios, including four General Circulation Models, two Representative Concentration Pathways, three percentiles of future SLR estimates, and five planning horizons (20 year intervals from 2000 to 2100) were considered. The impact of coastal flooding on fuel transportation networks was studied at two different scales: regional and local. At the regional scale, basic network properties and network efficiency were analyzed across multiple flooding scenarios. At the local scale, cascading effects of individual node disruptions were simulated. Based on this research, smarter and more holistic risk-based adaptation strategies can be established which could lead to a more resilient fuel transportation network system.
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(This article belongs to the Special Issue GIS and Spatial Analysis in Environmental Assessment under Uncertainty)
Open AccessArticle
The Integration of Linguistic and Geospatial Features Using Global Context Embedding for Automated Text Geocoding
ISPRS Int. J. Geo-Inf. 2021, 10(9), 572; https://doi.org/10.3390/ijgi10090572 - 24 Aug 2021
Abstract
Geocoding is an essential procedure in geographical information retrieval to associate place names with coordinates. Due to the inherent ambiguity of place names in natural language and the scarcity of place names in textual data, it is widely recognized that geocoding is challenging.
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Geocoding is an essential procedure in geographical information retrieval to associate place names with coordinates. Due to the inherent ambiguity of place names in natural language and the scarcity of place names in textual data, it is widely recognized that geocoding is challenging. Recent advances in deep learning have promoted the use of the neural network to improve the performance of geocoding. However, most of the existing approaches consider only the local context, e.g., neighboring words in a sentence, as opposed to the global context, e.g., the topic of the document. Lack of global information may have a severe impact on the robustness of the model. To fill the research gap, this paper proposes a novel global context embedding approach to generate linguistic and geospatial features through topic embedding and location embedding, respectively. A deep neural network called LGGeoCoder, which integrates local and global features, is developed to solve the geocoding as a classification problem. The experiments on a Wikipedia place name dataset demonstrate that LGGeoCoder achieves competitive performance compared with state-of-the-art models. Furthermore, the effect of introducing global linguistic and geospatial features in geocoding to alleviate the ambiguity and scarcity problem is discussed.
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(This article belongs to the Special Issue GIS Software and Engineering for Big Data)
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Application-Based COVID-19 Micro-Mobility Solution for Safe and Smart Navigation in Pandemics
ISPRS Int. J. Geo-Inf. 2021, 10(8), 571; https://doi.org/10.3390/ijgi10080571 - 23 Aug 2021
Abstract
Short distance travel and commute being inevitable, safe route planning in pandemics for micro-mobility, i.e., cycling and walking, is extremely important for the safety of oneself and others. Hence, we propose an application-based solution using COVID-19 occurrence data and a multi-criteria route planning
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Short distance travel and commute being inevitable, safe route planning in pandemics for micro-mobility, i.e., cycling and walking, is extremely important for the safety of oneself and others. Hence, we propose an application-based solution using COVID-19 occurrence data and a multi-criteria route planning technique for cyclists and pedestrians. This study aims at objectively determining the routes based on various criteria on COVID-19 safety of a given route while keeping the user away from potential COVID-19 transmission spots. The vulnerable spots include places such as a hospital or medical zones, contained residential areas, and roads with a high connectivity and influx of people. The proposed algorithm returns a multi-criteria route modeled on COVID-19-modified parameters of micro-mobility and betweenness centrality considering COVID-19 avoidance as well as the shortest available safe route for user ease and shortened time of outside environment exposure. We verified our routing algorithm in a part of Delhi, India, by visualizing containment zones and medical establishments. The results with COVID-19 data analysis and route planning suggest a safer route in the context of the coronavirus outbreak as compared to normal navigation and on average route extension is within 8%–12%. Moreover, for further advancement and post-COVID-19 era, we discuss the need for adding open data policy and the spatial system architecture for data usage, as a part of a pandemic strategy. The study contributes new micro-mobility parameters adapted for COVID-19 and policy guidelines based on aggregated contact tracing data analysis maintaining privacy, security, and anonymity.
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(This article belongs to the Special Issue Geo-Information Applications in Active Mobility and Health in Cities)
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Open AccessFeature PaperArticle
Exploring the Planning and Configuration of the Hospital Wayfinding System by Space Syntax: A Case Study of Cheng Ching Hospital, Chung Kang Branch in Taiwan
ISPRS Int. J. Geo-Inf. 2021, 10(8), 570; https://doi.org/10.3390/ijgi10080570 - 23 Aug 2021
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With regard to the outpatient areas of a hospital, the smoothness of the route is now taken into consideration in the process of configuring the wayfinding system. As patients often spend time on ineffective wayfinding processes, and there is limited manpower at hospitals
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With regard to the outpatient areas of a hospital, the smoothness of the route is now taken into consideration in the process of configuring the wayfinding system. As patients often spend time on ineffective wayfinding processes, and there is limited manpower at hospitals and a lack of clarity in the information provided by the wayfinding system, it is difficult to provide effective and timely consultation services for patients. This study was conducted at Cheng Ching Hospital, Chung Kang Branch (CCH/CKB) in Taiwan. This study attempts to investigate the relationships between the wayfinding system of the outpatient areas and the patients’ behaviors in the hospital. Depthmap software based on space syntax is adopted to assist in the route analysis and wayfinding behaviors. It integrates axial mapping analysis and isovist analysis and gives suggestions on the location, format and content of the wayfinding system. The final results of the study show that in the wayfinding task experiment gender has no significant impact on the effect of wayfinding efficiency, while a significant difference is found for age. Older people need more time to complete the wayfinding task, which means that they have poorer performance in wayfinding efficiency. The analysis of the results of space syntax shows that a good wayfinding system should be a symmetric tree-branch structure rather than circular structure in a medical building, that areas where it is easy to become lost should have a clear signage guiding system planning and configuration, and that clear guidance information should be provided to the patients to achieve the goal of saving consultation time and improving the quality of the medical environment.
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Open AccessArticle
Effect of Compositions of MRT System Route Maps on Cognitive Mapping
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ISPRS Int. J. Geo-Inf. 2021, 10(8), 569; https://doi.org/10.3390/ijgi10080569 - 23 Aug 2021
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Route maps, common in public transportation systems, refer to thematic maps drawn according to topological concepts. To simplify complex route information, a transport network is represented using primary graphic elements. First used in 1931 with topological concepts, the octilinear design has influenced the
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Route maps, common in public transportation systems, refer to thematic maps drawn according to topological concepts. To simplify complex route information, a transport network is represented using primary graphic elements. First used in 1931 with topological concepts, the octilinear design has influenced the compositions of traffic route maps to this day. The current study involved cognitive mapping research on a representative route map in Taiwan: the Metro Taipei Route Map. Through two task experiments, this study analyzed users’ cognitive behavior when using the route map and alternative route map representations. The results indicated that the route map composed of all curves resulted in higher user performance than maps using a hybrid system and the conventional octilinear system. The route map based on the hybrid system, which included a route in the shape of a perfect circle, was highly evaluated and subjectively preferred by the users. Thus, the addition of appropriate curves in route maps is beneficial for improving usability, cognitive memory, and subjective evaluation. Finally, adding travel time information to a route map effectively enhances users’ decision-making during route planning.
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Open AccessArticle
Spatiotemporal Dynamic Analysis of A-Level Scenic Spots in Guizhou Province, China
ISPRS Int. J. Geo-Inf. 2021, 10(8), 568; https://doi.org/10.3390/ijgi10080568 - 23 Aug 2021
Abstract
A-level scenic spots are a unique evaluation form of tourist attractions in China, which have an important impact on regional tourism development. Guizhou is a key tourist province in China. In recent years, the number of A-level scenic spots in Guizhou Province has
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A-level scenic spots are a unique evaluation form of tourist attractions in China, which have an important impact on regional tourism development. Guizhou is a key tourist province in China. In recent years, the number of A-level scenic spots in Guizhou Province has been increasing, and the regional tourist economy has improved rapidly. The spatial distribution evolution characteristics and influencing factors of A-level scenic spots in Guizhou Province from 2005 to 2019 were measured using spatial data analysis methods, trend analysis methods, and geographical detector methods. The results elaborated that the number of A-level scenic spots in all counties of Guizhou Province increased, while in the south it developed slowly. From 2005 to 2019, the spatial distribution in A-level scenic spots were characterized by spatial agglomeration. The spatial distribution equilibrium degree of scenic spots in nine cities in Guizhou Province was gradually developed to reach the “relatively average” level. By 2019, the kernel density distribution of A-level scenic spots had formed the “two-axis, multi-core” layout. One axis was located in the north central part of Guizhou Province, and the other axis ran across the central part. The multi-core areas were mainly located in Nanming District, Yunyan District, Honghuagang District, and Xixiu District. From 2005 to 2007, the standard deviation ellipses of the scenic spots distribution changed greatly in direction and size. After 2007, the long-axis direction of the ellipses gradually formed a southwest to northeast direction. We chose elevation, population density, river density, road network density, tourism income, and GDP as factors, to discuss the spatiotemporal evolution of the scenic spots’ distribution with coupling and attribution analysis. It was found that the river, population distribution, road network density, and the A-level scenic spots’ distribution had a relatively high coupling phenomenon. Highway network density and tourist income have a higher influence on A-level tourist resorts distribution. Finally, on account of the spatiotemporal pattern characteristics of A-level scenic spots in Guizhou Province and the detection results of influencing factors, we put forward suggestions to strengthen the development of scenic spots in southern Guizhou Province and upgrade the development model of “point-axis network surface” to the current “two-axis multi-core” pattern of tourism development. This study can explain the current situation of the spatial development of tourist attractions in Guizhou Province, formulate a regulation mechanism of tourism development, and provide a reference for decision-making to boost the high-quality development of the tourist industry.
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(This article belongs to the Special Issue Geo Data Science for Tourism)
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Open AccessArticle
An In-Depth Analysis of Parking Patterns in a Typical Chinese Danwei via Customized Data Collection App
ISPRS Int. J. Geo-Inf. 2021, 10(8), 567; https://doi.org/10.3390/ijgi10080567 - 23 Aug 2021
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The danwei is a distinctive spatial unit in China, as a legacy of the Maoist era. In a danwei, state-owned enterprises supplied a full set of facilities, such that people’s daily activities did not often extend beyond their danweis. However, with the rapid
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The danwei is a distinctive spatial unit in China, as a legacy of the Maoist era. In a danwei, state-owned enterprises supplied a full set of facilities, such that people’s daily activities did not often extend beyond their danweis. However, with the rapid alteration of civic social space in Chinese cities, many employees are no longer tied to a particular danwei. Traditional Chinese danweis have suddenly been faced with a shortage of car-parking space. In the context of the municipal call for danweis to “dismantle the walls and open up for traffic microcirculation”, this study aims to propose a practical approach that analyzes the parking status in a typical danwei. Based on both the parking data collected via a self-designed smartphone application and the survey data collected via questionnaires, the approach analyzes the parking situation in terms of four aspects, including hot parking zones, dynamic parking demand, vehicle parking behaviors, and perceptions of the parking situation. We conducted the experiment on the Information Department Campus of Wuhan University, which is a typical Chinese danwei with complicated surroundings. The results indicate non-negligible issues in the current parking situation, such as vulnerabilities in parking resource management, and a contradiction between supply and demand. Based on the results, we recommend possible strategies to alleviate the tense parking situation and we are confident of the feasibility of opening danwei roads first instead of opening parking facilities, as a response to “open up” the danweis. This study may serve as a representative example of how danweis should analyze their current parking situation and how to respond to the municipality’s suggestions: using modern technology to conduct data collection, perform in-depth and detailed analysis, and synthesize explicit localized policy.
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Refinement Proposals for Geodiversity Assessment—A Case Study in the Bakony–Balaton UNESCO Global Geopark, Hungary
by
and
ISPRS Int. J. Geo-Inf. 2021, 10(8), 566; https://doi.org/10.3390/ijgi10080566 - 22 Aug 2021
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Geodiversity is the variety of natural elements that are excluded from biodiversity, such as: geological, geomorphological, and soil features including their properties, systems, and relationships. Geodiversity assessment measures these features, emphasising the characteristics and physical fragility of the examined areas. In this study,
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Geodiversity is the variety of natural elements that are excluded from biodiversity, such as: geological, geomorphological, and soil features including their properties, systems, and relationships. Geodiversity assessment measures these features, emphasising the characteristics and physical fragility of the examined areas. In this study, a quantitative methodology has been applied in Bakony–Balaton UGGp, Hungary. The Geopark’s area was divided into 2 × 2 km cells in which geodiversity indices were calculated using various data: maps, spatial databases, and elevation models. However, data sources differ significantly in each country: thematic information may not be entirely public or does not have the appropriate scale and complexity. We proposed to use universal data—geomorphons and a watercourse network—derived from Digital Elevation Models (DEMs) to calculate geomorphological diversity. Making a balance between the base materials was also an aim of this research. As sources with different data densities are used, some abiotic elements may be overrepresented, while others seem to have less significance. The normalisation of thematic layers solves this problem: it gives a proportion to each sub-element and creates a balanced index. By applying worldwide accessible digital base data and statistical standardization methods, abiotic nature quantification may open new perspectives in geoconservation.
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Defining a Model for Integrating Indoor and Outdoor Network Data to Support Seamless Navigation Applications
ISPRS Int. J. Geo-Inf. 2021, 10(8), 565; https://doi.org/10.3390/ijgi10080565 - 21 Aug 2021
Abstract
Spaces are continuous realms where human beings freely navigate, such as from indoor to outdoor and optionally to another indoor space. However, currently available data models to represent space for navigation do not entirely reflect this continuity of freedom and movement. Data conversion
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Spaces are continuous realms where human beings freely navigate, such as from indoor to outdoor and optionally to another indoor space. However, currently available data models to represent space for navigation do not entirely reflect this continuity of freedom and movement. Data conversion or complications in implementation hinder current approaches to link indoor space with outdoor space due to the variety of present data models. Furthermore, this representation of indoor–outdoor connection becomes oversimplified during the integration process. Consequently, location-based applications based on these datasets are limited in conveying mobility within these spaces and aiding navigation activity. This paper defines a framework for integrating indoor and outdoor navigable space to enable seamless navigation. This model enables the connection between indoor and outdoor navigation networks. We describe the connections between these networks through spatial relationships, which can be generalized to represent various cases of indoor–outdoor transitional spaces. Using sample datasets, we demonstrate the framework’s potential to provide a seamless connection between indoor and outdoor space in a route analysis experiment.
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(This article belongs to the Special Issue Big Geo-Spatial Data and Advanced 3D Modelling in GIS)
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