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A Review of Bayesian Spatiotemporal Models in Spatial Epidemiology ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-18 Yufeng Wang, Xue Chen, Feng Xue
Spatial epidemiology investigates the patterns and determinants of health outcomes over both space and time. Within this field, Bayesian spatiotemporal models have gained popularity due to their capacity to incorporate spatial and temporal dependencies, uncertainties, and intricate interactions. However, the complexity of modelling and computations associated with Bayesian spatiotemporal models vary
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Spatial Process Analysis of the Evolution of Farmland Landscape in China ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-18 Yan Fu, Qingwen Qi, Lili Jiang, Yapeng Zhao
Accurately identifying the patterns of evolution in farmland plays an important role in optimizing farmland management. The aim of this study is to classify the evolution patterns of farmland in China and explore related mechanisms, providing a reference for constructing a systematic farmland management plan. Using land cover data from five periods in China, nine types of farmland evolution process
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Sustainable and Resilient Land Use Planning: A Multi-Objective Optimization Approach ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-18 Tomé Sicuaio, Pengxiang Zhao, Petter Pilesjo, Andrey Shindyapin, Ali Mansourian
Land use allocation (LUA) is of prime importance for the development of urban sustainability and resilience. Since the process of planning and managing land use requires balancing different conflicting social, economic, and environmental factors, it has become a complex and significant issue in urban planning worldwide. LUA is usually regarded as a spatial multi-objective optimization (MOO) problem
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ConvTEBiLSTM: A Neural Network Fusing Local and Global Trajectory Features for Field-Road Mode Classification ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-14 Cunxiang Bian, Jinqiang Bai, Guanghe Cheng, Fengqi Hao, Xiyuan Zhao
Field-road mode classification (FRMC) that identifies “in-field” and “on-road” categories for Global Navigation Satellite System (GNSS) trajectory points of agricultural machinery containing geographic information is essential for effective crop improvement. Most previous studies utilize local trajectory features (i.e., the relationships between a point and its neighboring points), but they ignore
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Similarity Measurement and Retrieval of Three-Dimensional Voxel Model Based on Symbolic Operator ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-11 Zhenwen He, Xianzhen Liu, Chunfeng Zhang
Three-dimensional voxel models are widely applied in various fields such as 3D imaging, industrial design, and medical imaging. The advancement of 3D modeling techniques and measurement devices has made the generation of three-dimensional models more convenient. The exponential increase in the number of 3D models presents a significant challenge for model retrieval. Currently, these models are numerous
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Evaluation of Qualitative Colour Palettes for Tactile Maps ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-15 Jakub Wabiński, Emilia Śmiechowska-Petrovskij
Much attention is currently being paid to developing universally designed solutions. Tactile maps, designed for people with visual impairments (PVI), require both graphic and tactile content. While many more- or less-official guidelines regarding tactile symbols exist, the subject literature lacks clear guidance on creating legible, highly contrasting graphic symbols for visual perception by those
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Knowledge Graph Representation of Multi-Source Urban Storm Surge Hazard Information Based on Spatio-Temporal Coding and the Hazard Events Ontology Model ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-11 Xinya Lei, Yuewei Wang, Wei Han, Weijing Song
Coastal cities are increasingly vulnerable to urban storm surge hazards and the secondary hazards they cause (e.g., coastal flooding). Accurate representation of the spatio-temporal process of hazard event development is essential for effective emergency response. However, current knowledge graph representations face the challenge of integrating multi-source information with various spatial and temporal
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Simulating Urban Expansion from the Perspective of Spatial Anisotropy and Expansion Neighborhood ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-15 Minghao Liu, Jianxiang Wang, Qingxi Luo, Lingbo Sun, Enming Wang
Exploring spatial anisotropy features and capturing spatial interactions during urban change simulation is of great significance to enhance the effectiveness of dynamic urban modeling and improve simulation accuracy. Addressing the inadequacies of current cellular automaton-based urban expansion models in exploring spatial anisotropy features, overlooking spatial interaction forces, and the ineffective
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Quantifying Urban Linguistic Diversity Related to Rainfall and Flood across China with Social Media Data ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-15 Jiale Qian, Yunyan Du, Fuyuan Liang, Jiawei Yi, Nan Wang, Wenna Tu, Sheng Huang, Tao Pei, Ting Ma
Understanding the public’s diverse linguistic expressions about rainfall and flood provides a basis for flood disaster studies and enhances linguistic and cultural awareness. However, existing research tends to overlook linguistic complexity, potentially leading to bias. In this study, we introduce a novel algorithm capturing rainfall and flood-related expressions, considering the relationship between
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Study on Spatio-Temporal Indexing Model of Geohazard Monitoring Data Based on Data Stream Clustering Algorithm ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-15 Jiahao Li, Weiwei Song, Jianglong Chen, Qunlan Wei, Jinxia Wang
Yunnan Province, residing in the eastern segment of the Qinghai–Tibet Plateau and the western part of the Yunnan–Guizhou Plateau, faces significant challenges due to its intricate geological structures and frequent geohazards. These pose monumental risks to community safety and infrastructure. Unfortunately, conventional spatial indexing methods struggle with the enormous influx of geohazard data,
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Multiscale Urban Functional Zone Recognition Based on Landmark Semantic Constraints ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-15 Xuejing Xie, Yongyang Xu, Bin Feng, Wenjun Wu
The classification of urban functional areas is important for understanding the characteristics of urban areas and optimizing the utilization of urban land resources. Existing related methods have improved accuracy. However, they neglect cognitive differences amongst humans in the different scales of regional functions. Moreover, how to build the correlations of cross-scale characteristics is still
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Best BiCubic Method to Compute the Planimetric Misregistration between Images with Sub-Pixel Accuracy: Application to Digital Elevation Models ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-15 Serge Riazanoff, Axel Corseaux, Clément Albinet, Peter A. Strobl, Carlos López-Vázquez, Peter L. Guth, Takeo Tadono
In recent decades, an important number of regional and global digital elevation models (DEMs) have been released publicly. As a consequence, researchers need to choose between several of these models to perform their studies and to use these DEMs as third-party data to compute derived products (e.g., for orthorectification). However, the comparison of DEMs is not trivial. For most quantitative comparisons
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A Novel and Extensible Remote Sensing Collaboration Platform: Architecture Design and Prototype Implementation ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-08 Wenqi Gao, Ninghua Chen, Jianyu Chen, Bowen Gao, Yaochen Xu, Xuhua Weng, Xinhao Jiang
Geospatial data, especially remote sensing (RS) data, are of significant importance for public services and production activities. Expertise is critical in processing raw data, generating geospatial information, and acquiring domain knowledge and other remote sensing applications. However, existing geospatial service platforms are more oriented towards the professional users in the implementation process
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Distinguishing the Intervalley Plain from the Intermountain Flat for Landform Mapping Using the Sightline Algorithm ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-08 Ge Yan, Guoan Tang, Dingyang Lu, Junfei Ma, Xin Yang, Fayuan Li
The intervalley plain is an important type of landform for mapping, and it has good connectivity for urban construction and development on the Loess Plateau. During the global landform mapping of the Deep-time Digital Earth (DDE) Big Science Program, it was found that slope and relief amplitude hardly distinguished intervalley plains from intermountain flats. This study established a novel descriptive
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Crossing Boundaries: The Ethics of AI and Geographic Information Technologies ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-09 Isaac Oluoch
Over the past two decades, there has been increasing research on the use of artificial intelligence (AI) and geographic information technologies for monitoring and mapping varying phenomena on the Earth’s surface. At the same time, there has been growing attention given to the ethical challenges that these technologies present (both individually and collectively in fields such as critical cartography
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Modeling Shallow Landslide Runout Distance in Eocene Flysch Facies Using Empirical–Statistical Models (Western Black Sea Region of Türkiye) ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-08 Muge Pinar Komu, Hakan Ahmet Nefeslioglu, Candan Gokceoglu
Uncertainties related to runout distances in shallow landslide analyses may not only affect lives but may also result in economic losses. Owing to the increase in shallow landslides, which are especially triggered by heavy rainfall, runout distances have been investigated to decipher whether applications of a functional runout distance are feasible. This paper aims to give insights into the modeling
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Enhancing Maritime Navigational Safety: Ship Trajectory Prediction Using ACoAtt–LSTM and AIS Data ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-08 Mingze Li, Bing Li, Zhigang Qi, Jiashuai Li, Jiawei Wu
Predicting ship trajectories plays a vital role in ensuring navigational safety, preventing collision incidents, and enhancing vessel management efficiency. The integration of advanced machine learning technology for precise trajectory prediction is emerging as a new trend in sophisticated geospatial applications. However, the complexity of the marine environment and data quality issues pose significant
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What Local Environments Drive Opportunities for Social Events? A New Approach Based on Bayesian Modeling in Dallas, Texas, USA ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-05 Yalin Yang, Yanan Wu, May Yuan
In-person social events bring people to places, while people and places influence where and what social events occur. Knowing what people do and where they build social relationships gives insights into the distribution and availability of places for social functions. We developed a Bayesian Network model, integrating points of interest (POIs) and sociodemographic characteristics, to estimate the probabilistic
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Spatial Patterns and the Evolution of Logistics Service Node Facilities in Large Cities—A Case from Wuhan ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-05 Jie Lu, Jing Luo, Lingling Tian, Ye Tian
Logistics services are integral to urban economic activity, and delving into the spatial distribution traits and evolutionary pathways of various kinds of logistics service node facilities (LSNF) is markedly valuable for understanding a city’s functional spatial makeup and refining the spatial layout of logistics services. This study quantitatively and qualitatively analyzes the spatial congregation
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Smart Urban Cadastral Map Enrichment—A Machine Learning Method ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-04 Alireza Hajiheidari, Mahmoud Reza Delavar, Abbas Rajabifard
Enriching and updating maps are among the most important tasks of any urban management organization for informed decision making. Urban cadastral map enrichment is a time-consuming and costly process, which needs an expert’s opinion for quality control. This research proposes a smart framework to enrich a cadastral base map using a more up-to-date map automatically by machine learning algorithms. The
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Hourly PM2.5 Concentration Prediction Based on Empirical Mode Decomposition and Geographically Weighted Neural Network ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-03-02 Yan Chen, Chunchun Hu
Accurate prediction of fine particulate matter (PM2.5) concentration is crucial for improving environmental conditions and effectively controlling air pollution. However, some existing studies could ignore the nonlinearity and spatial correlation of time series data observed from stations, and it is difficult to avoid the redundancy between features during feature selection. To further improve the
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Bayesian Shared Component Spatial Modeling for Assessing the Shared and Age Group-Specific Mental Health Disorder Risk of Young and Old Age Groups: A Case Study of Toronto Neighborhoods, Canada ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-28 Abu Yousuf Md Abdullah, Jane Law
Mental health disorder risks of young and old age groups hold considerable importance for understanding present and future risk burdens. However, assessing mental health risks is significantly constrained by the influence of shared and age group-specific spatial processes and risk factors. Therefore, this study employed Bayesian shared component spatial modeling (BSCSM) to analyze mental health disorder
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Method for the Identification and Classification of Zones with Vehicular Congestion ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-28 Gary Reyes, Roberto Tolozano-Benites, Laura Lanzarini, César Estrebou, Aurelio F. Bariviera, Julio Barzola-Monteses
Persistently, urban regions grapple with the ongoing challenge of vehicular traffic, a predicament fueled by the incessant expansion of the population and the rise in the number of vehicles on the roads. The recurring challenge of vehicular congestion casts a negative influence on urban mobility, thereby diminishing the overall quality of life of residents. It is hypothesized that a dynamic clustering
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Exploring Forest Fire Dynamics: Fire Danger Mapping in Antalya Region, Türkiye ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-28 Hatice Atalay, Adalet Dervisoglu, Ayse Filiz Sunar
The Mediterranean region experiences the annual destruction of thousands of hectares due to climatic conditions. This study examines forest fires in Türkiye’s Antalya region, a Mediterranean high-risk area, from 2000 to 2023, analyzing 26 fires that each damaged over 50 hectares. Fire danger maps created from fire weather indexes (FWI) indicated that 85.7% of the analyzed fire areas were categorized
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Identifying Spatial Determinants of Rice Yields in Main Producing Areas of China Using Geospatial Machine Learning ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-28 Qingyan Wang, Longzhi Sun, Xuan Yang
Rice yield is essential to global food security under increasingly frequent and severe climate change events. Spatial analysis of rice yields becomes more critical for regional action to ensure yields and reduce climate impacts. However, the understanding of the spatially varied geographical, climate, soil, and environmental factors of rice yields needs to be improved, leading to potentially biased
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Superblock Design and Evaluation by a Microscopic Door-to-Door Simulation Approach ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-29 Ngoc An Nguyen, Joerg Schweizer, Federico Rupi, Sofia Palese, Leonardo Posati
The present study contributes to narrowing down the research gap in modeling individual door-to-door trips in a superblock scenario and in evaluating the respective impacts in terms of travel times, modal shifts, traffic performance, and environmental benefits. The methods used are a multiple-criteria approach to identify the superblocks and a large-scale, multi-model, activity-based microscopic simulation
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A Knowledge-Guided Intelligent Analysis Method of Geographic Digital Twin Models: A Case Study on the Diagnosis of Geometric Deformation in Tunnel Excavation Profiles ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-29 Ce Liang, Jun Zhu, Jinbin Zhang, Qing Zhu, Jingyi Lu, Jianbo Lai, Jianlin Wu
It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual description, which has low analysis efficiency. This paper proposes a knowledge-guided
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Multi-Scale Non-Local Spatio-Temporal Information Fusion Networks for Multi-Step Traffic Flow Forecasting ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-27 Shuai Lu, Haibo Chen, Yilong Teng
Traffic flow prediction is a crucial research area in traffic management. Accurately predicting traffic flow in each area of the city over the long term can enable city managers to make informed decisions regarding the allocation of urban transportation resources in the future. The existing traffic flow prediction models either give insufficient attention to the interactions of long-lasting spatio-temporal
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Enhanced Seamless Indoor–Outdoor Tracking Using Time Series of GNSS Positioning Errors ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-27 Eduard Angelats, Alban Gorreja, Pedro F. Espín-López, M. Eulàlia Parés, Eva Savina Malinverni, Roberto Pierdicca
The seamless integration of indoor and outdoor positioning has gained considerable attention due to its practical implications in various fields. This paper presents an innovative approach aimed at detecting and delineating outdoor, indoor, and transition areas using a time series analysis of Global Navigation Satellite System (GNSS) error statistics. By leveraging this contextual understanding, the
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Functional Method for Analyzing Open-Space Ratios around Individual Buildings and Its Implementation with GIS ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-25 Kayo Okabe, Atsuyuki Okabe
An open-space ratio is often used as a first basic metric to examine the distribution of open space in urbanized areas. Originally, the open-space ratio was defined as the ratio of the area of open space (unbuilt area) to the area of its building site. In recent years, residents have become more concerned with the open-space ratios in the broader neighborhoods of their individual buildings than with
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Cartographic Metadata for Improving Accessibility and Facilitating Knowledge Extraction and Validation in Planetary Mapping Based on Remote-Sensing Observations ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-24 Stephan van Gasselt, Andrea Naß
The field of planetary mapping and cartography builds almost exclusively on remote-sensing data and can be defined by three distinct concepts: systematic imaging as performed through spacecraft surveying, reference mapping as performed through the compilation of reference maps, i.e., regional to global image and topographic maps, and thematic mapping, which aims at abstracting and contextualizing spatial
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Spatial and Temporal Changes in Social Vulnerability to Natural Hazards in Mexico ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-22 José Francisco León-Cruz, David Romero, Hugo Ignacio Rodríguez-García
The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020, and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made
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Framing VRRSability Relationships among Vulnerability, Risk, Resilience, and Sustainability for Improving Geo-Information Evaluations within Geodesign Decision Support ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-23 Timothy Nyerges, John A. Gallo, Keith M. Reynolds, Steven D. Prager, Philip J. Murphy, Wenwen Li
Improving geo-information decision evaluation is an important part of geospatial decision support research, particularly when considering vulnerability, risk, resilience, and sustainability (V-R-R-S) of urban land–water systems (ULWSs). Previous research enumerated a collection of V-R-R-S conceptual component commonalties and differences resulting in a synthesis concept called VRRSability. As a single
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Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-23 Yuncheng Jiang, Bin Ouyang, Zhigang Yan
Clarifying the spatiotemporal changes in the supply and demand of water-related ecosystem services (WESs) can provide comprehensive support information for ecological governance decisions. However, the spatial mismatch between the supply and demand of WESs is often overlooked, resulting in a lack of targeted decision-making. At the grid scale, while preserving both natural and social attributes, this
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Supporting Asset Management with GIS and Business Intelligence Technologies: The Case Study of the University of Turin ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-21 Paola Gasbarri, Daniele Accardo, Elisa Cacciaguerra, Silvia Meschini, Lavinia Chiara Tagliabue
Despite the promising outcomes achieved over time in Asset Management, data accessibility, correlation, analysis, and visualization still represent challenges. The integration, readability, and interpretation of heterogeneous information by different stakeholders is a further concern, especially at the urban scale, where spatial data integration is required to correlate virtual information with the
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Reconstruction of 3D Information of Buildings from Single-View Images Based on Shadow Information ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-20 Zhixin Li, Song Ji, Dazhao Fan, Zhen Yan, Fengyi Wang, Ren Wang
Accurate building geometry information is crucial for urban planning in constrained spaces, fueling the growing demand for large-scale, high-precision 3D city modeling. Traditional methods like oblique photogrammetry and LiDAR prove time consuming and expensive for low-cost 3D reconstruction of expansive urban scenes. Addressing this challenge, our study proposes a novel approach to leveraging single-view
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A Spatial Regression Model for Predicting Prices of Short-Term Rentals in Athens, Greece ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-20 Polixeni Iliopoulou, Vassilios Krassanakis, Loukas-Moysis Misthos, Christina Theodoridi
Short-term house rentals constitute a growing component of tourist accommodation in several countries and the determination of factors affecting rents is an important consideration in relevant studies. Short-term rentals have shown increasing trends in the city of Athens, Greece; however, this activity has not been adequately studied. In this paper, spatial data of Airbnb rentals in Athens are analyzed
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Learning Universal Trajectory Representation via a Siamese Geography-Aware Transformer ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-20 Chenhao Wu, Longgang Xiang, Libiao Chen, Qingcen Zhong, Xiongwei Wu
With the development of location-based services and data collection equipment, the volume of trajectory data has been growing at a phenomenal rate. Raw trajectory data come in the form of sequences of “coordinate-time-attribute” triplets, which require complicated manual processing before they can be used in data mining algorithms. Current works have started to explore the emerging deep representation
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Measuring Villagers’ Perceptions of Changes in the Landscape Values of Traditional Villages ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-18 Mingxuan Li, Yu Yan, Ziyi Ying, Long Zhou
This study aims to analyze the perceptions and driving factors behind villagers’ changing perceptions of landscape values in the context of drastic landscape changes in traditional Chinese villages. Empirical evidence emphasizes the interplay between local residents’ values and the local policy framework. This study establishes a method to capture the landscape values and preferences of rural community
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Comparing Characteristics of the Urban Thermal Environment Based on the Local Climate Zone in Three Chinese Metropolises ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-19 Riguga Su, Chaobin Yang, Zhibo Xu, Tingwen Luo, Lilong Yang, Lifeng Liu, Chao Wang
Urban landscape has important effects on urban climate, and the local climate zone (LCZ) framework has been widely applied in related studies. However, few studies have compared the relative contributions of LCZ on the urban thermal environment across different cities. Therefore, Beijing, Shanghai, and Shenzhen in China were selected to conduct a comparative study to explore the relationship between
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Secant Cylinders Are Evil—A Case Study on the Standard Lines of the Universal Transverse Mercator and Universal Polar Stereographic Projections ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-13 Kerkovits Krisztián
The literature usually calls downscaled versions of basic conformal map projections “secant”, referring to conceptual developable map surfaces that intersect the reference frame. However, recent studies pointed out on the examples of various mappings of the sphere that this model may lead to incorrect conclusions. In this study, we examine the paradigm of secant surfaces for two popular map projections
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A Spatiotemporal Hierarchical Analysis Method for Urban Traffic Congestion Optimization Based on Calculation of Road Carrying Capacity in Spatial Grids ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-15 Dong Jiang, Wenji Zhao, Yanhui Wang, Biyu Wan
Traffic congestion is a globally widespread problem that causes significant economic losses, delays, and environmental impacts. Monitoring traffic conditions and analyzing congestion factors are the first, challenging steps in optimizing traffic congestion, one of the main causes of which is regional spatiotemporal imbalance. In this article, we propose an improved spatiotemporal hierarchical analysis
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Methodological Innovations for Establishing Cemetery Spatial Databases—A UAV-Based Workflow Helping Small Communities ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-14 Márton Pál, Edina Hajdú
Various modern large-scale mapping techniques have already been introduced in earth sciences, cadastral mapping, and the agricultural sector. These methodologies often use remotely sensed data to compile various analogue or digital cartographic products as well as spatial databases. However, the mapping of cemeteries and standards for establishing a spatial database for them have rarely been published
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Study on LOS to Vertical Deformation Conversion Model on Embankment Slopes Using Multi-Satellite SAR Interferometry ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-14 Jie Liu, Tao Li, Sijie Ma, Qiang Shan, Weiping Jiang
Slant range geometry plays a crucial role in interpreting synthetic aperture radar (SAR) observations, especially in converting line-of-sight (LOS) surface deformations to actual vertical subsidence. This paper proposes a new conversion model to retrieve vertical settlements of the embankment slopes using the geometrical parameters of the dam and the SAR sensor. The simulation results highlight the
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Online Decision Support Infrastructures for Integrating Spatial Planning and Flood Risk Management Policies ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-11 Jing Ran, Zorica Nedovic-Budic
Accessible geospatial data are crucial for informed decision making and policy development in urban planning, environmental governance, and hazard mitigation. Spatial data infrastructures (SDIs) have been implemented to facilitate such data access. However, with the rapid advancements in geospatial software and modelling tools, it is important to re-visit the theoretical discussion about the different
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Historical Heritage Maintenance via Scan-to-BIM Approaches: A Case Study of the Lisbon Agricultural Exhibition Pavilion ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-11 Gustavo Rocha, Luís Mateus, Victor Ferreira
Building Information Modeling (BIM) has emerged as a revolutionary tool in the domain of architectural conservation and documentation. When combined with terrestrial 3D laser scanning, it presents a powerful method to capture and represent the intricate details and nuances of historic structures. Such buildings, with their unique architectural lineage, often exude a geometric complexity unparalleled
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Evaluation of the Accessibility of Children’s Spaces at the Community Scale: The Case Study of Hangzhou ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-12 Yuanzheng Cui, Qiuting Wang, Guixiang Zha, Yunxiao Dang, Xuejun Duan, Lei Wang, Ming Luo
The safety, inclusivity, accessibility, and green communities emphasized in the United Nations’ Sustainable Development Goals (SDGs) play a vital role in the establishment of child-friendly cities. The governments are actively promoting the development of sustainable, child-friendly cities that prioritize people’s needs and aim to enhance the well-being of residents, from children to families. However
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Generating Spatial Knowledge Graphs with 2D Indoor Floorplan Data: A Case Study on the Jeonju Express Bus Terminal ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-09 Hanme Jang, Kiyun Yu, Jiyoung Kim
With the boom in online information, knowledge graphs like Freebase, Wikidata, and YAGO have emerged, thanks to the introduction of the RDF (Resource Description Framework). As RDF data grew, more and more spatial data was incorporated into it. While we have a lot of 2D data for outdoor spaces, mapping indoor spaces in 3D is challenging because it is expensive and time-consuming. In our research, we
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A Spatial Optimization Model for Delineating Metropolitan Areas ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-06 Gusiyuan Wang, Wangshu Mu
A metropolitan area comprises a collection of cities and counties bound by strong socioeconomic ties. Despite the pivotal role that metropolitan areas play in regional economics, their delineation remains a challenging task for researchers and urban planners. Current threshold-based delineation methods select counties based on their connection strength with prespecified core counties. Such an approach
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Cultural Itineraries Generated by Smart Data on the Web ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-03 Cosmo Capodiferro, Massimo De Maria, Mauro Mazzei, Matteo Spreafico, Oleg V. Bik, Armando L. Palma, Anna V. Solovyeva
The development of storage standards for databases of different natures and origins makes it possible to aggregate and interact with different data sources in order to obtain and show complex and thematic information to the end user. This article aims to analyze some possibilities opened up by new applications and hypothesize their possible developments. With this work, using the currently available
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A Time-Identified R-Tree: A Workload-Controllable Dynamic Spatio-Temporal Index Scheme for Streaming Processing ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-04 Weichen Peng, Luo Chen, Xue Ouyang, Wei Xiong
Many kinds of spatio-temporal data in our daily lives, such as the trajectory data of moving objects, stream natively. Streaming systems exhibit significant advantages in processing streaming data due to their distributed architecture, high throughput, and real-time performance. The use of streaming processing techniques for spatio-temporal data applications is a promising research direction. However
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Study on Spatio-Temporal Patterns of Commuting under Adverse Weather Events: Case Study of Typhoon In-Fa ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-05 Tao Ji, Xian Huang, Jinliang Shao, Yunqiang Zhu, Shejun Deng, Shijun Yu, Huajun Liao
This study focuses on the main urban area of Yangzhou City and conducts a quantitative comparative analysis of traffic accessibility during normal weather and extreme precipitation conditions (typhoon) based on GPS trajectories of buses. From both temporal and spatial dimensions, it comprehensively examines the impact of extreme precipitation on bus travel speed, travel time, and the commuting range
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A Novel Visual Narrative Framework for Tourist Map Design Based on Local Chronicles: A Case Study of the Songshan Scenic Area ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-02 Wenjie Zhen, Shifang Huang, Zhihui Tian, Xiaoyue Yang
Tourist maps provide tourists with destination information that reflects their unique characteristics and cultural connotations and play an important role in attracting tourists and serving marketing purposes. However, existing designs of tourist maps often ignore the importance of cultural resource selection and the relationship between maps and structural linguistics, thereby affecting the narrative
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Multidimensional Spatial Vitality Automated Monitoring Method for Public Open Spaces Based on Computer Vision Technology: Case Study of Nanjing’s Daxing Palace Square ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-03 Xinyu Hu, Ximing Shen, Yi Shi, Chen Li, Wei Zhu
Assessing the vitality of public open spaces is critical in urban planning and provides insights for optimizing residents’ lives. However, prior research has fragmented study scopes and lacks fine-grained behavioral data segmentation capabilities and diverse vitality dimension assessments. We utilized computer vision technology to collect fine-grained behavioral data and proposed an automated spatial
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Measuring the Potential and Realized (or Revealed) Spatial Access from Places of Residence and Work to Food Outlets in Rural Communities of Québec, Canada ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-01 Eric Robitaille, Gabrielle Durette, Marianne Dubé, Olivier Arbour, Marie-Claude Paquette
This study aims to bridge the gap between the potential and realized spatial access to food outlets in rural areas of Québec, Canada. By assessing both aspects, this research aims to provide a comprehensive understanding of the challenges faced by rural communities in accessing food resources and the effectiveness of existing interventions in addressing these challenges. A mixed methods approach was
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How Information and Communications Technology Affects the Micro-Location Choices of Stores on On-Demand Food Delivery Platforms: Evidence from Xinjiekou’s Central Business District in Nanjing ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-02 Xinyu Hu, Gutao Zhang, Yi Shi, Peng Yu
The digitization of consumption, led by information and communications technology (ICT), has reshaped the urban commercial spatial structure (UCSS) of restaurants and retailers. However, the impacts of ICT on UCSS and location selection remain unclear. In this study, based on on-demand food delivery data and real-time traffic data, we used two types of machine learning algorithms, random forest regression
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EventGeoScout: Fostering Citizen Empowerment and Augmenting Data Quality through Collaborative Geographic Information Governance and Optimization ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-02-02 Jose A. Montenegro, Antonio Muñoz
In this manuscript, we present EventGeoScout, an innovative framework for collaborative geographic information management, tailored to meet the needs of the dynamically changing landscape of geographic data integration and quality enhancement. EventGeoScout enables the seamless fusion of open data from different sources and provides users with the tools to refine and improve data quality. A distinctive
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Measuring Efficiency and Accuracy in Locating Symbols on Mobile Maps Using Eye Tracking ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-01-30 Wojciech Rymarkiewicz, Paweł Cybulski, Tymoteusz Horbiński
This study investigated the impact of smartphone usage frequency on the effectiveness and accuracy of symbol location in a variety of spatial contexts on mobile maps using eye-tracking technology while utilizing the example of Mapy.cz. The scanning speed and symbol detection were also considered. The use of mobile applications for navigation is discussed, emphasizing their popularity and convenience
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A Semantic Partition Algorithm Based on Improved K-Means Clustering for Large-Scale Indoor Areas ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-01-27 Kegong Shi, Jinjin Yan, Jinquan Yang
Reasonable semantic partition of indoor areas can improve space utilization, optimize property management, and enhance safety and convenience. Existing algorithms for such partitions have drawbacks, such as the inability to consider semantics, slow convergence, and sensitivity to outliers. These limitations make it difficult to have partition schemes that can match the real-world observations. To obtain
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Dynamic Graph Convolutional Network-Based Prediction of the Urban Grid-Level Taxi Demand–Supply Imbalance Using GPS Trajectories ISPRS Int. J. Geo-Inf. (IF 3.4) Pub Date : 2024-01-24 Haiqiang Yang, Zihan Li
The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. The application of Graph Convolutional Networks (GCNs) in traffic forecasting has inspired the development of a spatial–temporal model for grid-level prediction