ISPRS International Journal of Geo-Information

16 pages, 4290 KiB

Open AccessSystematic Review

GIS-Based Multi-Criteria Evaluation (MCE) Methods for Aquaculture Site Selection: A Systematic Review and Meta-Analysis

by Sanae Chentouf, Boutaina Sebbah, El Houssine Bahousse, Miriam Wahbi and Mustapha Maâtouk

ISPRS Int. J. Geo-Inf. 2023, 12(10), 439; https://doi.org/10.3390/ijgi12100439 - 23 Oct 2023

Viewed by 1764

With the growing demand for aquatic products, aquaculture has become a prominent means of meeting this demand. However, the selection of suitable sites for aquaculture remains a key factor in the success of any aquaculture operation. While various methods exist for site selection, [...] Read more.

With the growing demand for aquatic products, aquaculture has become a prominent means of meeting this demand. However, the selection of suitable sites for aquaculture remains a key factor in the success of any aquaculture operation. While various methods exist for site selection, geographic information system (GIS)-based multi-criteria evaluation (MCE) methods have emerged as the most widely utilized approach to identifying potential aquaculture sites. Following the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA), this paper presents a systematic review and meta-analysis of GIS-based MCE methods used in aquaculture sites selection. The objective of this study is to offer a comprehensive overview of existing research in this field and develop a general model for selecting sites for fish and shellfish aquaculture. The main findings indicate a growing number of studies utilizing GIS-based MCE in aquaculture site selection in recent years, with Asia being the leading continent in terms of publications in this domain. Among the journals publishing in this field, the Aquaculture journal stands out as the top publisher. Using consistent criteria across the reviewed studies, two models have been generated, each consisting of four sub-models: water quality, soil quality, infrastructure, and socioeconomic factors; and topography, environment, and physical parameters. These models can aid future researchers and assist decision-makers in identifying optimal locations for aquaculture development. Full article

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20 pages, 2566 KiB

Open AccessArticle

Research on Time-Aware Group Query Method with Exclusion Keywords

by Liping Zhang, Jing Li and Song Li

ISPRS Int. J. Geo-Inf. 2023, 12(10), 438; https://doi.org/10.3390/ijgi12100438 - 23 Oct 2023

Cited by 1 | Viewed by 1105

Abstract

Aiming at the problem that the existing spatial keyword group query problem did not consider the query requirements with exclusion keywords and time attributes, a time-aware group query problem with exclusion keywords (TEGSKQ) is proposed for the first time. To solve this problem [...] Read more.

Aiming at the problem that the existing spatial keyword group query problem did not consider the query requirements with exclusion keywords and time attributes, a time-aware group query problem with exclusion keywords (TEGSKQ) is proposed for the first time. To solve this problem effectively, this paper proposes a query method based on the EKTIR-Tree index and dominating group (EKTDG). This method first proposes the EKTIR-tree index, which incorporates Huffman coding and integrates Bloom filters to deal with excluded keywords in order to improve the hit rate of keyword queries, significantly improving the query efficiency and reducing the storage occupancy. Then, the Candidate algorithm is proposed based on the EKTIR-tree index to filter out the spatial–textual objects that meet the query’s keywords and time requirements, narrowing the search space for subsequent queries on a large scale. To address the problem of the low efficiency of existing algorithms based on a spatial distance query, a distance-dominating group is defined and a pruning algorithm based on a spatial distance-dominating group is proposed, which is a refining process of query results and greatly improves the search efficiency of the query. Theoretical and experimental studies show that the proposed method can better handle group queries with exclusion keywords based on time awareness. Full article

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17 pages, 4027 KiB

Open AccessArticle

Measuring the Influence of Multiscale Geographic Space on the Heterogeneity of Crime Distribution

by Zhanjun He, Zhipeng Wang, Yu Gu and Xiaoya An

ISPRS Int. J. Geo-Inf. 2023, 12(10), 437; https://doi.org/10.3390/ijgi12100437 - 23 Oct 2023

Viewed by 1444

Abstract

Urban crimes are not homogeneously distributed but exhibit spatial heterogeneity across a range of spatial scales. Meanwhile, while geographic space shapes human activities, it is also closely related to multiscale characteristics. Previous studies have explored the influence of underlying geographic space on crime [...] Read more.

Urban crimes are not homogeneously distributed but exhibit spatial heterogeneity across a range of spatial scales. Meanwhile, while geographic space shapes human activities, it is also closely related to multiscale characteristics. Previous studies have explored the influence of underlying geographic space on crime occurrence from the mechanistic perspective, treating geographic space as a collection of points or lines, neglecting the multiscale nature of the spatial heterogeneity of crime and underlying geographic space. Therefore, inspired by the recent concept of “living structure” in geographic information science, this study applied a multiscale analysis method to explore the association between underlying geographic space and crime distribution. Firstly, the multiscale heterogeneity is described while simultaneously considering both the statistical and geometrical characteristics. Then, the spatial association rule mining approach is adopted to quantitatively measure the association between crime occurrence and geographic space at multiple scales. Finally, the effectiveness of the proposed methods is evaluated by crime incidents in the city of Philadelphia. Experimental results show that crime heterogeneity is indeed closely related with the spatial scales. It is also proven that the influence of underlying geographic space on crime heterogeneity varies with the spatial scales. This study may enrich the methodology in crime pattern and crime explanation analysis, and it provides useful insights for effective crime prevention. Full article

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32 pages, 10787 KiB

Open AccessArticle

Climate Change, Forest Fires, and Territorial Dynamics in the Amazon Rainforest: An Integrated Analysis for Mitigation Strategies

by Nathalia Celis, Alejandro Casallas, Ellie Anne Lopez-Barrera, Martina Felician, Massimo De Marchi and Salvatore E. Pappalardo

ISPRS Int. J. Geo-Inf. 2023, 12(10), 436; https://doi.org/10.3390/ijgi12100436 - 23 Oct 2023

Cited by 2 | Viewed by 2912

Abstract

Recent times have witnessed wildfires causing harm to both ecological communities and urban–rural regions, underscoring the necessity to comprehend wildfire triggers and assess measures for mitigation. This research hones in on Cartagena del Chairá, diving into the interplay between meteorological conditions and land [...] Read more.

Recent times have witnessed wildfires causing harm to both ecological communities and urban–rural regions, underscoring the necessity to comprehend wildfire triggers and assess measures for mitigation. This research hones in on Cartagena del Chairá, diving into the interplay between meteorological conditions and land cover/use that cultivates a conducive environment for wildfires. Meteorologically, the prevalence of wildfires is concentrated during boreal winter, characterized by warm and dry air, strong winds, and negligible precipitation. Additionally, wildfires gravitate toward river-adjacent locales housing agriculture-linked shrubs, notably in the northern part of the zone, where a confluence of land attributes and meteorological factors synergize to promote fire incidents. Employing climate scenarios, we deduced that elevated temperature and reduced humidity augment wildfire susceptibility, while wind speed and precipitation discourage their propagation across most scenarios. The trajectory toward a warmer climate could instigate fire-friendly conditions in boreal summer, indicating the potential for year-round fire susceptibility. Subsequently, via machine-learning-driven sensitivity analysis, we discerned that among the scrutinized socio-economic variables, GINI, low educational attainment, and displacement by armed groups wield the most substantial influence on wildfire occurrence. Ultimately, these findings converge to shape proposed wildfire mitigation strategies that amalgamate existing practices with enhancements or supplementary approaches. Full article

(This article belongs to the Special Issue Human-Induced Disaster and Conflict Analysis, Prediction, and Prevention by Geospatial Analytics and Information Systems)

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28 pages, 10082 KiB

Open AccessArticle

Spatiotemporal Pattern of Carbon Compensation Potential and Network Association in Urban Agglomerations in the Yellow River Basin

by Haihong Song, Yifan Li, Liyuan Gu, Jingnan Tang and Xin Zhang

ISPRS Int. J. Geo-Inf. 2023, 12(10), 435; https://doi.org/10.3390/ijgi12100435 - 23 Oct 2023

Viewed by 1367

Abstract

The Yellow River Basin is an important energy base and economic belt in China, but its water resources are scarce, its ecology is fragile, and the task of achieving the goal of carbon peak and carbon neutrality is arduous. Carbon compensation potential can [...] Read more.

The Yellow River Basin is an important energy base and economic belt in China, but its water resources are scarce, its ecology is fragile, and the task of achieving the goal of carbon peak and carbon neutrality is arduous. Carbon compensation potential can also be used to study the path to achieving carbon neutrality, which can clarify the potential of one region’s carbon sink surplus to be compensated to the other areas. Still, there needs to be more research on the carbon compensation potential of the Yellow River Basin. Therefore, this study calculated the carbon compensation potential using the β convergence test and parameter comparison method. With the help of spatial measurement tools such as GIS, GeoDa, Stata, and social network analysis methods, the spatiotemporal pattern and network structure of the carbon compensation potential in the Yellow River Basin were studied from the perspective of urban agglomeration. The results demonstrate the following: (1) The overall carbon compensation rate of the YRB showed a downward trend from 2005 to 2019, falling by 0.94, and the specific pattern was “high in the northwest and low in the southeast”. The spatial distribution is roughly spread along the east–west axis, and the distribution axis and the center of gravity keep shifting to the northwest. It also showed a weak divergence and a bifurcation trend. (2) The carbon compensation rate in the YRB passed the spatial correlation and β convergence tests, demonstrating the existence of spatial correlation and a “catch-up effect” among cities. (3) The overall distribution pattern of the carbon compensation potential in the YRB is a “low in the west and high in the east” pattern, and its value increased by 8.86% during the sampled period. (4) The network correlation of carbon compensation potential in the YRB has been significantly enhanced, with the downstream region being more connected than the upstream region. (5) The Shandong Peninsula Urban Agglomeration has the largest network center, followed by the Central Plains Urban Agglomeration, and the Ningxia along the Yellow River Urban Agglomeration has the fewest linked conduction paths. According to the research results, accurate and efficient planning and development suggestions are proposed for urban agglomeration in the Yellow River Basin. Full article

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28 pages, 8474 KiB

Open AccessArticle

ExhibitXplorer: Enabling Personalized Content Delivery in Museums Using Contextual Geofencing and Artificial Intelligence

by Rosen Ivanov

ISPRS Int. J. Geo-Inf. 2023, 12(10), 434; https://doi.org/10.3390/ijgi12100434 - 22 Oct 2023

Viewed by 2169

Abstract

In recent years, there has been an increasing demand for personalized experiences in various domains, including the cultural and educational sectors. Museums, as custodians of art, history, and scientific knowledge, are seeking innovative ways to engage their visitors and provide tailored content that [...] Read more.

In recent years, there has been an increasing demand for personalized experiences in various domains, including the cultural and educational sectors. Museums, as custodians of art, history, and scientific knowledge, are seeking innovative ways to engage their visitors and provide tailored content that enhances their understanding and appreciation of the exhibits. This article presents ExhibitXplorer, a distributed architecture service that leverages geofencing, artificial intelligence, and microservices to enable personalized content delivery in museums. By combining implicit and explicit segmentation of museum visitors and utilizing the GPT API for content generation, ExhibitXplorer offers a dynamic experience to different visitor segments, including researchers, students, casual visitors, and children. The system utilizes push notifications triggered by visitor location changes, allowing seamless delivery of personalized information both indoors and outdoors. Tests were conducted to evaluate the user experience of visitors to an outdoor ethnographic museum. The results showed that 55% of the test participants were satisfied and 45% very satisfied with the way personalized content was delivered. Full article

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25 pages, 11815 KiB

Open AccessArticle

Revealing the Spatio-Temporal Heterogeneity of the Association between the Built Environment and Urban Vitality in Shenzhen

by Zhitao Li and Guanwei Zhao

ISPRS Int. J. Geo-Inf. 2023, 12(10), 433; https://doi.org/10.3390/ijgi12100433 - 22 Oct 2023

Cited by 1 | Viewed by 1607

Abstract

Sensing urban vitality is a useful method for understanding urban development. However, the spatio-temporal characteristics of the association between the built environment and urban vitality in Shenzhen, the youngest mega-city in China, have not yet been explored. In this paper, we examined the [...] Read more.

Sensing urban vitality is a useful method for understanding urban development. However, the spatio-temporal characteristics of the association between the built environment and urban vitality in Shenzhen, the youngest mega-city in China, have not yet been explored. In this paper, we examined the effects of built environment indicators on urban vitality by using spatial regression models and multi-source geospatial data. The main research findings were as follows. Firstly, urban vitality displayed a consistent high–low pattern during both weekdays and weekends. Differences in the distribution of urban vitality with time between weekdays and weekends were more significant. Secondly, the effects of various built environment indicators on urban vitality exhibited significant temporal disparities. Within a day, population density, building density, bus station density, and distance to metro stations all exhibited positive effects, while distance to the central business district (CBD) exhibited negative effects, with pronounced diurnal differences. Moreover, the effects of road network density and functional mix on urban vitality were both positive and negative throughout the day. Thirdly, besides population density and building density, road network density, functional mix, bus stop density, and distance from metro stations exhibited positive and negative disparities within the study area. Overall, distance to the CBD had a negative effect on urban vitality. This concludes that planning for urban vitality should consider the spatio-temporal heterogeneity of the association between the built environment and urban vitality. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 840 KiB

Open AccessArticle

An Efficient and Accurate Convolution-Based Similarity Measure for Uncertain Trajectories

by Guanyao Li, Xingdong Deng, Jianmin Xu, Yang Liu, Ji Zhang, Simin Xiong and Feng Gao

ISPRS Int. J. Geo-Inf. 2023, 12(10), 432; https://doi.org/10.3390/ijgi12100432 - 22 Oct 2023

Viewed by 1268

Abstract

With the rapid development of localization techniques and the prevalence of mobile devices, massive amounts of trajectory data have been generated, playing essential roles in areas of user analytics, smart transportation, and public safety. Measuring trajectory similarity is one of the fundamental tasks [...] Read more.

With the rapid development of localization techniques and the prevalence of mobile devices, massive amounts of trajectory data have been generated, playing essential roles in areas of user analytics, smart transportation, and public safety. Measuring trajectory similarity is one of the fundamental tasks in trajectory analytics. Although considerable research has been conducted on trajectory similarity, the majority of existing approaches measure the similarity between two trajectories by calculating the distance between aligned locations, leading to challenges related to uncertain trajectories (e.g., low and heterogeneous data sampling rates, as well as location noise). To address these challenges, we propose Contra, a convolution-based similarity measure designed specifically for uncertain trajectories. The main focus of Contra is to identify the similarity of trajectory shapes while disregarding the time/order relevance of each record within the trajectory. To this end, it leverages a series of convolution and pooling operations to extract high-level geo-information from trajectories, and subsequently compares their similarities based on these extracted features. Moreover, we introduce efficient trajectory index strategies to enhance the computational efficiency of our proposed measure. We conduct comprehensive experiments on two trajectory datasets to evaluate the performance of our proposed approach. The experiments on both datasets show the effectiveness and efficiency of our approach. Specifically, the mean rank of Contra is 3 times better than the state-of-the-art approaches, and the precision of Contra surpasses baseline approaches by 20–40%. Full article

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27 pages, 6787 KiB

Open AccessArticle

A Hybrid POI Recommendation System Combining Link Analysis and Collaborative Filtering Based on Various Visiting Behaviors

by Sumet Darapisut, Komate Amphawan, Nutthanon Leelathakul and Sunisa Rimcharoen

ISPRS Int. J. Geo-Inf. 2023, 12(10), 431; https://doi.org/10.3390/ijgi12100431 - 22 Oct 2023

Cited by 1 | Viewed by 1540

Abstract

Location-based recommender systems (LBRSs) have exhibited significant potential in providing personalized recommendations based on the user’s geographic location and contextual factors such as time, personal preference, and location categories. However, several challenges (such as data sparsity, the cold-start problem, and tedium problem) need [...] Read more.

Location-based recommender systems (LBRSs) have exhibited significant potential in providing personalized recommendations based on the user’s geographic location and contextual factors such as time, personal preference, and location categories. However, several challenges (such as data sparsity, the cold-start problem, and tedium problem) need to be addressed to develop more effective LBRSs. In this paper, we propose a novel POI recommendation system, called LACF-Rec3, which employs a hybrid approach of link analysis (HITS-3) and collaborative filtering (CF-3) based on three visiting behaviors: frequency, variety, and repetition. HITS-3 identifies distinctive POIs based on user- and POI-visit patterns, ranks them accordingly, and recommends them to cold-start users. For existing users, CF-3 utilizes collaborative filtering based on their previous check-in history and POI distinctive aspects. Our experimental results conducted on a Foursquare dataset demonstrate that LACF-Rec3 outperforms prior methods in terms of recommendation accuracy, ranking precision, and matching ratio. In addition, LACF-Rec3 effectively solves the challenges of data sparsity, the cold-start issue, and tedium problems for cold-start and existing users. These findings highlight the potential of LACF-Rec3 as a promising solution to the challenges encountered by LBRS. Full article

(This article belongs to the Topic Artificial Intelligence in Navigation)

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11 pages, 4943 KiB

Open AccessArticle

Describing the Urban Jungle: A Multicriteria Urbanization Index for the Amazon

by Pablo Cabrera-Barona, Denise Albán and Gustavo Durán

ISPRS Int. J. Geo-Inf. 2023, 12(10), 430; https://doi.org/10.3390/ijgi12100430 - 17 Oct 2023

Viewed by 1749

Abstract

The Amazon has a population that is largely urban. However, research is limited regarding representations and analysis of the urban Amazon. This article represents and describes Amazonian urban areas by applying a multicriteria urbanization index. Using the Ecuadorian Amazon as a case study, [...] Read more.

The Amazon has a population that is largely urban. However, research is limited regarding representations and analysis of the urban Amazon. This article represents and describes Amazonian urban areas by applying a multicriteria urbanization index. Using the Ecuadorian Amazon as a case study, we constructed this index considering spatial indicators of fractal dimension, number of paved streets, urban luminosity, population density, and Euclidean distances from each urban patch to the closest deforested area, to the closest oil pollution point, and to the closest mining pollution point. The multicriteria urbanization index was classified in five classes (degrees) of urbanization: very low, low, medium, high, and very high levels of urbanization. Most of the urban areas have a low degree of urbanization; notwithstanding, there are areas with a medium degree of urbanization encompassing consolidated cities and suburbs, with a high potential for extension in the future. There are also areas of high and very high urbanization related to the oil industry, including cities which have a high impact on the territorial system of the Amazon. This investigation serves as an introduction to multidimensional spatial and quantitative analyses of the urban Amazon. We suggest monitoring the urban advance in the Amazon using the index developed in this investigation, to support better territorial planning in this region of the world having high strategical importance. Full article

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17 pages, 2586 KiB

Open AccessArticle

A Hybrid Discrete Artificial Bee Colony Algorithm Based on Label Similarity for Solving Point-Feature Label Placement Problem

by Wen Cao, Jiaqi Xu, Yong Zhang, Siqi Zhao, Chu Xu and Xiaofeng Wu

ISPRS Int. J. Geo-Inf. 2023, 12(10), 429; https://doi.org/10.3390/ijgi12100429 - 17 Oct 2023

Cited by 1 | Viewed by 1331

Abstract

The artificial bee colony algorithm (ABC) is a promising metaheuristic algorithm for continuous optimization problems, but it performs poorly in solving discrete problems. To address this issue, this paper proposes a hybrid discrete artificial bee colony (HDABC) algorithm based on label similarity for [...] Read more.

The artificial bee colony algorithm (ABC) is a promising metaheuristic algorithm for continuous optimization problems, but it performs poorly in solving discrete problems. To address this issue, this paper proposes a hybrid discrete artificial bee colony (HDABC) algorithm based on label similarity for the point-feature label placement (PFLP) problem. Firstly, to better adapt to PFLP, we have modified the update mechanism for employed bees and onlooker bees. Employed bees learn the label position of the better individuals, while onlooker bees perform dynamic probability searches using two neighborhood operators. Additionally, the onlooker bees’ selection method selects the most promising solutions based on label similarity, which improves the algorithm’s search capabilities. Finally, the Metropolis acceptance strategy is replaced by the original greedy acceptance strategy to avoid the premature convergence problem. Systematic experiments are conducted to verify the effectiveness of the neighborhood solution generation method, the selection operation based on label similarity, and the Metropolis acceptance strategy in this paper. In addition, experimental comparisons were made at different instances and label densities. The experimental results show that the algorithm proposed in this paper is better or more competitive with the compared algorithm. Full article

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17 pages, 11199 KiB

Open AccessArticle

The Study of Regional Innovation Network Structure: Evidence from the Yangtze River Delta Urban Agglomeration

by Jie Chen, Liang Jiang, Ye Tian and Jing Luo

ISPRS Int. J. Geo-Inf. 2023, 12(10), 428; https://doi.org/10.3390/ijgi12100428 - 17 Oct 2023

Viewed by 1428

Abstract

As a driving force for regional development, innovation holds an increasing position in regional competitiveness, and a reasonable and coordinated innovation network structure can promote high-quality regional development. Utilizing the modified gravity model and social network analysis method, an innovation network composed of [...] Read more.

As a driving force for regional development, innovation holds an increasing position in regional competitiveness, and a reasonable and coordinated innovation network structure can promote high-quality regional development. Utilizing the modified gravity model and social network analysis method, an innovation network composed of 27 cities in the Yangtze River Delta urban agglomeration from 2010 to 2021 was studied. The following conclusions were founded: (1) The innovation development level in the Yangtze River Delta urban agglomeration was constantly improving, and the innovation development level generally showed a spatial pattern of high in the southeast and low in the northwest. (2) The intensity and density of innovation network correlations in urban agglomerations were increasing, and the centrality of network nodes had an obvious hierarchical characteristic. The innovation network had a significant core–periphery spatial structure, with core cities that had higher centrality, such as Shanghai, Nanjing, and Hangzhou, playing the role of “intermediaries” and “bridges”, while cities with lower centrality, such as Anhui and cities in northern Jiangsu, generally played the role of “periphery actors” in the network. (3) The spatial correlation network of innovation of the Yangtze River Delta urban agglomeration could be divided into four blocks, namely, main benefit, broker, two-way spillover, and net spillover, and the spillover effect among them had obvious gradient characteristics of hierarchy. Full article

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18 pages, 5667 KiB

Open AccessArticle

Automated Generation of Room Usage Semantics from Point Cloud Data

by Guoray Cai and Yimu Pan

ISPRS Int. J. Geo-Inf. 2023, 12(10), 427; https://doi.org/10.3390/ijgi12100427 - 17 Oct 2023

Viewed by 1382

Abstract

Room usage semantics in models of large indoor environments such as public buildings and business complex are critical in many practical applications, such as health and safety regulations, compliance, and emergency response. Existing models such as IndoorGML have very limited semantic information at [...] Read more.

Room usage semantics in models of large indoor environments such as public buildings and business complex are critical in many practical applications, such as health and safety regulations, compliance, and emergency response. Existing models such as IndoorGML have very limited semantic information at room level, and it remains difficult to capture semantic knowledge of rooms in an efficient way. In this paper, we formulate the task of generating rooms usage semantics as a special case of room classification problems. Although methods for room classification tasks have been developed in the field of social robotics studies and indoor maps, they do not deal with room usage and occupancy aspects of semantics, and they ignore the value of furniture objects in understanding room usage. We propose a method for generating room usage semantics based on the spatial configuration of room objects (e.g., furniture, walls, windows, doors). This method uses deep learning architecture to support a room usage classifier that can learn spatial configuration features directly from semantically labelled point cloud (SLPC) data that represent room scenes with furniture objects in place. We experimentally assessed the capacity of our method in classifying rooms in office buildings using the Stanford 3D (S3DIS) dataset. The results showed that our method was able to achieve an overall accuracy of 91% on top-level room categories (e.g., offices, conference rooms, lounges, storage) and above 97% accuracy in recognizing offices and conference rooms. We further show that our classifier can distinguish fine-grained categories of of offices and conference rooms such as shared offices, single-occupancy offices, large conference rooms, and small conference rooms, with comparable intelligence to human coders. In general, our method performs better on rooms with a richer variety of objects than on rooms with few or no furniture objects. Full article

(This article belongs to the Special Issue Unlocking the Power of Geospatial Data: Semantic Information Extraction, Ontology Engineering, and Deep Learning for Knowledge Discovery)

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19 pages, 3278 KiB

Open AccessArticle

Extraction of Urban Road Boundary Points from Mobile Laser Scanning Data Based on Cuboid Voxel

by Jingxue Wang, Xiao Dong and Guangwei Liu

ISPRS Int. J. Geo-Inf. 2023, 12(10), 426; https://doi.org/10.3390/ijgi12100426 - 16 Oct 2023

Viewed by 1332

Abstract

The accuracy of point cloud processing results is greatly dependent on the determination of the voxel size and shape during the point cloud voxelization process. Previous studies predominantly set voxel sizes based on point cloud density or the size of ground objects. Voxels [...] Read more.

The accuracy of point cloud processing results is greatly dependent on the determination of the voxel size and shape during the point cloud voxelization process. Previous studies predominantly set voxel sizes based on point cloud density or the size of ground objects. Voxels are mostly considered square in shape by default. However, conventional square voxels are not applicable to all surfaces. This study proposes a method of using cuboid voxels to extract urban road boundary points using curb points as road boundary points. In comparison with conventional cubic voxels, cuboid voxels reduce the probability of mixed voxels at the road curb, highlight two geometric features of road curb voxels (i.e., normal vector and distribution dimension), and improve the accuracy of road curb point extraction. In this study, ground points were obtained using cloth simulation filtering. First, the cuboid-based voxelization of ground points was performed. Then, taking the voxel as a unit, two geometric features, namely, the normal vector of the voxel and the linear dimension of the point distribution in the voxel, were calculated. According to these geometric features, the voxels that met the conditions were regarded as candidate road curb voxels, and the points in them as candidate road curb points. Afterward, filtering was applied using the intensity value to eliminate the bottom points of fences, street trees, and other ground objects in the candidate road curb points. Finally, noise points were eliminated according to the clustering results of the density based spatial clustering of applications with noise (DBSCAN) algorithm. In this study, point cloud data obtained by the SSW vehicle-mounted mobile mapping system and three-point cloud datasets in the IQmulus & TerraMobilita competition dataset were used to experimentally extract road curbs. Results showed that this method could effectively extract road curb points as the precision of the four groups of data results was over 90% and the quality coefficient reached over 75%. Full article

(This article belongs to the Topic Urban Sensing Technologies)

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18 pages, 5031 KiB

Open AccessArticle

The Analyses of Land Use and Prevention in High-Density Main Urban Areas under the Constraint of Karst Ground Subsidence: Study of Wuhan City, China

by Lin Gao, Yan Shi, Yang Qiu, Chuanming Ma and Aiguo Zhou

ISPRS Int. J. Geo-Inf. 2023, 12(10), 425; https://doi.org/10.3390/ijgi12100425 - 16 Oct 2023

Viewed by 1210

Abstract

The development and utilization of land in the main urban area have significantly impacted the stability of the regional geological environment through various means, such as increased load and subway construction, primarily manifested as rock and soil mass deformation leading to geological hazards. [...] Read more.

The development and utilization of land in the main urban area have significantly impacted the stability of the regional geological environment through various means, such as increased load and subway construction, primarily manifested as rock and soil mass deformation leading to geological hazards. Therefore, it is worth exploring how to reduce the occurrence of karst ground subsidence (KGS) through reasonable land development and control measures in the main urban areas with large-scale developments of buried karst formations. This study focuses on the main urban area of Wuhan City. An evaluation model for KGS was constructed using the analytic hierarchy process (AHP) and comprehensive index evaluation method by analyzing the geological conditions that affect KGS. The susceptibility zoning of KGS was obtained with GIS spatial analysis technology. The results show that the susceptible areas can be divided into extreme, high, medium, and weak susceptibility, accounting for 4.93%, 15.30%, 33.21%, and 46.56%, respectively, which are consistent with the distribution density of past KSGs. Furthermore, by selecting the subway construction as a human activity type, it indirectly discusses the influence of land development intensity on KGS. The results show that past KSGs are mainly concentrated in areas with high engineering construction density and significant land development intensity. Based on the above, strategies for regional land development and prevention and control of KGSs are proposed. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 15347 KiB

Open AccessArticle

A Knowledge-Guided Fusion Visualisation Method of Digital Twin Scenes for Mountain Highways

by Ranran Tang, Jun Zhu, Ying Ren, Yongzhe Ding, Jianlin Wu, Yukun Guo and Yakun Xie

ISPRS Int. J. Geo-Inf. 2023, 12(10), 424; https://doi.org/10.3390/ijgi12100424 - 15 Oct 2023

Cited by 2 | Viewed by 1772

Abstract

Informatization is an important trend in the field of mountain highway management, and the digital twin is an effective way to promote mountain highway information management due to the complex and diverse terrain of mountainous areas, the high complexity of mountainous road scene [...] Read more.

Informatization is an important trend in the field of mountain highway management, and the digital twin is an effective way to promote mountain highway information management due to the complex and diverse terrain of mountainous areas, the high complexity of mountainous road scene modeling and low visualisation efficiency. It is challenging to construct the digital twin scenarios efficiently for mountain highways. To solve this problem, this article proposes a knowledge-guided fusion expression method for digital twin scenes of mountain highways. First, we explore the expression features and interrelationships of mountain highway scenes to establish the knowledge graph of mountain highway scenes. Second, by utilizing scene knowledge to construct spatial semantic constraint rules, we achieve efficient fusion modeling of basic geographic scenes and dynamic and static ancillary facilities, thereby reducing the complexity of scene modeling. Finally, a multi-level visualisation publishing scheme is established to improve the efficiency of scene visualisation. On this basis, a prototype system is developed, and case experimental analysis is conducted to validate the research. The results of the experiment indicate that the suggested method can accomplish the fusion modelling of mountain highway scenes through knowledge guidance and semantic constraints. Moreover, the construction time for the model fusion is less than 5.7 ms; meanwhile, the dynamic drawing efficiency of the scene is maintained above 60 FPS. Thus, the construction of twinned scenes can be achieved quickly and efficiently, the effect of replicating reality with virtuality is accomplished, and the informatisation management capacity of mountain highways is enhanced. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 11348 KiB

Open AccessArticle

The Seasonal Migrants Spatially Affect the Park Green Space Accessibility and Equity under Different Travel Modes: Evidence from Sanya, China

by Wentong Yang, Yeqing Cheng, Chunru Xu and Jinping Zhang

ISPRS Int. J. Geo-Inf. 2023, 12(10), 423; https://doi.org/10.3390/ijgi12100423 - 14 Oct 2023

Viewed by 1497

Abstract

The influx of seasonal migrants has a significant impact on public services in destination places and may reshape the spatial accessibility and equity patterns of park green space (PGS). However, the two-step floating catchment area (2SFCA) method and its extended forms neglect discrepancies [...] Read more.

The influx of seasonal migrants has a significant impact on public services in destination places and may reshape the spatial accessibility and equity patterns of park green space (PGS). However, the two-step floating catchment area (2SFCA) method and its extended forms neglect discrepancies between the travel behaviors of seasonal migrants and native residents and thus fail to delineate variations in PGS accessibility and equity in areas with seasonal migrants. To avoid this issue, this study drew on the case of Sanya, a city with large numbers of Houniao, who are primarily retirees leading seasonal migration between the north and the south of China. A multi-group, multi-mode Gaussian-based 2SFCA method was also proposed to evaluate the PGS accessibility and equity before and after the Houniao influx. The method considered the changes in the COVID-19 restrictions from a refined perspective, with fine-scale residential areas being the research units and travel time requested from the web map application programming interface. The results showed that most residential areas were found to have relatively low PGS accessibility and equity levels, except for those in the south-central and southwestern urban areas of Sanya. Both the Houniao influx and lifted COVID-19 restrictions affected the spatial patterns of PGS accessibility and equity. PGS accessibility and equity were decreased by the Houniao influx, whereas walking and public transport within a few residential areas outside Houniao gathering spots improved. This study can serve as a basis for the reasonable planning of PGS and other public services in cities receiving seasonal migrants, such as Sanya. Full article

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20 pages, 51538 KiB

Open AccessArticle

Deep-Learning-Based Annotation Extraction Method for Chinese Scanned Maps

by Xun Rao, Jiasheng Wang, Wenjing Ran, Mengzhu Sun and Zhe Zhao

ISPRS Int. J. Geo-Inf. 2023, 12(10), 422; https://doi.org/10.3390/ijgi12100422 - 14 Oct 2023

Viewed by 1325

Abstract

One of a map’s fundamental elements is its annotations, and extracting these annotations is an important step in enabling machine intelligence to understand scanned map data. Due to the complexity of the characters and lines, extracting annotations from scanned Chinese maps is difficult, [...] Read more.

One of a map’s fundamental elements is its annotations, and extracting these annotations is an important step in enabling machine intelligence to understand scanned map data. Due to the complexity of the characters and lines, extracting annotations from scanned Chinese maps is difficult, and there is currently little research in this area. A deep-learning-based framework for extracting annotations from scanned Chinese maps is presented in the paper. Improved the EAST annotation detection model and CRNN annotation recognition model based on transfer learning make up the two primary parts of this framework. Several sets of the comparative tests for annotation detection and recognition were created in order to assess the efficacy of this method for extracting annotations from scanned Chinese maps. The experimental findings show the following: (i) The suggested annotation detection approach in this study revealed precision, recall, and h-mean values of 0.8990, 0.8389, and 0.8635, respectively. These measures demonstrate improvements over the currently popular models of −0.0354 to 0.0907, 0.0131 to 0.2735, and 0.0467 to 0.1919, respectively. (ii) The proposed annotation recognition method in this study revealed precision, recall, and h-mean values of 0.9320, 0.8956, and 0.9134, respectively. These measurements demonstrate improvements over the currently popular models of 0.0294 to 0.1049, 0.0498 to 0.1975, and 0.0402 to 0.1582, respectively. Full article

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22 pages, 8236 KiB

Open AccessArticle

Enhancing the Understanding of the EU Gender Equality Index through Spatiotemporal Visualizations

by Laya Targa, Silvia Rueda, Jose Vicente Riera, Sergio Casas and Cristina Portalés

ISPRS Int. J. Geo-Inf. 2023, 12(10), 421; https://doi.org/10.3390/ijgi12100421 - 13 Oct 2023

Viewed by 1701

Abstract

The Gender Equality Index allows analyzing and measuring the progress of gender equality in the EU and, therefore, the relation between men and women in different domains, such as Health, Work or Money. Even though the European Institute for Gender Equality has created [...] Read more.

The Gender Equality Index allows analyzing and measuring the progress of gender equality in the EU and, therefore, the relation between men and women in different domains, such as Health, Work or Money. Even though the European Institute for Gender Equality has created some visualizations that are useful to look at the data, this website does not manage to make graphs that allow for observing the spatiotemporal variable. This article enhances the understanding of the index with spatiotemporal visualizations, such as cartograms, heatmaps and choropleth maps, and some strategies focusing on analyzing the evolution of the countries over the years in an open-access environment. The results show how the application created may be used as an addition to the EIGE website. Full article

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22 pages, 10762 KiB

Open AccessArticle

A Self-Attention Model for Next Location Prediction Based on Semantic Mining

by Eric Hsueh-Chan Lu and You-Ru Lin

ISPRS Int. J. Geo-Inf. 2023, 12(10), 420; https://doi.org/10.3390/ijgi12100420 - 13 Oct 2023

Viewed by 1458

Abstract

With the rise in the Internet of Things (IOT), mobile devices and Location-Based Social Network (LBSN), abundant trajectory data have made research on location prediction more popular. The check-in data shared through LBSN hide information related to life patterns, and obtaining this information [...] Read more.

With the rise in the Internet of Things (IOT), mobile devices and Location-Based Social Network (LBSN), abundant trajectory data have made research on location prediction more popular. The check-in data shared through LBSN hide information related to life patterns, and obtaining this information is helpful for location prediction. However, the trajectory data recorded by mobile devices are different from check-in data that have semantic information. In order to obtain the user’s semantic, relevant studies match the stay point to the nearest Point of Interest (POI), but location error may lead to wrong semantic matching. Therefore, we propose a Self-Attention model for next location prediction based on semantic mining to predict the next location. When calculating the semantic feature of a stay point, the first step is to search for the k-nearest POI, and then use the reciprocal of the distance from the stay point to the k-nearest POI and the number of categories as weights. Finally, we use the probability to express the semantic without losing other important semantic information. Furthermore, this research, combined with sequential pattern mining, can result in richer semantic features. In order to better perceive the trajectory, temporal features learn the periodicity of time series by the sine function. In terms of location features, we build a directed weighted graph and regard the frequency of users visiting locations as the weight, so the location features are rich in contextual information. We then adopt the Self-Attention model to capture long-term dependencies in long trajectory sequences. Experiments in Geolife show that the semantic matching of this study improved by 45.78% in TOP@1 compared with the closest distance search for POI. Compared with the baseline, the model proposed in this study improved by 2.5% in TOP@1. Full article

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20 pages, 5688 KiB

Open AccessArticle

Identifying Urban Park Events through Computer Vision-Assisted Categorization of Publicly-Available Imagery

by Yizhou Tan, Wenjing Li, Da Chen and Waishan Qiu

ISPRS Int. J. Geo-Inf. 2023, 12(10), 419; https://doi.org/10.3390/ijgi12100419 - 13 Oct 2023

Cited by 1 | Viewed by 1711

Abstract

Understanding park events and their categorization offers pivotal insights into urban parks and their integral roles in cities. The objective of this study is to explore the efficacy of Convolutional Neural Networks (CNNs) in categorizing park events through images. Utilizing image and event [...] Read more.

Understanding park events and their categorization offers pivotal insights into urban parks and their integral roles in cities. The objective of this study is to explore the efficacy of Convolutional Neural Networks (CNNs) in categorizing park events through images. Utilizing image and event category data from the New York City Parks Events Listing database, we trained a CNN model with the aim of enhancing the efficiency of park event categorization. While this study focuses on New York City, the approach and findings have the potential to offer valuable insights for urban planners examining park event distributions in different cities. Different CNN models were tuned to complete this multi-label classification task, and their performances were compared. Preliminary results underscore the efficacy of deep learning in automating the event classification process, revealing the multifaceted activities within urban green spaces. The CNN showcased proficiency in discerning various event nuances, emphasizing the diverse recreational and cultural offerings of urban parks. Such categorization has potential applications in urban planning, aiding decision-making processes related to resource distribution, event coordination, and infrastructure enhancements tailored to specific park activities. Full article

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18 pages, 4636 KiB

Open AccessArticle

Estimation of a Fundamental Diagram with Heterogeneous Data Sources: Experimentation in the City of Santander

by Borja Alonso, Giuseppe Musolino, Corrado Rindone and Antonino Vitetta

ISPRS Int. J. Geo-Inf. 2023, 12(10), 418; https://doi.org/10.3390/ijgi12100418 - 12 Oct 2023

Cited by 2 | Viewed by 1340

Abstract

The reduction of urban congestion represents one of the main challenges for increasing sustainability. This implies the necessity to increase our knowledge of urban mobility and traffic. The fundamental diagram (FD) is a possible tool for analyzing the traffic conditions on an urban [...] Read more.

The reduction of urban congestion represents one of the main challenges for increasing sustainability. This implies the necessity to increase our knowledge of urban mobility and traffic. The fundamental diagram (FD) is a possible tool for analyzing the traffic conditions on an urban road link. FD is commonly associated with the links of a transport network, but it has recently been extended to the whole transport network and named the network macroscopic fundamental diagram (NMFD). When used at the link or network level, the FD is important for supporting the simulation, design, planning, and control of the transport system. Recently, floating car data (FCD), which are based on vehicles’ trajectories using GPS, are able to provide the trajectories of a number of vehicles circulating on the network. The objective of this paper is to integrate FCD with traffic data obtained from traditional loop-detector technology for building FDs. Its research contribution concerns the proposal of a methodology for the extraction of speed data from taxi FCD, corresponding to a specific link section, and the calibration of FDs from FCD and loop detector data. The methodology has been applied to a real case in the city of Santander. The first results presented are encouraging, supporting the paper’s thesis that FCD can be integrated with data obtained from loop detectors to build FD. Full article

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26 pages, 10199 KiB

Open AccessArticle

Deformation of High Rise Cooling Tower through Projection of Coordinates Resulted from Terrestrial Laser Scanner Observations onto a Vertical Plane

by Ashraf A. A. Beshr, Ali M. Basha, Samir A. El-Madany and Fathi Abd El-Azeem

ISPRS Int. J. Geo-Inf. 2023, 12(10), 417; https://doi.org/10.3390/ijgi12100417 - 11 Oct 2023

Viewed by 1229

Abstract

The appearance and development of new construction materials, technology and accurate geodetic instruments have led to the necessity of their inevitable use in the health monitoring, maintenance, and restoration of civil structures and special structures such as high-rise cooling towers. This paper presents [...] Read more.

The appearance and development of new construction materials, technology and accurate geodetic instruments have led to the necessity of their inevitable use in the health monitoring, maintenance, and restoration of civil structures and special structures such as high-rise cooling towers. This paper presents an accurate practical and analytical method for determining the structural deformation and axis inclination of high rise cooling towers using terrestrial laser scanner (TLS) observations through the projection of tower surface points coordinates on a vertical plane. Four cooling towers in El-Mahla El-Kubra city, Egypt are observed and studied. Two of them with height 56 m, and the others were 36 m height. The studied four towers have different cross-section diameters along the tower height. Each tower has a cone shape with a curved wall. The equation of the tower wall is determined using TLS observations and least squares adjustment techniques. The equations of cone projection with a curved wall are derived and presented in this paper. From TLS observations, the radii and accuracy of each 2 m tower height are determined with center coordinates, and then the inclination of the tower axis is calculated and drawn. From the results of TLS observations, data processing, and analysis using the suggested techniques, it is deduced that there is a deformation in tower walls with small values. The specified technique for observations collection and TLS data analysis through projection on a vertical plane is significant and valuable for determining the structural deformation of circular high rise buildings and towers. From the results, there are obvious deformation values in some cooling towers, so maintenance work must be included. The towers also must be checked and monitored several times at brief intervals. Full article

(This article belongs to the Topic Advances in Earth Observation and Geosciences)

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20 pages, 4926 KiB

Open AccessArticle

CatBoost-Based Automatic Classification Study of River Network

by Di Wang and Haizhong Qian

ISPRS Int. J. Geo-Inf. 2023, 12(10), 416; https://doi.org/10.3390/ijgi12100416 - 11 Oct 2023

Cited by 1 | Viewed by 1463

Abstract

Existing research on automatic river network classification methods has difficulty scientifically quantifying and determining feature threshold settings and evaluating weights when calculating multi-indicator features of the local and overall structures of river reaches. In order to further improve the accuracy of river network [...] Read more.

Existing research on automatic river network classification methods has difficulty scientifically quantifying and determining feature threshold settings and evaluating weights when calculating multi-indicator features of the local and overall structures of river reaches. In order to further improve the accuracy of river network classification and evaluate the feature weight, this paper proposes an automatic grading method for river networks based on ensemble learning in CatBoost. First, the graded river network based on expert knowledge is taken as the case; with the support of the existing case results, a total of eight features from the semantic, geometric, and topological aspects of the river network were selected for calculation. Second, the classification model, obtained through learning and training, was used to calculate the classification results of the main stream and tributaries of the river reach to be classified. Furthermore, the main stream river reaches were connected, and the main stream rivers at different levels were hierarchized to achieve river network classification. Finally, the Shapley Additive explanation (SHAP) framework for interpreting machine learning models was introduced to test the influence of feature terms on the classification results from the global and local aspects, so as to improve the interpretability and transparency of the model. Performance evaluation can determine the advantages and disadvantages of the classifier, improve the classification effect and practicability of the classifier, and improve the accuracy and reliability of river network classification. The experiment demonstrates that the proposed method achieves expert-level imitation and has higher accuracy for identifying the main stream and tributaries of river networks. Compared with other classification algorithms, the accuracy was improved by 0.85–5.94%, the precision was improved by 1.82–9.84%, and the F1_Score was improved by 0.8–5.74%. In this paper, CatBoost is used for river network classification for the first time, and SHAP is used to explain the influence of characteristics, which improves the accuracy of river network classification and enhances the interpretability of the classification method. By constructing a reasonable hierarchy, a better grading effect can be achieved, and the intelligence level of automatic grading of river networks can be further improved. Full article

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19 pages, 1271 KiB

Open AccessReview

Question Classification for Intelligent Question Answering: A Comprehensive Survey

by Hao Sun, Shu Wang, Yunqiang Zhu, Wen Yuan and Zhiqiang Zou

ISPRS Int. J. Geo-Inf. 2023, 12(10), 415; https://doi.org/10.3390/ijgi12100415 - 10 Oct 2023

Viewed by 1595

Abstract

In the era of GeoAI, Geospatial Intelligent Question Answering (GeoIQA) represents the ultimate pursuit for everyone. Even generative AI systems like ChatGPT-4 struggle to handle complex GeoIQA. GeoIQA is domain complex IQA, which aims at understanding and answering questions accurately. The core of [...] Read more.

In the era of GeoAI, Geospatial Intelligent Question Answering (GeoIQA) represents the ultimate pursuit for everyone. Even generative AI systems like ChatGPT-4 struggle to handle complex GeoIQA. GeoIQA is domain complex IQA, which aims at understanding and answering questions accurately. The core of IQA is the Question Classification (QC), which mainly contains four types: content-based, template-based, calculation-based and method-based classification. These IQA_QC frameworks, however, struggle to be compatible and integrate with each other, which may be the bottleneck restricting the substantial improvement of IQA performance. To address this problem, this paper reviewed recent advances on IQA with the focus on solving question classification and proposed a comprehensive IQA_QC framework for understanding user query intention more accurately. By introducing the basic idea of the IQA mechanism, a three-level question classification framework consisting of essence, form and implementation is put forward which could cover the complexity and diversity of geographical questions. In addition, the proposed IQA_QC framework revealed that there are still significant deficiencies in the IQA evaluation metrics in the aspect of broader dimensions, which led to low answer performance, functional performance and systematic performance. Through the comparisons, we find that the proposed IQA_QC framework can fully integrate and surpass the existing classification. Although our proposed classification can be further expanded and improved, we firmly believe that this comprehensive IQA_QC framework can effectively help researchers in both semantic parsing and question querying processes. Furthermore, the IQA_QC framework can also provide a systematic question-and-answer pair/library categorization system for AIGCs, such as GPT-4. In conclusion, whether it is explicit GeoAI or implicit GeoAI, the IQA_QC can play a pioneering role in providing question-and-answer types in the future. Full article

(This article belongs to the Special Issue Innovative GIS Models and Approaches for Large Environmental and Urban Applications in the Age of AI)

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18 pages, 4124 KiB

Open AccessArticle

The Spatiotemporal Pattern Evolution and Driving Force of Tourism Information Flow in the Chengdu–Chongqing City Cluster

by Yang Zhao, Zegen Wang, Zhiwei Yong, Peng Xu, Qian Wang and Xuemei Du

ISPRS Int. J. Geo-Inf. 2023, 12(10), 414; https://doi.org/10.3390/ijgi12100414 - 10 Oct 2023

Cited by 1 | Viewed by 1418

Abstract

In recent years, the tourism industry has developed rapidly. However, traditional tourism information has the disadvantages of slow response speed and limited information content, which cannot reflect the evolution trend of spatial and temporal patterns of tourism information in time. Here, based on [...] Read more.

In recent years, the tourism industry has developed rapidly. However, traditional tourism information has the disadvantages of slow response speed and limited information content, which cannot reflect the evolution trend of spatial and temporal patterns of tourism information in time. Here, based on the Baidu Index, we construct an evaluation framework to analyse the spatial and temporal flow of tourism information in the Chengdu–Chongqing urban cluster from 2011 to 2021. Then, we analyse the urban links between different network levels from the evolution pattern. Finally, we use the geodetector model to analyse its driving mechanism. The results show that Chengdu and Chongqing are the most active cities in the study area in terms of tourism information. The unbalanced development of tourism information between Chengdu and Chongqing and other cities in the region gradually deepens during the period 2011–2019 (polarization effect), but the unbalanced development moderates after 2019. On the other hand, cities in the middle of the Chengdu–Chongqing cluster always have weak agglomeration effects of tourism information. Cities with high tourism information outflow rates in the Chengdu–Chongqing city cluster are mainly concentrated around Chengdu. The average outflow rate of Deyang is the highest, at 27.8%. Cities with low tourist information outflow rates are primarily located in the west, central and south. Ya’an is the city with the lowest outflow rate, with an average of −62.2%. Specifically, Chengdu is the dominant and most radiantly influential city. The tourism information of the Chengdu–Chongqing urban cluster shows a radial network with Chengdu and Chongqing as the core. The driving force analysis shows that the push factor of tourist source, such as the number of people buying pension insurance, is the core driving mechanism, while the pull factor of destination, such as the park green area, and resistance factors such as psychological distance, are in the secondary position. In general, this paper uses Internet tourism data to expand the traditional tourism information research of the Chengdu–Chongqing urban cluster, which can better respond to the changes and needs of the tourism market and provide reference for the spatial optimization of tourism destinations. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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20 pages, 7590 KiB

Open AccessArticle

Implementation of Web Map Services for Old Cadastral Maps

by Alvaro Verdu-Candela, Carmen Femenia-Ribera, Gaspar Mora-Navarro and Rafael Sierra-Requena

ISPRS Int. J. Geo-Inf. 2023, 12(10), 413; https://doi.org/10.3390/ijgi12100413 - 10 Oct 2023

Viewed by 1666

Abstract

It is widely accepted that old cadastral maps have multiple uses, such as reestablishing cadastral parcel boundaries, municipality boundaries, and coastal limits, or conducting historical, economic, and social studies. In Spain, the Directorate General for Cadastre, and the National Geographic Institute, has numerous [...] Read more.

It is widely accepted that old cadastral maps have multiple uses, such as reestablishing cadastral parcel boundaries, municipality boundaries, and coastal limits, or conducting historical, economic, and social studies. In Spain, the Directorate General for Cadastre, and the National Geographic Institute, has numerous digitized old maps that are accessible to users. In the Comunidad Valenciana, the georeferencing of certain series of old cadastral maps is being carried out in phases, which is one of the subjects of this study. A metric analysis of two series of old cadastral maps from a municipality was conducted. One of the series was georeferenced by the Valencia Provincial Cadastre Office, while the other was georeferenced in this research. Additionally, a spatial data infrastructure (SDI) was created, providing WMS, catalog, and document download services. Metadata were also published, containing information about the source, digitalization process, georeferencing, and achieved accuracy, following the ISO 19115 standard for geographic metadata. Furthermore, through individual and group interviews, participatory social research was conducted, to assess the use of old cadastral maps and the created SDI services, aiming to understand the users’ appreciation of the services. The results of the social research indicate that the SDI services created are highly valued, but certain conditions need to be met to ensure their effective use by the general public in order to avoid misuses and misinterpretations. Full article

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20 pages, 6425 KiB

Open AccessArticle

Evaluating the Usability of a Gaze-Adaptive Approach for Identifying and Comparing Raster Values between Multilayers

by Changbo Zhang, Hua Liao, Yongbo Huang and Weihua Dong

ISPRS Int. J. Geo-Inf. 2023, 12(10), 412; https://doi.org/10.3390/ijgi12100412 - 08 Oct 2023

Viewed by 1231

Abstract

Raster maps provide intuitive visualizations of remote sensing data representing various phenomena on the Earth’s surface. Reading raster maps with intricate information requires a high cognitive workload, especially when it is necessary to identify and compare values between multiple layers. In traditional methods, [...] Read more.

Raster maps provide intuitive visualizations of remote sensing data representing various phenomena on the Earth’s surface. Reading raster maps with intricate information requires a high cognitive workload, especially when it is necessary to identify and compare values between multiple layers. In traditional methods, users need to repeatedly move their mouse and switch their visual focus between the map content and legend to interpret various grid value meanings. Such methods are ineffective and may lead to the loss of visual context for users. In this research, we aim to explore the potential benefits and drawbacks of gaze-adaptive interactions when interpreting raster maps. We focus on the usability of the use of low-cost eye trackers on gaze-based interactions. We designed two gaze-adaptive methods, gaze fixed and gaze dynamic adaptations, for identifying and comparing raster values between multilayers. In both methods, the grid content of different layers is adaptively adjusted depending on the user’s visual focus. We then conducted a user experiment by comparing such adaptation methods with a mouse dynamic adaptation method and a traditional method. Thirty-one participants (n = 31) were asked to complete a series of single-layer identification and multilayer comparison tasks. The results indicated that although gaze interaction with adaptive legends confused participants in single-layer identification, it improved multilayer comparison efficiency and effectiveness. The gaze-adaptive approach was well received by the participants overall, but was also perceived to be distracting and insensitive. By analyzing the participants’ eye movement data, we found that different methods exhibited significant differences in visual behaviors. The results are helpful for gaze-driven adaptation research in (geo)visualization in the future. Full article

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24 pages, 2019 KiB

Open AccessArticle

The Spatial Structure and Driving Mechanisms of Multi-Source Networks in the Chengdu–Chongqing Economic Circle of China

by Ludan Zhang, Xueman Zuo, Ziyi Wu, Cheng Chen, Zibao Pan and Xisheng Hu

ISPRS Int. J. Geo-Inf. 2023, 12(10), 411; https://doi.org/10.3390/ijgi12100411 - 08 Oct 2023

Viewed by 1290

Abstract

The phenomenon of polarized development among regional cities has sparked extensive contemplation and indicated a need for research on multi-source regional networks. However, such research faces two obstacles: the absence of quantitative measurement of differences in network structures and the lack of a [...] Read more.

The phenomenon of polarized development among regional cities has sparked extensive contemplation and indicated a need for research on multi-source regional networks. However, such research faces two obstacles: the absence of quantitative measurement of differences in network structures and the lack of a thorough examination of the degree of city clustering and the dynamics of community composition in hierarchical networks. Thus, we identified 16 cities in the Chengdu–Chongqing Economic Circle (CCEC) as the spatial units to examine the spatial network structures of population, resources, and transportation and the integrated spatial network structure. Using social network analysis, this paper describes the structural characteristics of the three networks (population, resource, and transportation), followed by an analysis of their collective and hierarchical network clustering characteristics, and explores the driving mechanisms and factors that make up each network model. Our results show the following: (1) All three networks exhibit an “east dense, west sparse” characteristic, but there are differences in the layouts of the core cities in terms of the three networks. (2) The clustering characteristics of the hierarchical networks are more pronounced than those of the overall network. The results of the analysis combined with the network formation mechanisms can help effectively plan the future coordinated development of the CCEC. Full article

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18 pages, 29738 KiB

Open AccessArticle

Do Locations of Employment and Residence Influence whether People Use Virtual Social Networks? A Case Study of Residents in Wuhan, China

by Huixia Deng, Qiang Niu and Lei Wu

ISPRS Int. J. Geo-Inf. 2023, 12(10), 410; https://doi.org/10.3390/ijgi12100410 - 06 Oct 2023

Cited by 1 | Viewed by 1217

Abstract

High-speed information technology development has made virtual social networking (VSN) a social interaction trend. Studies have been carried out to investigate the spatial clustering characteristics of the locations where there is online social interaction, but they have not yet concentrated on the geographic [...] Read more.

High-speed information technology development has made virtual social networking (VSN) a social interaction trend. Studies have been carried out to investigate the spatial clustering characteristics of the locations where there is online social interaction, but they have not yet concentrated on the geographic phenomenon associated with the distribution of occupational and residential locations of citizens who use VSN. According to usage statistics gathered from China Unicom for people living in the Wuhan metropolitan development area, there are geographical characteristics for the sites of employment and residence of virtual social application (VSA) users. Compared with people who live or work in the central city, suburban citizens are more willing to conduct virtual social networking, and those who are most likely to do so are concentrated in the suburbs 20–30 km from the main city. Additionally, we used geographically weighted regressions to evaluate the relationship between the density of physical social facilities and the possibility of the usage of VSAs, revealing the influence of various conventional social conveniences on the propensity to use the VSA. Residents are more inclined to engage in VSN in places where traditional social interaction is inconvenient, particularly in suburbs, indicating that VSN is an addition to traditional social interaction. Nonetheless, neither an improvement in, nor the replacement of, VSN activities is apparent in places where conventional socializing is practical. This study identified the clustering of virtual social users’ places of employment and residence in metropolitan areas and concluded that virtual social interaction offers new social channels for people who lack access to adequate physical social facilities; that is, it complements traditional social interaction. These results can deepen the understanding of the relationship between traditional social interaction and VSN. They also offer a fresh viewpoint on facility planning for the potential future creation of a more balanced and diverse social interaction environment through the joint planning of virtual and physical social facilities. Full article

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ISPRS Int. J. Geo-Inf., Volume 12, Issue 10 (October 2023) – 53 articles

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