A distance cartogram is a deformed map where the distance between points conforms to a specific proximity indicator. Its readability is crucial, requiring a similar spatial arrangement of points between the original map and cartogram. Previous studies mainly incorporated angle changes of point pairs into the optimization objective. However, this soft constraint fails to provide high readability for spatial interaction data with numerous points and links. This study emphasizes the significance of maintaining Delaunay triangulation during deformation. To achieve this, topology‐constrained particle swarm optimization (TC‐PSO) is proposed, in which triangle intersections and flipping are prevented during optimization. Additionally, a topology error is introduced to evaluate the difference in triangulation between the original and deformed maps. TC‐PSO outperforms previous approaches by exhibiting the smallest topology error and producing more readable cartograms in simulation experiments and Baidu index data. These show TC‐PSO's advantage as a cartographic tool.
{"title":"Constructing topology‐constrained distance cartograms with application on spatial interaction data","authors":"Tianyou Cheng, Hao Guo, Xiao‐Jian Chen, Quanhua Dong, Chaogui Kang, Yu Liu","doi":"10.1111/tgis.13168","DOIUrl":"https://doi.org/10.1111/tgis.13168","url":null,"abstract":"A distance cartogram is a deformed map where the distance between points conforms to a specific proximity indicator. Its readability is crucial, requiring a similar spatial arrangement of points between the original map and cartogram. Previous studies mainly incorporated angle changes of point pairs into the optimization objective. However, this soft constraint fails to provide high readability for spatial interaction data with numerous points and links. This study emphasizes the significance of maintaining Delaunay triangulation during deformation. To achieve this, topology‐constrained particle swarm optimization (TC‐PSO) is proposed, in which triangle intersections and flipping are prevented during optimization. Additionally, a topology error is introduced to evaluate the difference in triangulation between the original and deformed maps. TC‐PSO outperforms previous approaches by exhibiting the smallest topology error and producing more readable cartograms in simulation experiments and Baidu index data. These show TC‐PSO's advantage as a cartographic tool.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yucheng Shu, Zihao Tang, Yiming Zhang, Yongning Wen, Min Chen, S. Yue
Global climate change has escalated flood risks, necessitating advanced hydrodynamic models for predicting watershed dynamics. Integrating flow‐field visualization with web maps offers a time‐sensitive, geographic context for sharing and understanding these dynamic changes virtually. Traditional methods use texture series on maps for flow visualization but fall short in interactive detail examination. Drawing geometric shapes directly on maps has been limited by low efficiency. Addressing the need for interactive visualization and efficiency, this study presents a texture polymorphism strategy for geometric visualization of time‐varying flow fields. This approach combines geometric style simulation with texture‐assisted computation, optimizing interactivity and performance on web map platforms. Our evaluation confirms that this method enhances usability and integration, ensuring high performance in visualizing flow dynamics.
{"title":"A geometry‐based method for visualizing time‐varying flow fields on web map platforms using texture polymorphism","authors":"Yucheng Shu, Zihao Tang, Yiming Zhang, Yongning Wen, Min Chen, S. Yue","doi":"10.1111/tgis.13177","DOIUrl":"https://doi.org/10.1111/tgis.13177","url":null,"abstract":"Global climate change has escalated flood risks, necessitating advanced hydrodynamic models for predicting watershed dynamics. Integrating flow‐field visualization with web maps offers a time‐sensitive, geographic context for sharing and understanding these dynamic changes virtually. Traditional methods use texture series on maps for flow visualization but fall short in interactive detail examination. Drawing geometric shapes directly on maps has been limited by low efficiency. Addressing the need for interactive visualization and efficiency, this study presents a texture polymorphism strategy for geometric visualization of time‐varying flow fields. This approach combines geometric style simulation with texture‐assisted computation, optimizing interactivity and performance on web map platforms. Our evaluation confirms that this method enhances usability and integration, ensuring high performance in visualizing flow dynamics.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of reliable seafloor topography models is a complex, multi‐track process, which is due to the diversity of available sets of data, their resolution, acquisition methods, complex seafloor forms, and the multitude of interpolation techniques. This article is aimed at assessing the suitability of different algorithms for seafloor modelling based on hybrid datasets (multi‐beam soundings and raster GEBCO models). The study involves the selection of optimum solutions as well as a comparative analysis of sea level change trends based on altimetric data. The study area relates to four forms of seafloor topography, namely the oceanic trench, the submarine canyon, the seamount region, and the undulating areas. The most reliable models were built by interpolating by the Kriging methods at a 0.01‐degree grid spacing. The smallest residues and the greatest correlation are found between models generated from all available sounding datasets. Raster GEBCO models can be an alternative in the additional model densification. The results show the following relationships: the greater the variation in the topography, the greater the divergence in the values of the sea level change trends. As for seamounts, hills, and folds, when the terrain rises rapidly, the trend values also increase and then decrease during the decline. Seafloor structure mapping enables the search for relationships between the seafloor topography and the changes occurring at the water surface.
{"title":"Possibility and quality assessment in seafloor modeling relative to the sea surface using hybrid data","authors":"Idzikowska Magdalena, Pająk Katarzyna, Kowalczyk Kamil","doi":"10.1111/tgis.13178","DOIUrl":"https://doi.org/10.1111/tgis.13178","url":null,"abstract":"The development of reliable seafloor topography models is a complex, multi‐track process, which is due to the diversity of available sets of data, their resolution, acquisition methods, complex seafloor forms, and the multitude of interpolation techniques. This article is aimed at assessing the suitability of different algorithms for seafloor modelling based on hybrid datasets (multi‐beam soundings and raster GEBCO models). The study involves the selection of optimum solutions as well as a comparative analysis of sea level change trends based on altimetric data. The study area relates to four forms of seafloor topography, namely the oceanic trench, the submarine canyon, the seamount region, and the undulating areas. The most reliable models were built by interpolating by the Kriging methods at a 0.01‐degree grid spacing. The smallest residues and the greatest correlation are found between models generated from all available sounding datasets. Raster GEBCO models can be an alternative in the additional model densification. The results show the following relationships: the greater the variation in the topography, the greater the divergence in the values of the sea level change trends. As for seamounts, hills, and folds, when the terrain rises rapidly, the trend values also increase and then decrease during the decline. Seafloor structure mapping enables the search for relationships between the seafloor topography and the changes occurring at the water surface.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140984066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The grid map, often referred to as the tile map, stands as a vital tool in geospatial visualization, possessing unique attributes that differentiate it from more commonly known techniques such as choropleths and cartograms. It transforms geographic regions into grids, which requires the displacement of both region centroids and boundary nodes to establish a coherent grid arrangement. However, existing approaches typically displace region centroids and boundary nodes separately, potentially resulting in self‐intersected boundaries and compromised relative orientation relations between regions. In this article, we introduce a novel approach that leverages the Snake displacement algorithm from cartographic generalization to concurrently displace region centroids and boundary nodes. The revised constrained Delaunay triangulation (CDT) is employed to represent the relations between regions and serves as a structural foundation for the Snake algorithm. Forces for displacing the region centroids into a grid‐like pattern are then computed. These forces are iteratively applied within the Snake model until a satisfactory new boundary is achieved. Subsequently, the grid map is created by aligning the grids with the newly generated boundary, utilizing a one‐to‐one match algorithm to assign each region to a specific grid. Experimental results demonstrate that the proposed approach excels in maintaining the relative orientation and global shape of regions, albeit with a potential increase in local location deviations. We also present two strategies aligned with existing approaches to generate diverse grid maps for user preferences. Further details and resources are available on our project website: https://github.com/TrentonWei/DorlingMap.git.
{"title":"Generating grid maps via the snake model","authors":"Zhiwei Wei, Nai Yang, Wenjia Xu, Ding Su","doi":"10.1111/tgis.13174","DOIUrl":"https://doi.org/10.1111/tgis.13174","url":null,"abstract":"The grid map, often referred to as the tile map, stands as a vital tool in geospatial visualization, possessing unique attributes that differentiate it from more commonly known techniques such as choropleths and cartograms. It transforms geographic regions into grids, which requires the displacement of both region centroids and boundary nodes to establish a coherent grid arrangement. However, existing approaches typically displace region centroids and boundary nodes separately, potentially resulting in self‐intersected boundaries and compromised relative orientation relations between regions. In this article, we introduce a novel approach that leverages the Snake displacement algorithm from cartographic generalization to concurrently displace region centroids and boundary nodes. The revised constrained Delaunay triangulation (CDT) is employed to represent the relations between regions and serves as a structural foundation for the Snake algorithm. Forces for displacing the region centroids into a grid‐like pattern are then computed. These forces are iteratively applied within the Snake model until a satisfactory new boundary is achieved. Subsequently, the grid map is created by aligning the grids with the newly generated boundary, utilizing a one‐to‐one match algorithm to assign each region to a specific grid. Experimental results demonstrate that the proposed approach excels in maintaining the relative orientation and global shape of regions, albeit with a potential increase in local location deviations. We also present two strategies aligned with existing approaches to generate diverse grid maps for user preferences. Further details and resources are available on our project website: https://github.com/TrentonWei/DorlingMap.git.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140983415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jianbin Zhou, Jin Ben, Qishuang Liang, Xinhai Huang, Junjie Ding
One of the basic scientific problems concerning geographic information science is how to rapidly organize, query, and compute spatiotemporal big data. The spatiotemporal discrete global grid system (DGGS) provides a homogenized discrete structure for processing multiscale and multitype spatiotemporal data. To date, most research in spatiotemporal DGGS has focused on spatial discretization while neglecting temporal discretization. Here, we propose a general modeling scheme for spatiotemporal DGGS with emphasis on encoding and operating multiscale time grids. We subdivide continuous time into multiscale temporal grids, which are then encoded as integers. Moreover, we designed integer code operations, including hierarchical traversal, neighborhood finding, and temporal relationship calculations. Compared to the multiscale time segment integer coding (MTSIC) approach, the proposed method resulted in 22% higher encoding efficiency, 10.92 times faster decoding, 2.81 times better parent code finding efficiency, 41% improved efficiency, 100% accuracy in finding children codes (compared to less than 100% with MTSIC), and a 62% enhancement in temporal relationship calculation efficiency. The application of querying spatiotemporal trajectory data validates the feasibility and practicality of substituting conventional string‐based time and floating‐point location coordinates with spatiotemporal integer codes to query data. The time encoding and operation methods proposed here indicate high efficiency, superior accuracy, and broad application prospects.
{"title":"A general modeling scheme for spatiotemporal DGGS with emphasis on encoding and operating multiscale time grids","authors":"Jianbin Zhou, Jin Ben, Qishuang Liang, Xinhai Huang, Junjie Ding","doi":"10.1111/tgis.13173","DOIUrl":"https://doi.org/10.1111/tgis.13173","url":null,"abstract":"One of the basic scientific problems concerning geographic information science is how to rapidly organize, query, and compute spatiotemporal big data. The spatiotemporal discrete global grid system (DGGS) provides a homogenized discrete structure for processing multiscale and multitype spatiotemporal data. To date, most research in spatiotemporal DGGS has focused on spatial discretization while neglecting temporal discretization. Here, we propose a general modeling scheme for spatiotemporal DGGS with emphasis on encoding and operating multiscale time grids. We subdivide continuous time into multiscale temporal grids, which are then encoded as integers. Moreover, we designed integer code operations, including hierarchical traversal, neighborhood finding, and temporal relationship calculations. Compared to the multiscale time segment integer coding (MTSIC) approach, the proposed method resulted in 22% higher encoding efficiency, 10.92 times faster decoding, 2.81 times better parent code finding efficiency, 41% improved efficiency, 100% accuracy in finding children codes (compared to less than 100% with MTSIC), and a 62% enhancement in temporal relationship calculation efficiency. The application of querying spatiotemporal trajectory data validates the feasibility and practicality of substituting conventional string‐based time and floating‐point location coordinates with spatiotemporal integer codes to query data. The time encoding and operation methods proposed here indicate high efficiency, superior accuracy, and broad application prospects.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140942306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher A. Ramezan, Aaron E. Maxwell, Joshua T. Meadows
As the demand for geospatial analytics continues to grow, geographic information systems (GIS) professionals are needed to build, operate, and maintain GIS technologies, data, and software to provide geospatial insights for modern industries and organizations. To best train the next generation of GIS professionals, an understanding of qualifications and requirements of GIS positions is needed. Thus, this work analyzes 508 GIS positions, grouped by position type (analysts, developers, educators, managers, specialists, technicians) to provide insights on key pre‐requisite requirements, such as education, experience, certifications, soft communication skills, programming skills, and knowledge of GIS or IT. In general, possession of a bachelor's degree in GIS, geography, or computer science, prior professional experience, and knowledge of GIS and IT software were common pre‐requisites for most GIS roles. Soft communication skills were also frequently desired for GIS roles. We also found that some position requirements tended to vary by position type, such as manager and developer roles requiring on average 5 years or higher prior experience, while analyst, specialist, and technician roles had much lower experience and education requirements. Higher education institutions and GIS training programs should note the desired requirements for GIS position types and continue to refine programs and develop pathways for success for aspiring GIS professionals.
{"title":"An analysis of qualifications and requirements for geographic information systems (GIS) positions in the United States","authors":"Christopher A. Ramezan, Aaron E. Maxwell, Joshua T. Meadows","doi":"10.1111/tgis.13176","DOIUrl":"https://doi.org/10.1111/tgis.13176","url":null,"abstract":"As the demand for geospatial analytics continues to grow, geographic information systems (GIS) professionals are needed to build, operate, and maintain GIS technologies, data, and software to provide geospatial insights for modern industries and organizations. To best train the next generation of GIS professionals, an understanding of qualifications and requirements of GIS positions is needed. Thus, this work analyzes 508 GIS positions, grouped by position type (analysts, developers, educators, managers, specialists, technicians) to provide insights on key pre‐requisite requirements, such as education, experience, certifications, soft communication skills, programming skills, and knowledge of GIS or IT. In general, possession of a bachelor's degree in GIS, geography, or computer science, prior professional experience, and knowledge of GIS and IT software were common pre‐requisites for most GIS roles. Soft communication skills were also frequently desired for GIS roles. We also found that some position requirements tended to vary by position type, such as manager and developer roles requiring on average 5 years or higher prior experience, while analyst, specialist, and technician roles had much lower experience and education requirements. Higher education institutions and GIS training programs should note the desired requirements for GIS position types and continue to refine programs and develop pathways for success for aspiring GIS professionals.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140940014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article proposes a new approach to market area analysis. Market area analysis is conducted in various academic fields, such as retail geography, marketing science, transportation science, and tourism study. It aims to understand the factors that affect visitors' choice behavior, which improves the performance of various sites, such as stores, restaurants, museums, and stadiums. Methods for market area analysis, however, have not been fully developed in the literature. To fill the research gap, this article proposes new methods of market area analysis. The first method considers the relationship between a site and its visitors. Our focus is on the spatial pattern of visitors around a site. The second method discusses the spatial relationship between the visitors of two sites. We evaluate the competing relationship between different sites. We applied the methods to the analysis of mountain climbers in Japan. The results gave us useful and interesting empirical findings, indicating the method's soundness.
{"title":"Market area analysis with a focus on the spatial relationship between sites and their visitors","authors":"Yukio Sadahiro, Hidetaka Matsumoto","doi":"10.1111/tgis.13167","DOIUrl":"https://doi.org/10.1111/tgis.13167","url":null,"abstract":"This article proposes a new approach to market area analysis. Market area analysis is conducted in various academic fields, such as retail geography, marketing science, transportation science, and tourism study. It aims to understand the factors that affect visitors' choice behavior, which improves the performance of various sites, such as stores, restaurants, museums, and stadiums. Methods for market area analysis, however, have not been fully developed in the literature. To fill the research gap, this article proposes new methods of market area analysis. The first method considers the relationship between a site and its visitors. Our focus is on the spatial pattern of visitors around a site. The second method discusses the spatial relationship between the visitors of two sites. We evaluate the competing relationship between different sites. We applied the methods to the analysis of mountain climbers in Japan. The results gave us useful and interesting empirical findings, indicating the method's soundness.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140942555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Floods are becoming more widely acknowledged as a common occurrence of nature's dangers on a global scale. Although forecasting models primarily focus on timely warnings, models aimed at evaluating dangerous zones can play a vital role in shaping policies for adaptation, mitigation, and reducing the risk of disasters. Using machine learning techniques including hybrid black widow optimization (BWO) with XGBoost, LGBoost, and AdaBoost. We generate a flood susceptibility map for considered region of lower mahanadi basin (LMB). This study examines the effectiveness of these machine learning models in assessing and mapping flood susceptibility, while also providing suggestions for future research in this area. Flood susceptibility model was developed using 13 variables: Altitude, Aspect, Curvature, Distance from river, Drainage Density, Stream Power Index (SPI), Sediment Transport Index (STI), Rainfall intensity, Land Use Land Cover (LULC), Topographic Wetness Index (TWI), Terrain Roughness Index (TRI), Normalized Difference Vegetation Index (NDVI), and slope. Additionally, flood inventory data were incorporated into the model. Dataset was divided into a 70% portion for training model and a 30% portion for validating model. To assess the performance of the model, several evaluation metrics were employed, including receiver operating characteristic (ROC) curve and other performance indices. Evaluation of flood susceptibility mapping, using ROC curve method in combination with flood density yielded strong and reliable results for various models. BWO‐XGBoost achieved a score of 0.889, BWO‐LGBoost achieved a score of 0.937, and BWO‐ADABoost achieved a score of 0.904. These scores indicate effectiveness of these models in accurately predicting flood susceptibility in the study area. A comparison was made with commonly used methods in flood susceptibility assessment to evaluate the efficiency of proposed models. It was found that having a first‐class and enlightening database is crucial for accurately classifying flood types in flood susceptibility mapping. This aspect greatly contributes to improving the overall performance of the model. Among the evaluated methods, the hybrid model BWO‐LGBoost demonstrated better performance compared with others, indicating its effectiveness in accurately predicting flood susceptibility.
{"title":"Flood susceptibility modeling by integrating tree‐based regression with metaheuristic algorithm, BWO","authors":"Deba Prakash Satapathy, Bibhu Prasad Mishra","doi":"10.1111/tgis.13171","DOIUrl":"https://doi.org/10.1111/tgis.13171","url":null,"abstract":"Floods are becoming more widely acknowledged as a common occurrence of nature's dangers on a global scale. Although forecasting models primarily focus on timely warnings, models aimed at evaluating dangerous zones can play a vital role in shaping policies for adaptation, mitigation, and reducing the risk of disasters. Using machine learning techniques including hybrid black widow optimization (BWO) with XGBoost, LGBoost, and AdaBoost. We generate a flood susceptibility map for considered region of lower mahanadi basin (LMB). This study examines the effectiveness of these machine learning models in assessing and mapping flood susceptibility, while also providing suggestions for future research in this area. Flood susceptibility model was developed using 13 variables: Altitude, Aspect, Curvature, Distance from river, Drainage Density, Stream Power Index (SPI), Sediment Transport Index (STI), Rainfall intensity, Land Use Land Cover (LULC), Topographic Wetness Index (TWI), Terrain Roughness Index (TRI), Normalized Difference Vegetation Index (NDVI), and slope. Additionally, flood inventory data were incorporated into the model. Dataset was divided into a 70% portion for training model and a 30% portion for validating model. To assess the performance of the model, several evaluation metrics were employed, including receiver operating characteristic (ROC) curve and other performance indices. Evaluation of flood susceptibility mapping, using ROC curve method in combination with flood density yielded strong and reliable results for various models. BWO‐XGBoost achieved a score of 0.889, BWO‐LGBoost achieved a score of 0.937, and BWO‐ADABoost achieved a score of 0.904. These scores indicate effectiveness of these models in accurately predicting flood susceptibility in the study area. A comparison was made with commonly used methods in flood susceptibility assessment to evaluate the efficiency of proposed models. It was found that having a first‐class and enlightening database is crucial for accurately classifying flood types in flood susceptibility mapping. This aspect greatly contributes to improving the overall performance of the model. Among the evaluated methods, the hybrid model BWO‐LGBoost demonstrated better performance compared with others, indicating its effectiveness in accurately predicting flood susceptibility.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140940013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Coastal landscapes exert a significant impact on the human sentimental perceptions and physical and mental well‐being of people. However, little is known about explicitly linking between the landscape characteristics and people's sentimental preferences expressed in social media data. The main objective of this study was to explore the nonlinear and interaction effects of key factors that influenced sentiments in the coastal areas of Hong Kong, considering both subjective landscape preferences and objective landscape patterns. We quantified users' sentiment polarity based on the crowdsourcing textual data of Flickr. To study users' subjective landscape preferences, we computed various visual landscape objects' proportion in images. Meanwhile, eight user clusters and nine image clusters were detected by the identified visual object labels. We quantified objective landscape patterns considering the land use pattens and the availability of public service facilities. Finally, we utilized an interpretable classification model to analyze the factors that may affect sentiments and their interplay interactions. We found that ecotourism‐related clusters exhibited the most positive sentiment. The proportion of floor and sky pixels in images exhibits the highest global relative importance when predicting sentiments. This study extends a new insight on the relationship between landscape characteristics and sentiments from both subjective and objective perspectives based on social media data and interpretable machine learning methods. This research may help decision‐makers in designing landscapes that aptly satisfy to the needs of the public and promote sustainable management of the coastal environment.
{"title":"Unraveling the relationship between coastal landscapes and sentiments: An integrated approach based on social media data and interpretable machine learning methods","authors":"Haojie Cao, Min Weng, Mengjun Kang, Shiliang Su","doi":"10.1111/tgis.13175","DOIUrl":"https://doi.org/10.1111/tgis.13175","url":null,"abstract":"Coastal landscapes exert a significant impact on the human sentimental perceptions and physical and mental well‐being of people. However, little is known about explicitly linking between the landscape characteristics and people's sentimental preferences expressed in social media data. The main objective of this study was to explore the nonlinear and interaction effects of key factors that influenced sentiments in the coastal areas of Hong Kong, considering both subjective landscape preferences and objective landscape patterns. We quantified users' sentiment polarity based on the crowdsourcing textual data of Flickr. To study users' subjective landscape preferences, we computed various visual landscape objects' proportion in images. Meanwhile, eight user clusters and nine image clusters were detected by the identified visual object labels. We quantified objective landscape patterns considering the land use pattens and the availability of public service facilities. Finally, we utilized an interpretable classification model to analyze the factors that may affect sentiments and their interplay interactions. We found that ecotourism‐related clusters exhibited the most positive sentiment. The proportion of floor and sky pixels in images exhibits the highest global relative importance when predicting sentiments. This study extends a new insight on the relationship between landscape characteristics and sentiments from both subjective and objective perspectives based on social media data and interpretable machine learning methods. This research may help decision‐makers in designing landscapes that aptly satisfy to the needs of the public and promote sustainable management of the coastal environment.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140940015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nai Yang, Zhitao Deng, Fangtai Hu, Yi Chao, Lin Wan, Qingfeng Guan, Zhiwei Wei
Understanding the spatial distribution patterns of urban perception and analyzing the correlation between human emotional perception and street composition elements are important for accurately understanding how people interact with the urban environment, urban planning, and urban management. Previous studies on urban perception using street view data have not fully considered the actual level of attention to different visual elements when browsing street view images. In this article, we use eye tracking technology to collect eye movement data and subjective perception evaluation data when people browse street view images, and analyze the correlation between the time to first fixation, duration of first fixation, and fixation frequency of different visual elements and the six perceptual outcomes of wealthy, safe, lively, beautiful, boring, and depressing. Furthermore, this article integrates eye movement data with street view semantic data and introduces a novel method for predicting urban perception using a machine learning algorithm. The proposed method outperforms a comparative model that solely relies on semantic data, exhibiting higher accuracy in perception prediction. Additionally, the study presents a perceptual mapping of the prediction results, providing a visual representation of the predicted urban perception outcomes. As vision is the primary perceptual channel, this study achieves a more objective and scientifically reliable urban perception, which is of reference value for the study of physical and mental health due to the urban physical environment.
{"title":"Urban perception by using eye movement data on street view images","authors":"Nai Yang, Zhitao Deng, Fangtai Hu, Yi Chao, Lin Wan, Qingfeng Guan, Zhiwei Wei","doi":"10.1111/tgis.13172","DOIUrl":"https://doi.org/10.1111/tgis.13172","url":null,"abstract":"Understanding the spatial distribution patterns of urban perception and analyzing the correlation between human emotional perception and street composition elements are important for accurately understanding how people interact with the urban environment, urban planning, and urban management. Previous studies on urban perception using street view data have not fully considered the actual level of attention to different visual elements when browsing street view images. In this article, we use eye tracking technology to collect eye movement data and subjective perception evaluation data when people browse street view images, and analyze the correlation between the time to first fixation, duration of first fixation, and fixation frequency of different visual elements and the six perceptual outcomes of wealthy, safe, lively, beautiful, boring, and depressing. Furthermore, this article integrates eye movement data with street view semantic data and introduces a novel method for predicting urban perception using a machine learning algorithm. The proposed method outperforms a comparative model that solely relies on semantic data, exhibiting higher accuracy in perception prediction. Additionally, the study presents a perceptual mapping of the prediction results, providing a visual representation of the predicted urban perception outcomes. As vision is the primary perceptual channel, this study achieves a more objective and scientifically reliable urban perception, which is of reference value for the study of physical and mental health due to the urban physical environment.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140881806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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