Pub Date : 2022-01-24DOI: 10.1080/15230406.2021.2014974
N. Dyer, C. Kastrisios, L. De Floriani
ABSTRACT Hydrographic sounding selection is the process of generalizing high-resolution bathymetry data to a more manageable subset capable of supporting nautical chart compilation or bathymetric modeling, and thus, is a fundamental task in nautical cartography. As technology improves and bathymetric data are collected at higher resolutions, the need for automated generalization algorithms that respect nautical cartographic constraints increases, since errors in this phase are carried over to the final product. Currently, automated algorithms for hydrographic sounding selection rely on radius- and grid-based approaches; however, their outputs contain a dense set of soundings with a significant number of cartographic constraint violations, thus increasing the burden and cost of the subsequent, mostly manual, cartographic sounding selection. This work presents a novel label-based generalization algorithm that utilizes the physical dimensions of the symbolized depth values on charts to avoid the over-plot of depth labels at scale. Additionally, validation tests based on cartographic constraints for nautical charting are implemented to compare the results of the proposed algorithm to radius and grid-based approaches. It is shown that the label-based generalization approach best adheres to the constraints of functionality (safety) and legibility.
{"title":"Label-based generalization of bathymetry data for hydrographic sounding selection","authors":"N. Dyer, C. Kastrisios, L. De Floriani","doi":"10.1080/15230406.2021.2014974","DOIUrl":"https://doi.org/10.1080/15230406.2021.2014974","url":null,"abstract":"ABSTRACT Hydrographic sounding selection is the process of generalizing high-resolution bathymetry data to a more manageable subset capable of supporting nautical chart compilation or bathymetric modeling, and thus, is a fundamental task in nautical cartography. As technology improves and bathymetric data are collected at higher resolutions, the need for automated generalization algorithms that respect nautical cartographic constraints increases, since errors in this phase are carried over to the final product. Currently, automated algorithms for hydrographic sounding selection rely on radius- and grid-based approaches; however, their outputs contain a dense set of soundings with a significant number of cartographic constraint violations, thus increasing the burden and cost of the subsequent, mostly manual, cartographic sounding selection. This work presents a novel label-based generalization algorithm that utilizes the physical dimensions of the symbolized depth values on charts to avoid the over-plot of depth labels at scale. Additionally, validation tests based on cartographic constraints for nautical charting are implemented to compare the results of the proposed algorithm to radius and grid-based approaches. It is shown that the label-based generalization approach best adheres to the constraints of functionality (safety) and legibility.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"338 - 353"},"PeriodicalIF":2.5,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47021736","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}
Pub Date : 2022-01-24DOI: 10.1080/15230406.2021.2013946
Z. Ghaemi, U. Engelke, Barrett Ens, B. Jenny
ABSTRACT In human computer interaction, proxemics describes the ways that people use space to interact with other people or objects. We focus on proxemic maps, which are virtual maps in immersive environments that react to proxemic interaction. Proxemic maps take advantage of new opportunities brought about by immersive visualization, where virtual maps can be freely positioned in virtual or physical space and adapt themselves relative to the spatial position of the viewer. We discuss proxemic interactions that alter the content and type of maps, including changing scale, symbolization, type of visualization and geometry. We propose a novel transformation that changes the geometry of maps based on their proximity to users. Users move the map back and forth and the map transitions between ring, horizontal, vertical and cylindrical geometries. The ring geometry surrounds the user and aligns features on the map with features in the real world. We implemented the map transformation in virtual reality and conducted a user study to evaluate it. The results of the user study indicate that participants preferred the ring and horizontal geometries. The ring geometry is useful because it simplifies connecting virtual features on the map with real features in the landscape, while the horizontal geometry provides an overall view of the landscape. We further found that combination of different geometries helped the study participants to overcome the limitations of each geometry.
{"title":"Proxemic maps for immersive visualization","authors":"Z. Ghaemi, U. Engelke, Barrett Ens, B. Jenny","doi":"10.1080/15230406.2021.2013946","DOIUrl":"https://doi.org/10.1080/15230406.2021.2013946","url":null,"abstract":"ABSTRACT In human computer interaction, proxemics describes the ways that people use space to interact with other people or objects. We focus on proxemic maps, which are virtual maps in immersive environments that react to proxemic interaction. Proxemic maps take advantage of new opportunities brought about by immersive visualization, where virtual maps can be freely positioned in virtual or physical space and adapt themselves relative to the spatial position of the viewer. We discuss proxemic interactions that alter the content and type of maps, including changing scale, symbolization, type of visualization and geometry. We propose a novel transformation that changes the geometry of maps based on their proximity to users. Users move the map back and forth and the map transitions between ring, horizontal, vertical and cylindrical geometries. The ring geometry surrounds the user and aligns features on the map with features in the real world. We implemented the map transformation in virtual reality and conducted a user study to evaluate it. The results of the user study indicate that participants preferred the ring and horizontal geometries. The ring geometry is useful because it simplifies connecting virtual features on the map with real features in the landscape, while the horizontal geometry provides an overall view of the landscape. We further found that combination of different geometries helped the study participants to overcome the limitations of each geometry.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"205 - 219"},"PeriodicalIF":2.5,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41521261","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}
Pub Date : 2022-01-19DOI: 10.1080/15230406.2021.2011419
Caglar Koylu, A. Kasakoff
ABSTRACT Studying migration over a long period is challenging due to lack of data, uneven data quality, and the methodological challenges that arise when analyzing migration over large geographic areas and long time spans with constantly changing political boundaries. Crowd-sourced family tree data are an untapped source of volunteered geographic information generated by millions of users. These trees contain information on individuals such as birth and death places and years, and kinship ties, and have the potential to support analysis of population dynamics and migration over many generations and far into the past. In this article, we introduce a methodology to measure and map long-term changes in migration flows using a population-scale family-tree data set. Our methodology includes many steps such as extracting migration events, temporal periodization, gravity normalization, and producing time-series flow maps. We study internal migration in the continental United States between 1789 and 1924 using birthplaces and birthyears of children from a cleaned, geocoded, and connected set of family trees from Rootsweb.com. To the best of our knowledge, the results are the first migration flow maps that show how the internal migration flows within the U.S. changed over such a long period of time (i.e. 135 years).
{"title":"Measuring and mapping long-term changes in migration flows using population-scale family tree data","authors":"Caglar Koylu, A. Kasakoff","doi":"10.1080/15230406.2021.2011419","DOIUrl":"https://doi.org/10.1080/15230406.2021.2011419","url":null,"abstract":"ABSTRACT Studying migration over a long period is challenging due to lack of data, uneven data quality, and the methodological challenges that arise when analyzing migration over large geographic areas and long time spans with constantly changing political boundaries. Crowd-sourced family tree data are an untapped source of volunteered geographic information generated by millions of users. These trees contain information on individuals such as birth and death places and years, and kinship ties, and have the potential to support analysis of population dynamics and migration over many generations and far into the past. In this article, we introduce a methodology to measure and map long-term changes in migration flows using a population-scale family-tree data set. Our methodology includes many steps such as extracting migration events, temporal periodization, gravity normalization, and producing time-series flow maps. We study internal migration in the continental United States between 1789 and 1924 using birthplaces and birthyears of children from a cleaned, geocoded, and connected set of family trees from Rootsweb.com. To the best of our knowledge, the results are the first migration flow maps that show how the internal migration flows within the U.S. changed over such a long period of time (i.e. 135 years).","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"154 - 170"},"PeriodicalIF":2.5,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42236660","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}
Pub Date : 2022-01-17DOI: 10.1080/15230406.2021.2013944
Jiawei Du, Fang Wu, J. Yin, Chengyi Liu, Xianyong Gong
ABSTRACT The present paper presents techniques for polyline simplification based on an artificial neural network within the constraints of generalization knowledge. The proposed method measures polyline shape characteristics that influence polyline simplification using abstracted descriptors and then introduces these descriptors into the artificial neural network as input properties. In total, 18 descriptors categorized into three types are presented in detail. In a second approach, map simplification principles are abstracted as controllers, imposed after the output layer of the trained artificial neural network to make the polyline simplification comply with these principles. This study worked with three controllers – a basic controller and two knowledge-based controllers. These descriptors and controllers abstracted from generalization knowledge were tested in experiments to determine their efficacy in polyline simplification based on the artificial neural network. The experimental results show that the utilization of abstracted descriptors and controllers can constrain the artificial neural network-based polyline simplification according to polyline shape characteristics and simplification principles.
{"title":"Polyline simplification based on the artificial neural network with constraints of generalization knowledge","authors":"Jiawei Du, Fang Wu, J. Yin, Chengyi Liu, Xianyong Gong","doi":"10.1080/15230406.2021.2013944","DOIUrl":"https://doi.org/10.1080/15230406.2021.2013944","url":null,"abstract":"ABSTRACT The present paper presents techniques for polyline simplification based on an artificial neural network within the constraints of generalization knowledge. The proposed method measures polyline shape characteristics that influence polyline simplification using abstracted descriptors and then introduces these descriptors into the artificial neural network as input properties. In total, 18 descriptors categorized into three types are presented in detail. In a second approach, map simplification principles are abstracted as controllers, imposed after the output layer of the trained artificial neural network to make the polyline simplification comply with these principles. This study worked with three controllers – a basic controller and two knowledge-based controllers. These descriptors and controllers abstracted from generalization knowledge were tested in experiments to determine their efficacy in polyline simplification based on the artificial neural network. The experimental results show that the utilization of abstracted descriptors and controllers can constrain the artificial neural network-based polyline simplification according to polyline shape characteristics and simplification principles.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"313 - 337"},"PeriodicalIF":2.5,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43722260","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}
ABSTRACT Voice-assisted digital maps have become mainstream navigation aids for pedestrian navigation. Although these maps are widely studied and applied, it is still unclear how they affect human behavior and spatial knowledge acquisition. In this study, we recruited thirty-three college students to carry out an outdoor wayfinding experiment. We compared the effects of voice-assisted digital maps with those of digital maps without voice instructions and paper maps by using eye tracking, sketch maps, questionnaires and interviews. The results show that, compared to the other map types, voice-assisted digital maps can help users reach their destinations more quickly and pay more attention to moving objects, thereby increasing the comfort levels of participants. However, the efficiency of voice-assisted maps on route memory tasks does not rival that of paper maps. Overall, the use of voice-assisted digital maps saves time but may reduce pedestrians’ spatial knowledge acquisition. The results of this study reveal the influence of voice on pedestrian wayfinding and deepen the scientific understanding of the multimedia navigation mode in shaping human spatial ability.
{"title":"How do voice-assisted digital maps influence human wayfinding in pedestrian navigation?","authors":"Yawei Xu, Tong Qin, Yulin Wu, Cheng Yu, Weihua Dong","doi":"10.1080/15230406.2021.2017798","DOIUrl":"https://doi.org/10.1080/15230406.2021.2017798","url":null,"abstract":"ABSTRACT Voice-assisted digital maps have become mainstream navigation aids for pedestrian navigation. Although these maps are widely studied and applied, it is still unclear how they affect human behavior and spatial knowledge acquisition. In this study, we recruited thirty-three college students to carry out an outdoor wayfinding experiment. We compared the effects of voice-assisted digital maps with those of digital maps without voice instructions and paper maps by using eye tracking, sketch maps, questionnaires and interviews. The results show that, compared to the other map types, voice-assisted digital maps can help users reach their destinations more quickly and pay more attention to moving objects, thereby increasing the comfort levels of participants. However, the efficiency of voice-assisted maps on route memory tasks does not rival that of paper maps. Overall, the use of voice-assisted digital maps saves time but may reduce pedestrians’ spatial knowledge acquisition. The results of this study reveal the influence of voice on pedestrian wayfinding and deepen the scientific understanding of the multimedia navigation mode in shaping human spatial ability.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"271 - 287"},"PeriodicalIF":2.5,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44278295","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}
Pub Date : 2022-01-13DOI: 10.1080/15230406.2021.2015720
M. Bartling, Bernd Resch, T. Reichenbacher, C. Havas, A. Robinson, S. Fabrikant, T. Blaschke
ABSTRACT The increased use of mobile maps in our highly mobile digital culture has resulted in a large variety of map users and map use situations. For mobile map applications that engage a broad user base and feature diverging map usage contexts, one-size-fits-all map interface designs might result in significant usability tradeoffs. To respond to this challenge, changing the map design based on map use context attributes, such as increasing icon sizes for people with impaired vision or using the user’s position to highlight information on the map are only a few of the many ways mobile map applications can be designed and adapted to respond to the needs of users and their map use situations. However, there remains a clear need for research on the intersections between map use contexts and mobile map application design and adaptation. Therefore, this article reviews and synthesizes literature on map use context research and design adaptation of mobile map applications. To push forward efforts in these areas, we propose future research themes and approaches. We first evaluate options for modeling map use context, which plays a significant part in map adaptations for detecting relevant context attributes on which to base adaptation decisions. We then consider dynamic possibilities to assess the usability of these adaptations by reviewing the HEART framework. We conclude by offering ways to move the suggested approaches from concepts closer to practice.
{"title":"Adapting mobile map application designs to map use context: a review and call for action on potential future research themes","authors":"M. Bartling, Bernd Resch, T. Reichenbacher, C. Havas, A. Robinson, S. Fabrikant, T. Blaschke","doi":"10.1080/15230406.2021.2015720","DOIUrl":"https://doi.org/10.1080/15230406.2021.2015720","url":null,"abstract":"ABSTRACT The increased use of mobile maps in our highly mobile digital culture has resulted in a large variety of map users and map use situations. For mobile map applications that engage a broad user base and feature diverging map usage contexts, one-size-fits-all map interface designs might result in significant usability tradeoffs. To respond to this challenge, changing the map design based on map use context attributes, such as increasing icon sizes for people with impaired vision or using the user’s position to highlight information on the map are only a few of the many ways mobile map applications can be designed and adapted to respond to the needs of users and their map use situations. However, there remains a clear need for research on the intersections between map use contexts and mobile map application design and adaptation. Therefore, this article reviews and synthesizes literature on map use context research and design adaptation of mobile map applications. To push forward efforts in these areas, we propose future research themes and approaches. We first evaluate options for modeling map use context, which plays a significant part in map adaptations for detecting relevant context attributes on which to base adaptation decisions. We then consider dynamic possibilities to assess the usability of these adaptations by reviewing the HEART framework. We conclude by offering ways to move the suggested approaches from concepts closer to practice.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"237 - 251"},"PeriodicalIF":2.5,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44410371","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}
Pub Date : 2021-12-16DOI: 10.1080/15230406.2021.2007419
Paweł Cybulski, Vassilios Krassanakis
ABSTRACT The present study aims to examine how the visual search for cartographic symbols is affected by the language of map labels. More specifically, we explore the influence of native language in the performance of a visual search map task which is referred to target point symbol detection. The main research hypothesis is that the relative position of the target symbols plays a significant role in the visual search process, although labels language impacts reaction time. In a controlled laboratory experiment with 38 participants and eye tracking technology, we used maps with labels in participants’ native language (Polish) and in Chinese, which participants could neither read nor write. We find that the detection of target symbols with Chinese labels is faster when the symbol’s location is peripheral. On the other hand, faster detection of target symbols with labels in participants’ native language favors central location. It turned out that having noticed the target symbol, participants fixated on the native language label. For Chinese labels, having seen the target symbol, participants did not fixate on the label. It also turned out that when participants searched for a target symbol located in the peripheral zone, more visual attention was in this zone. However, when the target symbol’s location was central, the participants’ visual attention focused mostly on the central zone. This confirms the significant role of the location of cartographic symbols in the visual search process.
{"title":"The effect of map label language on the visual search of cartographic point symbols","authors":"Paweł Cybulski, Vassilios Krassanakis","doi":"10.1080/15230406.2021.2007419","DOIUrl":"https://doi.org/10.1080/15230406.2021.2007419","url":null,"abstract":"ABSTRACT The present study aims to examine how the visual search for cartographic symbols is affected by the language of map labels. More specifically, we explore the influence of native language in the performance of a visual search map task which is referred to target point symbol detection. The main research hypothesis is that the relative position of the target symbols plays a significant role in the visual search process, although labels language impacts reaction time. In a controlled laboratory experiment with 38 participants and eye tracking technology, we used maps with labels in participants’ native language (Polish) and in Chinese, which participants could neither read nor write. We find that the detection of target symbols with Chinese labels is faster when the symbol’s location is peripheral. On the other hand, faster detection of target symbols with labels in participants’ native language favors central location. It turned out that having noticed the target symbol, participants fixated on the native language label. For Chinese labels, having seen the target symbol, participants did not fixate on the label. It also turned out that when participants searched for a target symbol located in the peripheral zone, more visual attention was in this zone. However, when the target symbol’s location was central, the participants’ visual attention focused mostly on the central zone. This confirms the significant role of the location of cartographic symbols in the visual search process.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"189 - 204"},"PeriodicalIF":2.5,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45881135","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}
Pub Date : 2021-12-13DOI: 10.1080/15230406.2021.1994469
T. Opach, J. K. Rød
ABSTRACT Common operational understanding among engaged emergency responders is facilitated through shared operational pictures during crisis situations. Sharing is typically achieved through interactive tools, either desktop or web-based, in which map displays play an essential role. That role can be further strengthened if (1) agreed emergency symbols that are used in map-based interactive tools are sufficient to encode multifaceted operational information visually; and (2) the symbols are legible and meaningful for the diverse users of those tools. The authors revisited official emergency map symbols in use in Norway and reconsidered them against current requirements. To this end, they first conducted several meetings with stakeholders to elicit adequate revision requirements. Next, the reconsideration included the extension of the symbol set, symbol modification, and grouping. After the reconsideration, emergency management officers and specialists were interviewed. The interviews confirmed the agreement with the symbol categorization, extension of the symbols, and their modifications. The interviewees also made numerous suggestions to be considered in a follow-up study. Moreover, two concepts – symbol standardization and symbol harmonization – were proposed.
{"title":"A user-centric optimization of emergency map symbols to facilitate common operational picture","authors":"T. Opach, J. K. Rød","doi":"10.1080/15230406.2021.1994469","DOIUrl":"https://doi.org/10.1080/15230406.2021.1994469","url":null,"abstract":"ABSTRACT Common operational understanding among engaged emergency responders is facilitated through shared operational pictures during crisis situations. Sharing is typically achieved through interactive tools, either desktop or web-based, in which map displays play an essential role. That role can be further strengthened if (1) agreed emergency symbols that are used in map-based interactive tools are sufficient to encode multifaceted operational information visually; and (2) the symbols are legible and meaningful for the diverse users of those tools. The authors revisited official emergency map symbols in use in Norway and reconsidered them against current requirements. To this end, they first conducted several meetings with stakeholders to elicit adequate revision requirements. Next, the reconsideration included the extension of the symbol set, symbol modification, and grouping. After the reconsideration, emergency management officers and specialists were interviewed. The interviews confirmed the agreement with the symbol categorization, extension of the symbols, and their modifications. The interviewees also made numerous suggestions to be considered in a follow-up study. Moreover, two concepts – symbol standardization and symbol harmonization – were proposed.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"134 - 153"},"PeriodicalIF":2.5,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48135252","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}
Pub Date : 2021-11-16DOI: 10.1080/15230406.2021.1992299
Xiao Li, H. Ning, Xiao Huang, B. Dadashova, Yuhao Kang, Andong Ma
ABSTRACT Auditing and mapping traffic infrastructure is a crucial task in urban management. For example, signalized intersections play an essential role in transportation management; however, effectively identifying these intersections remains unsolved. Traditionally, signalized intersection data are manually collected through field audits or checking street view images (SVIs), which is time-consuming and labor-intensive. This study proposes an effective protocol to identify signalized intersections using road networks and SVIs. First, we propose a six-step geoprocessing model to generate an intersection feature layer from road networks. Second, we utilize up to three nearest SVIs to capture streetscapes at each intersection. Then, a deep learning-based image segmentation model is adopted to recognize traffic light-related pixels from each SVI. Last, we design a post-processing step to generate new features characterizing SVIs’ segmentation results at each intersection and build a decision tree model to determine the traffic control type. Results demonstrate that the proposed protocol can effectively identify signalized intersections with an overall accuracy of 97.05%. It also proves the effectiveness of SVIs for auditing urban infrastructures. This study can directly benefit transportation agencies by providing a ready-to-use smart audit and mapping solution for large-scale identification and mapping of signalized intersections.
{"title":"Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images","authors":"Xiao Li, H. Ning, Xiao Huang, B. Dadashova, Yuhao Kang, Andong Ma","doi":"10.1080/15230406.2021.1992299","DOIUrl":"https://doi.org/10.1080/15230406.2021.1992299","url":null,"abstract":"ABSTRACT Auditing and mapping traffic infrastructure is a crucial task in urban management. For example, signalized intersections play an essential role in transportation management; however, effectively identifying these intersections remains unsolved. Traditionally, signalized intersection data are manually collected through field audits or checking street view images (SVIs), which is time-consuming and labor-intensive. This study proposes an effective protocol to identify signalized intersections using road networks and SVIs. First, we propose a six-step geoprocessing model to generate an intersection feature layer from road networks. Second, we utilize up to three nearest SVIs to capture streetscapes at each intersection. Then, a deep learning-based image segmentation model is adopted to recognize traffic light-related pixels from each SVI. Last, we design a post-processing step to generate new features characterizing SVIs’ segmentation results at each intersection and build a decision tree model to determine the traffic control type. Results demonstrate that the proposed protocol can effectively identify signalized intersections with an overall accuracy of 97.05%. It also proves the effectiveness of SVIs for auditing urban infrastructures. This study can directly benefit transportation agencies by providing a ready-to-use smart audit and mapping solution for large-scale identification and mapping of signalized intersections.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"49 1","pages":"32 - 49"},"PeriodicalIF":2.5,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44104138","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}
Pub Date : 2021-11-16DOI: 10.1080/15230406.2021.1991479
Heng Wan, Jim Yoon, Vivek Srikrishnan, Brent Daniel, D. Judi
ABSTRACT Multi-temporal and spatially explicit population data are vital in many fields, such as demography, urban planning, disaster prevention,economics, and environmental modeling. Population data used in these studies are typically aggregated at census enumeration units, which are too coarse for many applications. Accurate population downscaling methods are needed to obtain population data at finer spatial resolutions. We use a novel settlement-related database, Built-Up Property Records (BUPR) from the Historical Settlement Data Compilation for the United States (HISDAC-US) to downscale population from census tracts to block groups. The BUPR dataset provides the number of built-up property records for each 250-m grid at 5-year temporal resolution from 1810 to 2015 for most contiguous United States (CONUS). The ability of BUPR to downscale population from census tracts to block groups for four states, representing a range of population densities, is evaluated here by comparing against other commonly-used ancillary datasets. The BUPR-based method outperforms all other methods in all but one state with highly-incomplete BUPR. A more detailed accuracy assessment is performed by dividing each state into low, medium, and high population density categories. The BUPR method produces more accurate downscaled population estimates for low and medium categories, though its performance deteriorates in the high density category due to its relatively coarse spatial resolution. BUPR-based dasymetric mapping is subsequently applied to the CONUS and found to generalize well beyond the four comparison states with high downscaling accuracy. The long-term record of the HISDAC-US dataset enables the potential construction of fine-grained population data back to 1810.
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