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Exploring Human Mobility: A Time-Informed Approach to Pattern Mining and Sequence Similarity.
IF 4.3 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2025-01-01 Epub Date: 2024-11-21 DOI: 10.1080/13658816.2024.2427258
Hao Yang, X Angela Yao, Christopher C Whalen, Noah Kiwanuka
{"title":"Exploring Human Mobility: A Time-Informed Approach to Pattern Mining and Sequence Similarity.","authors":"Hao Yang, X Angela Yao, Christopher C Whalen, Noah Kiwanuka","doi":"10.1080/13658816.2024.2427258","DOIUrl":"https://doi.org/10.1080/13658816.2024.2427258","url":null,"abstract":"<p><p>The surge in the availability of spatial big data has sparked increased interest in researching human mobility patterns. Despite this, discovering human mobility patterns from such spatial big data and assessing the similarity between patterns remains a formidable challenge. This study introduces two novel methods: the Time-Informed pattern mining (TiPam) method for frequent pattern mining and a Time-Aware Longest Common Subsequence (T-LCS) algorithm for assessing similarity between time-conscious sequences. Leveraging these innovative algorithms, our research introduces an analytical framework for analyzing human mobility patterns at both individual and aggregated levels. As a case study, this proposed workflow is applied to examine the daily mobility patterns of voluntary mobile phone users in Kampala, Uganda. The 135 participants are found in four distinct groups labeled with distinct mobility properties for users in each group: \"stay-at-home,\" \"unoccupied,\" \"education-oriented,\" and \"work-oriented.\" The results effectively showcase the efficiency of the framework and the novel techniques employed. The framework's versatility extends to human mobility studies with other forms of data and across various research fields.</p>","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"39 3","pages":"627-651"},"PeriodicalIF":4.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906185/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
GPU-accelerated parallel all-pair shortest path routing within stochastic road networks 随机道路网络中的 GPU 加速并行全对最短路径路由选择
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-09-01 DOI: 10.1080/13658816.2024.2394651
Wenwu Tang, Tianyang Chen, Marc P. Armstrong
{"title":"GPU-accelerated parallel all-pair shortest path routing within stochastic road networks","authors":"Wenwu Tang, Tianyang Chen, Marc P. Armstrong","doi":"10.1080/13658816.2024.2394651","DOIUrl":"https://doi.org/10.1080/13658816.2024.2394651","url":null,"abstract":"All-pair shortest path routing within stochastic road networks is often more complicated and computationally challenging than routing in deterministic networks because uncertainties in travel time ...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"17 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Collective flow-evolutionary patterns reveal the mesoscopic structure between snapshots of spatial network 集体流演变模式揭示了空间网络快照之间的中观结构
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-09-01 DOI: 10.1080/13658816.2024.2395953
Zhongfu Ma, Di Zhu
{"title":"Collective flow-evolutionary patterns reveal the mesoscopic structure between snapshots of spatial network","authors":"Zhongfu Ma, Di Zhu","doi":"10.1080/13658816.2024.2395953","DOIUrl":"https://doi.org/10.1080/13658816.2024.2395953","url":null,"abstract":"Uncovering the collective behavior of flows among locations is critical to understanding the structure within an ever-changing spatial network. When a network evolves, there may exist subgraphs wit...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"45 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi’s domain adaptability 用于图像分析的地理空间基础模型：评估和增强 NASA-IBM Prithvi 的领域适应性
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-08-30 DOI: 10.1080/13658816.2024.2397441
Chia-Yu Hsu, Wenwen Li, Sizhe Wang
{"title":"Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi’s domain adaptability","authors":"Chia-Yu Hsu, Wenwen Li, Sizhe Wang","doi":"10.1080/13658816.2024.2397441","DOIUrl":"https://doi.org/10.1080/13658816.2024.2397441","url":null,"abstract":"Research on geospatial foundation models (GFMs) has become a trending topic in geospatial artificial intelligence (AI) research due to their potential for achieving high generalizability and domain...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"24 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Translating street view imagery to correct perspectives to enhance bikeability and walkability studies 将街景图像转换为正确的视角，以加强自行车可骑性和步行可行性研究
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-08-27 DOI: 10.1080/13658816.2024.2391969
Koichi Ito, Matias Quintana, Xianjing Han, Roger Zimmermann, Filip Biljecki
{"title":"Translating street view imagery to correct perspectives to enhance bikeability and walkability studies","authors":"Koichi Ito, Matias Quintana, Xianjing Han, Roger Zimmermann, Filip Biljecki","doi":"10.1080/13658816.2024.2391969","DOIUrl":"https://doi.org/10.1080/13658816.2024.2391969","url":null,"abstract":"Street view imagery (SVI), an emerging geospatial dataset, is useful for evaluating active transportation infrastructure, but it faces potential biases from its vehicle-based capture method, diverg...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"6 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A multi-view ensemble machine learning approach for 3D modeling using geological and geophysical data 利用地质和地球物理数据进行三维建模的多视角集合机器学习方法
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-08-22 DOI: 10.1080/13658816.2024.2394228
Deping Chu, Jinming Fu, Bo Wan, Hong Li, Lulan Li, Fang Fang, Shengwen Li, Shengyong Pan, Shunping Zhou
{"title":"A multi-view ensemble machine learning approach for 3D modeling using geological and geophysical data","authors":"Deping Chu, Jinming Fu, Bo Wan, Hong Li, Lulan Li, Fang Fang, Shengwen Li, Shengyong Pan, Shunping Zhou","doi":"10.1080/13658816.2024.2394228","DOIUrl":"https://doi.org/10.1080/13658816.2024.2394228","url":null,"abstract":"Geophysical data are often integrated into geological data for 3D modeling of underground spaces. However, the existing single-view approach means it is difficult to adequately fuse the valid infor...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"67 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A backfitting maximum likelihood estimator for hierarchical and geographically weighted regression modelling, with a case study of house prices in Beijing 用于分层和地理加权回归建模的反拟合最大似然估计器，以北京房价为例进行研究
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-08-21 DOI: 10.1080/13658816.2024.2391412
Yigong Hu, Richard Harris, Richard Timmerman, Binbin Lu
{"title":"A backfitting maximum likelihood estimator for hierarchical and geographically weighted regression modelling, with a case study of house prices in Beijing","authors":"Yigong Hu, Richard Harris, Richard Timmerman, Binbin Lu","doi":"10.1080/13658816.2024.2391412","DOIUrl":"https://doi.org/10.1080/13658816.2024.2391412","url":null,"abstract":"Geographically weighted regression (GWR) and its extensions are important local modelling techniques for exploring spatial heterogeneity in regression relationships. However, when dealing with spat...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"231 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On ignoring the heterogeneity in spatial autocorrelation: consequences and solutions 关于忽略空间自相关性中的异质性：后果与解决方案
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-08-20 DOI: 10.1080/13658816.2024.2391981
Zehua Zhang, Ziqi Li, Yongze Song
{"title":"On ignoring the heterogeneity in spatial autocorrelation: consequences and solutions","authors":"Zehua Zhang, Ziqi Li, Yongze Song","doi":"10.1080/13658816.2024.2391981","DOIUrl":"https://doi.org/10.1080/13658816.2024.2391981","url":null,"abstract":"Spatial autoregressive (SAR) models are often used to explicitly account for the spatial dependence underlying geographic phenomena. However, traditional SAR models are specified using a single SAR...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"6 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A systematic scheme to maintain multiple characteristics for effective polygon rasterization 为有效实现多边形光栅化而维护多种特征的系统方案
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-08-19 DOI: 10.1080/13658816.2024.2391982
Chen Zhou, Manchun Li
{"title":"A systematic scheme to maintain multiple characteristics for effective polygon rasterization","authors":"Chen Zhou, Manchun Li","doi":"10.1080/13658816.2024.2391982","DOIUrl":"https://doi.org/10.1080/13658816.2024.2391982","url":null,"abstract":"Polygon characteristics, including area, shape, and topology, may be lost during rasterization, leading to inaccurate analyses. Maintaining multiple characteristics remains a challenging multi-obje...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"38 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Map matching on low sampling rate trajectories through deep inverse reinforcement learning and multi-intention modeling 通过深度反强化学习和多意图建模实现低采样率轨迹的地图匹配
IF 5.7 1区 地球科学
International Journal of Geographical Information Science Pub Date : 2024-08-19 DOI: 10.1080/13658816.2024.2391411
Reza Safarzadeh, Xin Wang
{"title":"Map matching on low sampling rate trajectories through deep inverse reinforcement learning and multi-intention modeling","authors":"Reza Safarzadeh, Xin Wang","doi":"10.1080/13658816.2024.2391411","DOIUrl":"https://doi.org/10.1080/13658816.2024.2391411","url":null,"abstract":"Analyzing freight vehicle movements using GPS trajectory data presents challenges due to environmental conditions and hardware limitations impacting data accuracy. Map matching, the process of alig...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"19 1","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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