{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T17:50:37Z","timestamp":1782496237550,"version":"3.54.5"},"reference-count":66,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,6,14]],"date-time":"2026-06-14T00:00:00Z","timestamp":1781395200000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Transactions in GIS"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Human mobility data are increasingly used in applications such as transportation analysis, traffic management, and urban planning, leading to the rapid growth of large\u2010scale trajectory datasets. A crucial aspect of analyzing human trajectories is the identification of critical points within these datasets. These critical points serve as effective representatives of entire trajectories, thereby reducing the computational demands associated with processing and analysis while maintaining the necessary level of accuracy. This study proposes a framework called Spatio\u2010temporal Semantic Contextual Attention\u2010based Encoder\u2013Decoder Trajectory Prediction (STSC\u2010AED TrajecPred), designed to improve the identification and prediction of critical points in human trajectories. By utilizing fuzzy functions, the framework effectively integrates spatial, temporal, semantic, and contextual information to identify critical points that act as proxies for comprehensive datasets. The framework uses a transformer\u2010based encoder\u2013decoder model together with spatial, temporal, semantic, and contextual embeddings to improve trajectory prediction. Evaluation results on two large\u2010scale datasets demonstrate that STSC\u2010AED TrajecPred successfully identifies critical points and reconstructs trajectory structures with an emphasis on enriched critical regions, leading to significant improvements in prediction accuracy while reducing computational overhead compared to existing approaches.<\/jats:p>","DOI":"10.1111\/tgis.70303","type":"journal-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T03:57:24Z","timestamp":1781495844000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Analyzing Critical Regions in Human Trajectories: A Context\u2010Aware Framework for Deep Learning\u2010Based Movement Prediction"],"prefix":"10.1111","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9523-9385","authenticated-orcid":false,"given":"Simin Sadat","family":"Mirvahabi","sequence":"first","affiliation":[{"name":"School of Surveying and Geospatial Engineering, College of Engineering University of Tehran  Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7133-3844","authenticated-orcid":false,"given":"Rahim","family":"Ali Abbaspour","sequence":"additional","affiliation":[{"name":"School of Surveying and Geospatial Engineering, College of Engineering University of Tehran  Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5586-1997","authenticated-orcid":false,"given":"Christophe","family":"Claramunt","sequence":"additional","affiliation":[{"name":"Naval Academy Research Institute Lanveoc\u2010Poulmic  Brest France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,14]]},"reference":[{"issue":"1","key":"e_1_2_11_2_1","first-page":"701","article-title":"User Location Prediction Using Hybrid Birch Clustering and Machine Learning Approach","volume":"12","author":"Arora M.","year":"2024","journal-title":"Journal of Integrated Science Technology"},{"key":"e_1_2_11_3_1","first-page":"973","volume-title":"OpenStreetMap in GIScience. 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