ارائه رویکردی به ‌منظور ارزیابی الگوی مشارکت کاربران در اطلاعات مکانی داوطلبانه بزرگراه‌ها با استفاده از یادگیری ماشین

نوع مقاله : علمی - پژوهشی

نویسندگان
ُسعیده ساداتی 1
رحیم علی عباس پور 2
علیرضا چهرقان 3
عباس عابدینی 4
1 کارشناس ارشد، دانشکده نقشه‌برداری و اطلاعات مکانی، دانشکدگان فنی، دانشگاه تهران، ایران
2 دانشیار، دانشکده مهندسی نقشه‌برداری و اطلاعات مکانی، دانشکدگان فنی، دانشگاه تهران، ایران
3 دانشیار، دانشکده مهندسی معدن، دانشگاه صنعتی سهند، تبریز، ایران
4 استادیار، دانشکده مهندسی نقشه‌برداری و اطلاعات مکانی، دانشکدگان فنی، دانشگاه تهران، ایران
10.22119/jte.2024.435790.2695
چکیده
بزرگراه‌ها از پرترددترین و حیاتی‌ترین عوارض خطی در سیستم حمل‌و‌نقل کشور هستند که با گسترش زندگی شهری روزبه‌روز بر اهمیت آن‌ها افزوده شده است. ازاین‌رو دسترسی به اطلاعات به‌روز و کارآمد در ارتباط با این عوارض نقش به‌سزایی در مدیریت سیستم حمل‌و‌نقل کشورها دارد. ازجمله این اطلاعات می­توان اطلاعات مکانی داوطلبانه (Volunteer Geographic Information (VGI)) را نام برد که توسط کاربرانی ایجاد می‌شود که دانش تجربی یا محلی خود را از یک مکان یا موقعیت در پایگاه‌داده مکانی وارد می‌کنند. این مطالعه با ارائه رویکردی، روندهای ترسیم عوارض (نظیر بزرگراه‌ها و جاده‌ها) ایجاد شده توسط مشارکت‌کنندگان در پایگاه داده OpenStreetMap (OSM) را مورد بررسی قرار می ­دهد. همچنین یک بررسی آماری از الگوی مشارکتی کاربران به‌هنگام ترسیم شریان‌های ارتباطی انجام شده است و ویژگی­ های یک راه بر تعیین طبقه‌ آن مورد ارزیابی تحلیلی قرار گرفته است. در رویکرد پیشنهادی به منظور طبقه ­بندی انواع کلاس‌های بزرگراه‌ها از الگوریتم طبقه‌بندی جنگل تصادفی استفاده شده است. به منظور ارزیابی رویکرد پیشنهادی از داده‌های خطی شهر تهران استفاده شده است. نتایج طبقه‌بندی با استفاده از ویژگی­ های آزیموت خطوط بزرگراه‌ها، طول ژئودزیک خطوط، فاصله اولین نقاط ترسیمی تا نزدیک‌ترین خیابان و تراکم kernel اولین نقاط به F-Score برابر 71 درصد رسیده است. بررسی پارامترهای معنایی نظیر نام بزرگراه و نام کاربر نیز در این پژوهش انجام شد که نشان از عدم تأثیر آن‌ها بر دقت طبقه‌بندی دارد. پس از محاسبه اهمیت هر کدام از ویژگی­ های مورد استفاده، پارامتر طول ژئودزیک به‌عنوان مهم‌ترین عامل تأثیرگذار در رفتار کاربران مشارکت‌کننده در ترسیم انواع بزرگراه­ ها شناسایی گردید.

کلیدواژه‌ها

موضوعات

عنوان مقاله English

An Approach to Evaluate the User Participation Pattern in Highway's Volunteered Geographic Information using Machine Learning

نویسندگان English

Saeedeh Sadati 1
Rahim Ali abbaspour 2
Alireza Chehreghan 3
Abbas Abedini 4
1 M.Sc., School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 Associate Professor, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
3 Associate Professor, Faculty of Mining Engineering, Sahand University of Technology, Tabriz, Iran
4 Assistant Professor, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
چکیده English

Highways constitute one of the busiest and most vital linear elements in a country's transportation system, and their significance has grown steadily with the expansion of urban life. Consequently, access to up-to-date and efficient information about these linear elements plays a crucial role in managing the transportation systems of nations. Volunteered Geographic Information (VGI) is generated by users who contribute their experiential or local knowledge of a specific location to a spatial database. Statistical approaches help in understanding the trends of participatory behaviors. This study examines the patterns of contributors' involvement in mapping highways and roads in the OpenStreetMap (OSM) database in Tehran. Analyzing participatory patterns provides rich information on biases, statistics, and user activity directions and shifts, which are instrumental in transportation, urban planning, and management. The proposed approach evaluates how the characteristics of a road impact its classification. Highway classes are categorized using a random forest classifier, and the inferred mapping trends are analyzed based on the classification. Linear data from Tehran city will be used for the upcoming experiment, and the classification algorithm will be applied with the extraction parameters that resulted in the highest classification accuracy. Results demonstrate that the optimal combination of extraction parameters, such as the azimuth of highways, geodesic length of lines, distance from the first mapped point to the nearest street, and the kernel density of the initial points, achieves an F-Score of 71%. An examination of the semantic parameters, such as the highway name and user name, indicates their ineffectiveness on classification accuracy. After assessing the importance of each selected parameter, the azimuth parameter is identified as the most influential factor in the classification of highway types regarding user participation behavior.

کلیدواژه‌ها English

Volunteered Geographic Information (VGI)
OpenStreetMap (OSM)
Highway
Participation Pattern
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  • تاریخ دریافت 25 دی 1402
  • تاریخ بازنگری 29 اسفند 1402
  • تاریخ پذیرش 01 اردیبهشت 1403