Translating street view imagery to correct perspectives to enhance bikeability and walkability studies

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

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

引用次数: 0

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...

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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

街景图像（SVI）是一种新兴的地理空间数据集，可用于评估主动式交通基础设施，但其基于车辆的捕捉方法可能会产生偏差，与其他数据集存在差异。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.