打印

作者

Najmeh Neysani Samany

来源

CITIES,Vol.93,Issue1,Pages 1-12

语言

英文

关键字

Landmark extraction;Geo-tagged photos;Geo-social media;DNN;DBN

作者单位

Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran;Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran

摘要

Wayfinding is one of the most daily activities of peoples in urban spaces which could be facilitated by a set of landmarks to provide a mental map of the environment. Landmark detection in urban spaces is yet one of the great challenges in landmark-based wayfinding. This paper aims to apply new sources of geo-tagged photos derived from social media like Telegram for landmark extraction. This paper proposed a method to extract landmarks automatically through clustering of geo-tagged photos by Density Based Spatial Clustering of Applications with Noise (DBSCAN) method and object detection by deep artificial neural network (deep belief network) algorithm. The proposed method is implemented in 48 different routes of 3 districts of Tehran, Iran. The accuracy assessment demonstrated the efficiency of the algorithms for landmark extraction from huge geo-tagged photographs. Furthermore, the extracted landmarks are evaluated by 120 wayfinders. The experimental results demonstrated the usability of the proposed landmarks in wayfinding process with 87% of user satisfaction.