Positional accuracy analysis of Flickr and Panoramio images for selected world regions

Abstract

Flickr and Panoramio are fast-growing photo-sharing services that contain millions of geotagged images contributed by Web users from all over the world. This study analyses the positional accuracy of 1433 images for 45 areas in four selected world regions by comparing the geotagged position of photos to the manually corrected camera position based on the image content. The analysis reveals a better positional accuracy for Panoramio than for Flickr images, and some effects of image category and world region on positional accuracy. These findings can be helpful when considering Flickr and Panoramio images as data sources for future geo-applications and services.

Keywords:

• volunteered geographic information
• data quality
• positional accuracy