Extracting Built Environment Features for Planning Research with Computer Vision: A Review and Discussion of State-of-the-Art Approaches
It addresses the need for robust feature extraction in planning research, but is incremental as it focuses on reviewing existing methods.
This study reviewed state-of-the-art computer vision approaches for extracting built environment features to enhance empirical research in planning, synthesizing findings from interdisciplinary literature.
This is an extended abstract for a presentation at The 17th International Conference on CUPUM - Computational Urban Planning and Urban Management in June 2021. This study presents an interdisciplinary synthesis of the state-of-the-art approaches in computer vision technologies to extract built environment features that could improve the robustness of empirical research in planning. We discussed the findings from the review of studies in both planning and computer science.