The development of information technologies and the advent of extensive digital data since the 21st century have enabled more profound explorations and interpretations of the relationship between humans and the urban environment. This study systematically reviews the application of emerging data-driven methods in measuring human-environment interaction in urban spaces. The synthesis of 242 studies reveals a diversified application landscape of data-driven methods, employing street view imagery data, social media data, positioning data, physiological data, and video data, each carrying distinct information and addressing various research inquiries. We also review the new insights generated by their application, which offered evidence for analyzing and evaluating a wide range of established frameworks and classic theories concerning human perceptual, cognitive, emotional, and behavioral aspects in urban spaces. Based on these findings, we describe the trends, advancements, and limitations of this rising research field, and make recommendations for future researchers adopting data-driven methods to understand relationships between humans and environments in urban spaces.