Urban Informatics for Green Infrastructure: An Integrated Approach for Street Trees Data Collection, Analytics, and Citizen Science in New York City

Increasing spatial-temporal data enable granular and complex investigations of cities as complex systems. While previous studies investigated the promises of urban computing and spatial-temporal dynamics of human mobility in the urban environment, the urban landscape’s spatial-temporal complexity is still largely unexplored. This study overviews the origin, process, and impact of the New York City Street Trees Census, including its data collection process, integration and analytics methods, and citizen science connecting urban management and community engagement. Based on various limitations of current technology, the author proposes an integrated approach with both human-led and machine-conducted data generation techniques for urban forestry data collection and management. Reflecting on the case of NYC and other cities in the U.S., the author discusses the current development of urban forestry data in Chinese cities. The conclusion highlights an integrated approach’s critical contribution, which would fuse both manual and automated data collection and bring nature, technology, and people together in cities.