Cities, as the nodes and centers of human society’s economic, cultural, and political systems, should pay attention not only to the coordination of their system structure and function but also to their leading role in sustainable development and the impact on the overall system, especially in the era of economic globalization. Routine statistics and census data have poor spatial completeness, are not real time, and vary in data quality, resulting in relatively low spatial and temporal resolution of urban sustainability assessment results, questioned reliability and timeliness. Big data is critical for overcoming the deficiencies of traditional statistical data in the assessment of urban sustainable development. It can provide a new impetus for urban sustainable development assessment with its macro, dynamic, and diverse advantages, which can provide support for sustainable urban development in terms of data products, technical methods, case analysis, and decision support.

Co-Chairs: Prof. Huang Chunlin, Mr. Aromar Revi