Comparing relationships between urban heat exposure, ecological structure, and socio-economic patterns in Beijing and New York City

Wang, J., T. McPhearson, W. Zhou, E.M. Cook, P. Herreros-Cantis, and J. Liu. 2023. Comparing relationships between urban heat exposure, ecological structure, and socio-economic patterns in Beijing and New York City. Landscape and Urban Planning 235:104750.

Social media data for environmental sustainability: A critical review of opportunities, threats, and ethical use

Ghermandi, A. et al. 2023. Social media data for environmental sustainability: A critical review of opportunities, threats, and ethical use. One Earth 6(3):236-250.

Social media data are transforming sustainability science. However, challenges from restrictions in data accessibility and ethical concerns regarding potential data misuse have threatened this nascent field. Here, we review the literature on the use of social media data in environmental and sustainability research. We find that they can play a novel and irreplaceable role in achieving the UN Sustainable Development Goals by allowing a nuanced understanding of...

NYC Climate Adaptation Scenarios for 2100: Exploring Alternative, Positive Visions for a Resilient Future

Cook, E., J. Ventrella, T. McPhearson, A. Parris, M. Tier, T. Muñoz-Erickson, D. Iwaniec, L. Mannetti, C. Green, and D. Tagtachian. 2022. NYC Climate Adaptation Scenarios for 2100: Exploring Alternative, Positive Visions for a Resilient Future. Urban Systems Lab, The New School .

In the face of global climate change, city governments must anticipate and guide decisions in response to extreme weather-related events, including coastal and inland flooding, heat waves, multi-hazard risks, drought, and winter extremes. With the goal of addressing this challenge, between Sept. 24 – Oct. 22, 2021, the National Science Foundation (NSF) Social-Ecological-Technological Systems (SETS) Convergence Research Network partnered with the New York City Mayor’s...

Artificial intelligence, systemic risks, and sustainability

Galaz, V., M.A. Centeno, P.W. Callahan, A. Causevic, T. Patterson. et al. 2021. Artificial intelligence, systemic risks, and sustainability. Technology in Society 67:101741.

Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments and private actors perceive and respond to climate and ecological change. Methods based on various forms of artificial intelligence are already today being applied in a number of research fields related to climate change...