The urban planning profession is increasingly challenged to analyze extensive text data, from plans to public feedback. While natural language processing (NLP) has promising potential for aiding this analysis, its applications and purpose in planning remain unclear. This article reviews current planning research using NLP, seeking to highlight key themes and challenges, and suggesting a coherent future research agenda. The results reveal that existing research is primarily exploratory with a fragmented research landscape. Future studies should focus on sharing data, benchmarking NLP techniques, fostering collaborative research tailored to planning, and addressing ethical implications to harness NLP's full potential in planning.

Sea level rise (SLR) is expected, even without greenhouse gas emissions. As SLR is inevitable, adapting to its impacts has received increasing attention, and local governments are the key actors in this emerging agenda. This study indicates that adaptation planning for SLR should be integrated into two local major planning mechanisms in the United States: the local comprehensive plans and hazard mitigation plans. By evaluating 36 plans from 15 US coastal cities that are considered at high risk and vulnerable to rising sea levels, the results demonstrate that SLR is widely identified, but the overall quality of the plans to address it requires significant improvement. A detailed table of selected plans' characteristics is also provided as a lens on how localities tackle this challenging issue. The paper concludes with planning suggestions for coastal communities to better adapt to SLR.

Planners need to read plans to learn and adapt current practice. Planners may struggle to find time to read and study lengthy planning documents, especially in emerging areas such as climate change...