Exploring the new frontier of information extraction through large language models in urban analytics

Batty M (2019) Urban analytics defined. Environment and Planning B: Urban Analytics and City Science 46(3):403–405. https://doi.org/10.1177/2399808319839494

Batty M (2023) A new kind of search. Environment and Planning B: Urban Analytics and City Science 50(3):575–578. https://doi.org/10.1177/23998083231165363

Brown T Mann B Ryder N , et al. (2020) Language models are few-shot learners. In: Larochelle H Ranzato M Hadsell R , et al. (eds) 34th Conference on Neural Information Processing Systems. NeurIPS, Vancouver, Canada, pp 1877–1901

Date K Allweil Y (2022) Towards a new image archive for the built environment. Environment and Planning B: Urban Analytics and City Science 49(2):519–534. https://doi.org/10.1177/23998083211011474

Devlin J Chang MW Lee K , et al. (2018) BERT: pre-training of deep bidirectional transformers for language understanding. ArXiv Preprint arXiv:181004805

Feng Y Ding L Xiao G (2023) GeoQAMap - Geographic Question Answering with maps leveraging LLM and open knowledge base. In: Beecham R Long JA Smith D , et al. (eds) 12th International Conference on Geographic Information Science. Dagstuhl Publishing, Leeds, England, pp 28:1–28:7. https://doi.org/10.4230/LIPIcs.GIScience.2023.28

Fu X Wang R Li C (2023) Can ChatGPT evaluate plans? Journal of the American Planning Association pp 1–12. https://doi.org/10.1080/01944363.2023.2271893

Hu Y Mai G Cundy C , et al. (2023) Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages. International Journal of Geographical Information Science 37(11):2289–2318. https://doi.org/10.1080/13658816.2023.2266495

Jang KM Chen J Kang Y , et al. (2023) Understanding place identity with generative AI. In: Beecham R Long JA Smith D , et al. (eds) 12th International Conference on Geographic Information Science. Dagstuhl Publishing, Leeds, England, pp 41:1– 41:6, https://doi.org/10.4230/LIPIcs.GIScience.2023.41

Li S Ma S Tong D , et al. (2022) Associations between the quality of street space and the attributes of the built environment using large volumes of street view pictures. Environment and Planning B: Urban Analytics and City Science 49(4):1197–1211. https://doi.org/10.1177/23998083211056341

Li Z Ning H (2023) Autonomous GIS: the next-generation AI-powered GIS. ArXiv Preprint arXiv:230506453.

Ning H Ye X Chen Z , et al. (2022) Sidewalk extraction using aerial and street view images. Environment and Planning B: Urban Analytics and City Science 49(1):7–22. https://doi.org/10.1177/2399808321995817

Ouyang L Wu J Jiang X , et al. (2022) Training language models to follow instructions with human feedback. In: Koyejo S Mohamed S Agarwal A , et al. (eds) Advances in Neural Information Processing Systems. New Orleans, LA: NEURIPS, 35, 27730–27744.

Tao R Xu J (2023) Mapping with ChatGPT. ISPRS International Journal of Geo- Information 12(7):284. https://doi.org/10.3390/ijgi12070284

Zhou Z Zhong T Liu M , et al. (2023) Evaluating building color harmoniousness in a historic district intelligently: an algorithm-driven approach using street- view images. Environment and Planning B: Urban Analytics and City Science 50(7):1838–1857. https://doi.org/10.1177/23998083221146539

Zhu AX Zhao FH Liang P , et al. (2021) Next generation of GIS: must be easy. Annals of GIS 27(1):71–86. https://doi.org/10.1080/19475683.2020.1766563