Zobrazeno 1 - 10
of 838
pro vyhledávání: '"Li, Zhenlong"'
Recent advancements in Generative AI offer promising capabilities for spatial analysis. Despite their potential, the integration of generative AI with established GIS platforms remains underexplored. In this study, we propose a framework for integrat
Externí odkaz:
http://arxiv.org/abs/2411.03205
Numerous researchers have utilized GPS-enabled vehicle data and SafeGraph mobility data to analyze human movements. However, the comparison of their ability to capture human mobility remains unexplored. This study investigates differences in human mo
Externí odkaz:
http://arxiv.org/abs/2410.16462
The resurgence and rapid advancement of Generative Artificial Intelligence (GenAI) in 2023 has catalyzed transformative shifts across numerous industry sectors, including urban transportation and logistics. This study investigates the evaluation of L
Externí odkaz:
http://arxiv.org/abs/2409.14516
Powered by the emerging large language models (LLMs), autonomous geographic information systems (GIS) agents have the potential to accomplish spatial analyses and cartographic tasks. However, a research gap exists to support fully autonomous GIS agen
Externí odkaz:
http://arxiv.org/abs/2407.21024
Autor:
Zeng, Chengbo, Zhang, Jiajia, Li, Zhenlong, Sun, Xiaowen, Olatosi, Bankole, Weissman, Sharon, Li, Xiaoming
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 4, p e27045 (2021)
BackgroundPopulation mobility is closely associated with COVID-19 transmission, and it could be used as a proximal indicator to predict future outbreaks, which could inform proactive nonpharmaceutical interventions for disease control. South Carolina
Externí odkaz:
https://doaj.org/article/7728efd6291d49d3adeee2fdc8537015
Autor:
Li, Zhenlong, Li, Xiaoming, Porter, Dwayne, Zhang, Jiajia, Jiang, Yuqin, Olatosi, Bankole, Weissman, Sharon
Publikováno v:
JMIR Research Protocols, Vol 9, Iss 12, p e24432 (2020)
BackgroundHuman movement is one of the forces that drive the spatial spread of infectious diseases. To date, reducing and tracking human movement during the COVID-19 pandemic has proven effective in limiting the spread of the virus. Existing methods
Externí odkaz:
https://doaj.org/article/7d4d770d29284413a727592aea13f094
Information on the depth of floodwater is crucial for rapid mapping of areas affected by floods. However, previous approaches for estimating floodwater depth, including field surveys, remote sensing, and machine learning techniques, can be time-consu
Externí odkaz:
http://arxiv.org/abs/2402.16684
Autor:
Li, Zhenlong, Ning, Huan
Large Language Models (LLMs), such as ChatGPT, demonstrate a strong understanding of human natural language and have been explored and applied in various fields, including reasoning, creative writing, code generation, translation, and information ret
Externí odkaz:
http://arxiv.org/abs/2305.06453
Multiple geographical feature label placement (MGFLP) has been a fundamental problem in geographic information visualization for decades. The nature of label positioning is proven an NP-hard problem, where the complexity of such a problem is directly
Externí odkaz:
http://arxiv.org/abs/2211.17215
Human movements in urban areas are essential to understand human-environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose a novel sensor-based approach
Externí odkaz:
http://arxiv.org/abs/2208.07969