.png){kind=icon}
返回
An autonomous GIS agent framework for geospatial data retrieval
.png){kind=icon}
OA
AI
DOI：10.1080/17538947.2025.2458688.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Powered by the emerging large language models (LLMs), autonomous geographic information system (GIS) agents can perform spatial analyses and cartographic tasks. However, a research gap exists in enabling these agents to autonomously discover and retrieve the necessary data for spatial analysis. This study proposes an autonomous GIS agent framework capable of retrieving required geospatial data by generating, executing, and debugging programs. The framework, with an LLM-driven decision core, selects data sources from a predefined list and fetches data using source-specific handbooks that document metadata and data retrieval details. Designed in a plug-and-play style, the framework allows human users or automated data crawlers to add new sources by creating additional handbooks. A prototype agent based on the framework is developed and released as a QGIS plugin and a Python program. Experiment results demonstrate its capability of retrieving data from various sources, including OpenStreetMap, administrative boundaries and demographic data from the U.S. Census Bureau, satellite basemaps from ESRI World Imagery, global digital elevation model (DEM) from OpenTopography.org, weather data from a commercial provider, and the COVID-19 case data from the NYTimes GitHub. This study is among the first attempts to develop an autonomous GIS agent for geospatial data retrieval.
Keyword:
Autonomous GIS
geospatial data retrieval
large language models
generative AI
GIS agent
AI assistant
期刊
IF:
4.9
论文数:
2.0K
被引数:
4.7K
机构
引用论文
.png){kind=icon}
GPT, large language models (LLMs) and generative artificial intelligence (GAI) models in geospatial science: a systematic review地理空间科学中的GPT、大型语言模型 (llm) 和生成式人工智能 (GAI) 模型: 系统综述OAAI
OAAI分享收藏Approximation of the stiffness of laminate stacks of electric motors subjected to cyclic loads电机的层压堆叠在循环载荷作用下的刚度近似计算
PREAI
分享收藏Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages地理知识引导的GPT模型改进了从与灾难相关的社交媒体消息中提取位置描述OAAI
OAAI分享收藏
分享收藏 没有更多内容
没有更多内容