AutoGEEval: A Multimodal and Automated Evaluation Framework for Geospatial Code Generation on GEE with Large Language Models

AutoGEEval: A Multimodal and Automated Evaluation Framework for Geospatial Code Generation on GEE with Large Language Models

Geospatial code generation is emerging as a key direction in the integration of artificial intelligence and geoscientific analysis. However, there remains a lack of standardized tools for automatic evaluation in this domain. To address this gap, we propose AutoGEEval, the first multimodal, unit-leve...

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Bibliographic Details
Main Authors: Huayi Wu, Zhangxiao Shen, Shuyang Hou, Jianyuan Liang, Haoyue Jiao, Yaxian Qing, Xiaopu Zhang, Xu Li, Zhipeng Gui, Xuefeng Guan, Longgang Xiang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
geospatial code generation
large language models
Google Earth Engine
automated evaluation
unit test benchmark
Online Access:https://www.mdpi.com/2220-9964/14/7/256
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