52 citations · 108 across the 9 of their papers we have counts for
10 papers
AEF-Econ: Toward Plug-and-Play Socioeconomic Foundation Embeddings from AlphaEarth for Urban Remote Sensing
Shuyang Hou, Ziqi Liu, Haoyue Jiao +7
AlphaEarth Foundations (AEF) unify global remote sensing foundation embeddings through multimodal self-supervised learning, but their pretraining focuses on physical land-surface s…
Slum Detection and Density Mapping with AlphaEarth Foundations: A Representation Learning Evaluation Across 12 Global Cities
Shuyang Hou, Ziqi Liu, Haoyue Jiao +7
Pixel-level slum mapping has long been constrained by limited cross-city generalisation, the absence of continuous density estimation, and weak global comparability. AlphaEarth Fou…
GP-Tree: An in-memory spatial index combining adaptive grid cells with a prefix tree for efficient spatial querying
Xiangyang Yang, Xuefeng Guan, Lanxue Dang +4
Efficient spatial indexing is crucial for processing large-scale spatial data. Traditional spatial indexes, such as STR-Tree and Quad-Tree, organize spatial objects based on coarse…
GeoSQL-Eval: First Evaluation of LLMs on PostGIS-Based NL2GeoSQL Queries
Shuyang Hou, Haoyue Jiao, Ziqi Liu +5
Large language models (LLMs) have shown strong performance in natural language to SQL (NL2SQL) tasks within general databases. However, extending to GeoSQL introduces additional co…
GeoJSEval: An Automated Evaluation Framework for Large Language Models on JavaScript-Based Geospatial Computation and Visualization Code Generation
Guanyu Chen, Haoyue Jiao, Shuyang Hou +6
With the widespread adoption of large language models (LLMs) in code generation tasks, geospatial code generation has emerged as a critical frontier in the integration of artificia…
AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
Shuyang Hou, Zhangxiao Shen, Huayi Wu +10
Geospatial code generation is becoming a key frontier in integrating artificial intelligence with geo-scientific analysis, yet standardised automated evaluation tools for this task…
AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models
Shuyang Hou, Zhangxiao Shen, Huayi Wu +8
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 to…
GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks
Shuyang Hou, Zhangxiao Shen, Anqi Zhao +5
The increasing demand for spatiotemporal data and modeling tasks in geosciences has made geospatial code generation technology a critical factor in enhancing productivity. Although…
Forecast Network-Wide Traffic States for Multiple Steps Ahead: A Deep Learning Approach Considering Dynamic Non-Local Spatial Correlation and Non-Stationary Temporal Dependency
Xinglei Wang, Xuefeng Guan, Jun Cao +2
Obtaining accurate information about future traffic flows of all links in a traffic network is of great importance for traffic management and control applications. This research st…
A Hybrid Traffic Speed Forecasting Approach Integrating Wavelet Transform and Motif-based Graph Convolutional Recurrent Neural Network
Na Zhang, Xuefeng Guan, Jun Cao +2
Traffic forecasting is crucial for urban traffic management and guidance. However, existing methods rarely exploit the time-frequency properties of traffic speed observations, and…