AgenticCity-Bench: Longitudinal Multimodal Observations of Urban Dynamics with Agentic Reasoning

City systems are shaped by interactions among infrastructure, human activity, and environmental conditions. Existing earth observation and urban benchmarks are limited in unified modeling and in capturing their joint dynamics. We introduce AgenticCity-Bench, a longitudinal multimodal benchmark for multi-layer unified state modeling and agentic city task reasoning. The benchmark covers 16 cities in 12 countries across six continents from 2000 to 2025, and includes 18 modalities spanning urban function, activity, and environmental state. It organizes heterogeneous data sources around a common spatial reference and calendar index while preserving spatial and temporal coverage, provenance and tile-level availability. On this foundation, AgenticCity-Bench supports urban cross-modal translation together with diverse agentic city tasks involving forecasting, planning and resource analysis. This study provides a unified benchmark for studying the transition from multimodal urban and earth observation to joint understanding and agentic city decision-making. The dataset is available at https://anonymous.4open.science/r/AgenticCity-Bench.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-26
DOI
https://doi.org/10.48550/arxiv.2610.35293
Primary Topic
Smart Cities and Technologies
Type
preprint
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preprint

AgenticCity-Bench: Longitudinal Multimodal Observations of Urban Dynamics with Agentic Reasoning

Yanyu Mao, Heye Huang, Baotong Mi, Kailai Sun et al.
arXiv (Cornell University)
Smart Cities and Technologies
preprint

AgenticCity-Bench: Longitudinal Multimodal Observations of Urban Dynamics with Agentic Reasoning

Yanyu Mao, Heye Huang, Baotong Mi, Kailai Sun, Baoshen Guo, Alok Prakash, Xiaofei Yu, Yongcai WANG, Shenhao Wang, Jinhua Zhao
preprint en

Abstract

City systems are shaped by interactions among infrastructure, human activity, and environmental conditions. Existing earth observation and urban benchmarks are limited in unified modeling and in capturing their joint dynamics. We introduce AgenticCity-Bench, a longitudinal multimodal benchmark for multi-layer unified state modeling and agentic city task reasoning. The benchmark covers 16 cities in 12 countries across six continents from 2000 to 2025, and includes 18 modalities spanning urban function, activity, and environmental state. It organizes heterogeneous data sources around a common spatial reference and calendar index while preserving spatial and temporal coverage, provenance and tile-level availability. On this foundation, AgenticCity-Bench supports urban cross-modal translation together with diverse agentic city tasks involving forecasting, planning and resource analysis. This study provides a unified benchmark for studying the transition from multimodal urban and earth observation to joint understanding and agentic city decision-making. The dataset is available at https://anonymous.4open.science/r/AgenticCity-Bench.

arXiv (Cornell University)
Smart Cities and Technologies
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AgenticCity-Bench: Longitudinal Multimodal Observations of Urban Dynamics with Agentic Reasoning — Yanyu Mao, Heye Huang, et al. · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS