7 papers
Spatial Representation Learning Beyond Pixels: Unifying Raster Data and Vector Semantics for Human-Centric Geospatial Foundation Models
Steffen Knoblauch, Hao Li, Gengchen Mai +3
Earth Observation (EO) has fundamentally transformed the monitoring of environmental processes and human activities up to planetary scale. Recent advances in self-supervised learni…
NARA: Anchor-Conditioned Relation-Aware Contextualization of Heterogeneous Geoentities
Jina Kim, Gengchen Mai, Lingyi Zhao +2
Geospatial foundation models have primarily focused on raster data such as satellite imagery, where self-supervised learning has been widely studied. Vector geospatial data instead…
TRAJGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations
Maria Despoina Siampou, Gengchen Mai, Ni Lao +4
Multimodal self-supervised learning (MSSL) has emerged as a key paradigm for pretraining geospatial foundation models. However, existing geospatial MSSL methods are mainly designed…
Spatial-Agent: Agentic Geo-spatial Reasoning with Scientific Core Concepts
Riyang Bao, Cheng Yang, Dazhou Yu +3
Geospatial reasoning is essential for real-world applications such as urban analytics, transportation planning, and disaster response. However, existing LLM-based agents often fail…
Spatial-RAG: Spatial Retrieval Augmented Generation for Real-World Geospatial Reasoning Questions
Dazhou Yu, Riyang Bao, Ruiyu Ning +3
Answering real-world geospatial questions--such as finding restaurants along a travel route or amenities near a landmark--requires reasoning over both geographic relationships and…
ZooplanktonBench: A Geo-Aware Zooplankton Recognition and Classification Dataset from Marine Observations
Fukun Liu, Adam T. Greer, Gengchen Mai +1
Plankton are small drifting organisms found throughout the world's oceans and can be indicators of ocean health. One component of this plankton community is the zooplankton, which…