activity
20242026
collaborators

7 papers

cs.CV2026

Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications

Daniela Szwarcman, Sujit Roy, Paolo Fraccaro +33

This paper presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2 million global time…

cs.CY2026

Measuring Research Convergence in Interdisciplinary Teams Using Large Language Models and Graph Analytics

Wenwen Li, Yuanyuan Tian, Sizhe Wang +8

Understanding how interdisciplinary research teams converge on shared knowledge is a persistent challenge. This paper presents a novel, multi-layer, AI-driven analytical framework…

cs.CV2025

Landslide Hazard Mapping with Geospatial Foundation Models: Geographical Generalizability, Data Scarcity, and Band Adaptability

Wenwen Li, Sizhe Wang, Hyunho Lee +4

Landslides cause severe damage to lives, infrastructure, and the environment, making accurate and timely mapping essential for disaster preparedness and response. However, conventi…

cs.CV2025

A multi-scale vision transformer-based multimodal GeoAI model for mapping Arctic permafrost thaw

Wenwen Li, Chia-Yu Hsu, Sizhe Wang +4

Retrogressive Thaw Slumps (RTS) in Arctic regions are distinct permafrost landforms with significant environmental impacts. Mapping these RTS is crucial because their appearance se…

cs.DB2025

The KnowWhereGraph: A Large-Scale Geo-Knowledge Graph for Interdisciplinary Knowledge Discovery and Geo-Enrichment

Rui Zhu, Cogan Shimizu, Shirly Stephen +25

Global challenges such as food supply chain disruptions, public health crises, and natural hazard responses require access to and integration of diverse datasets, many of which are…

cs.CV2024

Enhancing GeoAI and location encoding with spatial point pattern statistics: A Case Study of Terrain Feature Classification

Sizhe Wang, Wenwen Li

This study introduces a novel approach to terrain feature classification by incorporating spatial point pattern statistics into deep learning models. Inspired by the concept of loc…