Results 111 to 120 of about 1,791 (210)
GeoAI Reproducibility and Replicability: a computational and spatial perspective
GeoAI has emerged as an exciting interdisciplinary research area that combines spatial theories and data with cutting-edge AI models to address geospatial problems in a novel, data-driven manner.
Hsu, Chia-Yu +3 more
core
Cross-Modal Learning of Housing Quality in Amsterdam
In our research we test data and models for the recognition of housing quality in the city of Amsterdam from ground-level and aerial imagery. For ground-level images we compare Google StreetView (GSV) to Flickr images.
Levering, Alex +2 more
core +1 more source
Special issue on geospatial artificial intelligence. [PDF]
Geoinformatica, 2023 Gao S, Hu Y, Li W, Zou L.
europepmc +1 more source
25th Annual Assembly of the Croatian Cartographic Society [PDF]
Dvadesetpeta godišnja skupština Hrvatskoga kartografskog društva (HKD) održana je 5. 12. 2024. s početkom u17:00 sati na Geodetskom fakultetu Sveučilišta u Zagrebu.The 25th Annual Assembly of the Croatian Cartographic Society (CCS) was held on 5 December
Kljajić, Ivka
core +1 more source
Geospatial Location Embedding (GLE) helps a Large Language Model (LLM) assimilate and analyze spatial data. GLE emergence in Geospatial Artificial Intelligence (GeoAI) is precipitated by the need for deeper geospatial awareness in our complex ...
Tucker, Sean
core
Beyond Maps: advancing geospatial AI with multimodal foundation models [PDF]
LAUREA MAGISTRALEL'uso delle tecnologie IA nei flussi di elaborazione dati per compiti correlati alla geospazialità è stato al centro dell'interesse di molti individui sia nel campo professionale che accademico.
DIAB, MOHANAD YOUSEF AHMAD
core
Vision-Language Models (VLMs) in GeoAI Systems: Enhancing Brownfield Change Detection through Semantic Reasoning [PDF]
This paper presents a hybrid GeoAI methodology for semantic change detection in satellite imagery by integrating Vision–Language Models (VLMs) into an unsupervised clustering-based pipeline.
Dürrbeck, Konrad +5 more
core +1 more source
An Ensemble Framework for Explainable Geospatial Machine Learning Models
Analyzing spatial varying effect is pivotal in geographic analysis. Yet, accurately capturing and interpreting this variability is challenging due to the complexity and non-linearity of geospatial data.
Liu, Lingbo
core
Harnessing Geospatial Artificial Intelligence (GeoAI) for Environmental Epidemiology: A Narrative Review. [PDF]
Curr Environ Health RepIyer HS +5 more
europepmc +1 more source
Statistical Downscaling of Climate Datasets with Deep Generative Model and Bayesian inference [PDF]
Facing the challenges of global climate change, precise and high spatial resolution climate data are crucial and in pressing need for scientific research and analysis. However, most existing datasets are only available with very coarse spatial resolution
Cao, Guofeng, Li, Guiye
core +1 more source