SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery

arXiv:2311.17179v3 Announce Type: replace-cross
Abstract: Geographic information is essential for modeling tasks in fields ranging from ecology to epidemiology. However, extracting relevant location characteristics for a given task can be challenging, often requiring expensive data fusion or distillation from massive global imagery datasets. To address this challenge, we introduce Satellite Contrastive Location-Image Pretraining (SatCLIP). This global, general-purpose geographic location encoder learns an implicit representation of locations by matching CNN and ViT inferred visual patterns of openly available satellite imagery with …

abstract arxiv challenge cs.ai cs.cv cs.cy cs.lg data datasets distillation ecology embeddings epidemiology fields fusion general global however image information location massive modeling satellite tasks type