Uncertainty-Aware Enrichment of Animal Movement Trajectories by VGI DOI Creative Commons
Yannick Metz, Daniel A. Keim

Published: Dec. 8, 2023

Abstract Combining data from different sources and modalities can unlock novel insights that are not available by analyzing single in isolation. We investigate how multimodal user-generated data, consisting of images, videos, or text descriptions, be used to enrich trajectories migratory birds, e.g., for research on biodiversity climate change. Firstly, we present our work advanced visual analysis GPS trajectory data. developed an interactive application lets domain experts ornithology naturally explore spatiotemporal effectively use their knowledge. Secondly, discuss the integration general-purpose image into citizen science platforms. As part inter-project cooperation, contribute development a classifier pipeline semi-automatically extract images integrated with vastly increase number records These works important foundation dynamic matching approach jointly integrate geospatial geo-referenced content. Building this work, joint visualization VGI while considering uncertainty observations. BirdTrace , analytics enable multi-scale is highlighted. Finally, comment possibility enhance prediction models integrating additional

Language: Английский

Crowdsourcing Canada Goldenrod Identification from Multimodal Weibo Data DOI
Jia Shang, Wei Yu, Junpeng Chen

et al.

Published: Dec. 16, 2024

Language: Английский

Citations

0
Uncertainty-Aware Enrichment of Animal Movement Trajectories by VGI DOI Creative Commons
Yannick Metz, Daniel A. Keim

Published: Dec. 8, 2023

Abstract Combining data from different sources and modalities can unlock novel insights that are not available by analyzing single in isolation. We investigate how multimodal user-generated data, consisting of images, videos, or text descriptions, be used to enrich trajectories migratory birds, e.g., for research on biodiversity climate change. Firstly, we present our work advanced visual analysis GPS trajectory data. developed an interactive application lets domain experts ornithology naturally explore spatiotemporal effectively use their knowledge. Secondly, discuss the integration general-purpose image into citizen science platforms. As part inter-project cooperation, contribute development a classifier pipeline semi-automatically extract images integrated with vastly increase number records These works important foundation dynamic matching approach jointly integrate geospatial geo-referenced content. Building this work, joint visualization VGI while considering uncertainty observations. BirdTrace , analytics enable multi-scale is highlighted. Finally, comment possibility enhance prediction models integrating additional

Language: Английский

Citations

0