Modular Open-Source Geospatial Data Science Ecosystem for Climate and Community Resilience 08/11/25 скачать в хорошем качестве

Modular Open-Source Geospatial Data Science Ecosystem for Climate and Community Resilience 08/11/25

Data to Science (D2S): Modular Open-Source Geospatial Data Science Ecosystem for Climate and Community Resilience Part of GPN's Climate and Community Resilience series, this webinar discusses recent advancements in sensor technologies that enable high-resolution remote sensing and automated feature extraction. The development of big data from UAVs (Uncrewed Aerial Vehicles) has been driven by continuous improvements in UAV hardware, providing substantial operational flexibility and allowing individuals or small research teams to collect high-quality geospatial data over regional areas at reasonable costs. This widespread adoption of UAV technology has led to an unprecedented volume of UAV data, much of which remains untouched for analysis, not to mention the sharing of big data for multidisciplinary collaboration. Although this data has the potential to revolutionize our understanding of many complex issues, a recent community survey reveals that researchers lack comprehensive tools and step-by-step protocols for UAV data processing pipelines, as well as trained personnel for analyzing UAV data. Furthermore, existing tools for analyzing geospatial data are often expensive, not open-source, and not integrated to enable a ‘user-friendly’ end-to-end analysis from image to quantitative information. For these reasons, the management of large volumes of geospatial data and the absence of FAIR (Findable, Accessible, Interoperable, and Reusable) infrastructure designed for big geospatial data hampers research collaboration among scientists from various disciplines. To address these challenges, we introduce Data to Science (D2S), an open-source online platform for managing large geospatial datasets. D2S includes a web application, QGIS plugin, Python library, and STAC (Spatio Temporal Archive Catalog), allowing users to upload, manage, and visualize geospatial data products generated from any mapping modality. The platform converts data into cloud-native formats, offers interactive visualizations, supports access control, and enables users to create new data products and perform analyses. This presentation provides an overview of the D2S architecture, explores several use cases of D2S in research applications such as precision agriculture and digital forestry, and demonstrates the modular design of D2S that can potentially be utilized for climate and community resilience GIS applications. Speaker: Dr. Jinha Jung, Associate Professor, School of Civil and Construction Engineering, Purdue University Moderator: Kevin Mickey, Director Professional Development and Geospatial Technologies Education, The Polis Center Luddy School of Informatics, Computing, and Engineering