09-09, 09:00–12:00 (America/Chicago), Holekamp Classroom
This workshop aims to bridge the gap between big geospatial data and research scientists by providing training on an open-source online platform for managing big drone and satellite data.
Recent advances in drone technology have revolutionized the remote sensing community by providing means to collect fine spatial and high temporal resolutions at affordable costs. As people are gaining access to increasingly larger volumes of drone and satellite geospatial data products, there is a growing need to extract relevant information from the vast amount of freely available geospatial data. However, the lack of specialized software packages tailored for processing such data makes it challenging to develop transdisciplinary research collaboration around them. This workshop aims to bridge the gap between big geospatial data and research scientists by providing training on an open-source online platform for managing big drone data known as Data to Science. Additionally, attendees will be introduced to powerful Python packages, namely Geemap and Leafmap, designed for the seamless integration and analysis of drone and satellite images in various applications. By participating in this workshop, attendees will acquire the skills necessary to efficiently search, visualize, and analyze geospatial data within a Jupyter environment, even with minimal coding experience. The workshop provides a hands-on learning experience through practical examples and interactive exercises, enabling participants to enhance their proficiency and gain valuable insights into leveraging geospatial data for various research purposes.
