Data to science: an open-source online platform for managing, visualizing, and publishing UAS data
Jinha Jung, Songlin Fei, Mitchell R. Tuinstra, Yang Yang, Diane Wang, Carol Song, Jeffrey K. Gillan, Mahendra Bhandari, Amir Ibrahim, Lan Zhao, Tyson L. Swetnam, Bryan Barker, Minyoung Jung, Benjamin G. Hancock · 2024
Recent advancements in sensor technologies make it possible to collect fine spatial and high temporal resolution remote sensing data and automatically extract informative features in a high throughput mode. As researchers increasingly have access to tools to collect big data, such as Unmanned Aerial Vehicles (UAV) and Controlled Environment Phenotyping Facility (CEPF), there is a need for generating quantitative phenotypic from the collected geospatial data. While precision agriculture technology aims to protect our environment and produce enough food to feed a growing population, the massive volume of geospatial data generated by the research scientists and the lack of software packages customized for processing these data make it challenging to develop transdisciplinary research collaboration around this data. We will share our efforts to develop an open-source online platform for UAS HTP data management to address the big data challenges.