Treffer: Bringing Analysis Closer to Data: Developing a Visualization Tool for L2 Earth Science Satellite Data

Title:
Bringing Analysis Closer to Data: Developing a Visualization Tool for L2 Earth Science Satellite Data
Publisher Information:
United States: NASA Center for Aerospace Information (CASI), 2019.
Publication Year:
2019
Subject Terms:
Document Type:
Report Report
Language:
English
Notes:
80GSFC17C0003
Accession Number:
edsnas.20200002000
Database:
NASA Technical Reports

Weitere Informationen

Earth Science satellite missions provide a unique opportunity for scientists to visualize complex and multifaceted observations projected geospatially across maps of the Earth. While visualization tools can help scientists comprehend, analyze, and share data, visualizing Level-2 Earth Sciences data poses its own specific set of challenges. Since the geospatial information in Level-2 data files is stored as independent variables, the plotting process involves matching dimensional information from latitude and longitude with a desired variable. Variables are stored in different ways across various Earth Science data file formats, which complicates the process of extracting data and plotting variables from a given file without requiring extensive user input and prerequisite familiarity with the file type variable structure. In coordination with NASA’s Goddard Earth Sciences Data Information Services Center (GES DISC), the team developed a Level-2 Earth Science data visualization tool that aims to address some of the complexities associated with plotting Level-2 data. This tool offers command-line and user interface support for file and variable selection to accommodate varying use cases and degrees of user familiarity with the structure of a given file. The visualization tool is written in Python 3 and utilizes a modular approach to facilitate continued expansion and reuse. In addressing some common complications involved in plotting Level-2 Earth Sciences data, the tool aims to help to link the process of analysis more directly with data acquisition and visualization, bringing analysis closer to data across levels of processing.