A Deep Learning Approach for Surface PM2.5 Estimations from Geostationary Satellite and Numerical Model Data
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Manisha Khatri↗
Engineering topics
Aaron S Kaulfus
Publications and source records attributed to Aaron S Kaulfus.
Supporting Open Science through Cloud-Based and Interoperable APIs for Data Access and Visualization: The Multi-Mission Algorithm and Analysis Platform (MAAP) Data System
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Aimee Barciauskas↗
Influence Network: Network visualization of influence between stories for Earth Science data and information exploration
Using storytelling to present data has been demonstrated as an effective way to help data users gain deeper insight of information. For this purpose, the “Data in Action” story concept has been adopted by NASA Commercial Smallsat Data Acquisition (CSDA) Program to encourage creating and sharing data information in story form. To aid researchers in exploring similar stories and data in their fields of interest, we created an “Influence Network” within the “Data in Action” framework. The Influence Network is a data visualization system component which gathers information of story relationships using a concept called “influence,” which we define based on the number of visits and keyword similarity between stories. The visualization then provides insights into the influence flows between different stories within the system. The visualization of this “Influence Network” focuses on one story at a time, introducing a time series of neighbor stories that have the most influence to the currently focused story. By focusing on views over time and visualizing influence flows between stories, we aim to assist authors in understanding how their readers perceive their stories as well as advancing their methods for delivering more meaningful stories to expand and lower the barrier to use of CSDA datasets.
Dan Pham↗
Using High-Resolution Planet Data to Retrieve Aerosol Properties for the 2020 Wildfire Events
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Ankur Kumar↗
SREDD: Framework to facilitate MLopS related to discovery of commercial satellite data
SREDD or Super Resolution Event Detection Dashboard is a comprehensive data discovery platform designed to facilitate the identification of multiple events. It is equipped to handle data of varying spatial resolutions and from various vendors, acquired by NASA’s Commercial Smallsat Data Acquisition (CSDA) Program, making it a convenient centralized hub for searching event-related information.
Sujit Roy↗