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San Jose State demonstrates Fuel Moisture Repository with mapping, plotting and CSV export
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Summary
San Jose State researchers demonstrated an internal Fuel Moisture Repository (FMR) web portal that maps fuel-sampling sites, lets users filter by fuel type and date range, produces plots (current year, historical average and historical low) and exports CSVs. The team said the portal will ingest FEMs API data soon but currently lacks samples collected after the national site outage in early March.
San Jose State University researchers on a conference call demonstrated a Fuel Moisture Repository web portal designed to mirror and extend the National Fuel Moisture Database’s visualization and export features. The portal shows a U.S. map of sampling sites, lets users filter by fuel type and date range, plots current and historical fuel-moisture values and downloads selected data as CSV files.
The project, led by the Wildfire Interdisciplinary Research Center Fire Modeling Group, uses an SQLite backend and a Python library paired with a Flask and JavaScript interface to make the data easy to query and use, the presenters said. Angel, a postdoctoral research associate with the group, described the national product as “the most comprehensive public fuel sampling database,” and said the local repository was created after the national web interface stopped working.
“My name is Jack Drucker,” said Jack Drucker, who identified himself as a former San Jose State student and the original developer now working at NOAA. “This was initially just an internal tool, but we put it out on the web so that anyone can access it.” Drucker demonstrated the portal’s landing map, which shows colored markers for sites and a color bar keyed to fuel-moisture percentage. He showed how selecting a fuel type updates site lists and the map’s color scale and how separate color scales can be used for live and dead fuels.
Drucker walked attendees through three plot types. One line shows the current year’s values for a selected station or group of stations, a second shows the historical average and a third shows historical low values. A polygon selection tool lets users aggregate many nearby stations into a single plot; a separate view displays the number of observations for the selected fuel types and time range. He also demonstrated a download-data button that compiles the selection into a CSV organized by station ID, fuel type, variation and sample date.
The presenters said the portal is especially useful for teams that need low-bandwidth access or a stable, consistent dataset for climatological analysis. “Those kinds of heavy GIS services are not always easy to work with, especially if you have a low bandwidth,” said one attendee during the discussion of design choices.
The team said the codebase includes a back end stored in a public repository and that endpoints are available for programmatic queries. Drucker said users can retrieve data by station ID, state and time frame for import into Excel or other analysis tools. The presenters invited feedback and feature requests; attendees requested an ability to overlay nonconsecutive years (for example, 2006 and 2012) and year-specific plotting options, which the developers said could be added.
The call ended with hosts thanking the San Jose State team and inviting continued collaboration and suggestions.
