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July 2020: LF Remap Advancements; Summer MoD-FIS release; NE / CONUS release
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LANDFIRE is Evolving!

Based on user feedback, the LANDFIRE Program is exploring options to provide annual product updates. To meet that need, LANDFIRE will be in a transition phase so users should be aware that there will be product changes over the next few update cycles as processes evolve. Providing your landscape disturbances (natural and human-caused) to LANDFIRE will be even more important in the future than the past, to be submitted by November 30th of each year. If you will submit your landscape changes directly to the LANDFIRE Program or data bases/sources we regularly utilize (FACTS, NFPORS, etc.), our commitment will be to track and incorporate those changes into LANDFIRE products more quickly than the past, and when update processes are fully tested and implemented, within a year of submission. We will provide details on what to expect in the next update cycle as they become available.

Picture: Steve S. Meyer, TNC. Pasque flowers at Schluckebier Sand Prairie, Wisconsin
After 15 Years, LANDFIRE Releases Remap:
New Techniques, New Data = Significant Improvement
Our understanding of land cover in the U.S. just got a little clearer. Yesterday LANDFIRE released the most significant upgrade in its 15-year history - LANDFIRE Remap project for the conterminous U.S. (CONUS). Gathering this data was anything but simple. Over 9 billion 30-meter pixels were used to generate this new, updated product suite. Users will find refined information on vegetation type and height, fuel sources and density, fire regimes, historical and annual disturbances and more. The level of continuous data and enhanced base maps in this Remap are unmatched when compared to other land cover products. With this release, LANDFIRE continues to be an essential behind the scenes driver for land managers and beyond.
 
Summer MoD-FIS is Now Available!
The Summer MoD-FIS (Modeling Dynamic Fuels with an Index System) is ready for download from the LF Data Distribution Site. This release covers the Northern Great Basin, portions of the Northwest, and the Southern region of the United States. In addition, and in response to user feedback, it also includes a change in extent to include areas of California coastal zones and some additional areas in the eastern zones. 
What is MoD-FIS? MoD-FIS captures the seasonal nature of fuels in these regions and incorporates seasonal variability of herbaceous cover (i.e. cheatgrass), to capture changes to fire behavior fuel models based on the current fire season herbaceous production. 
Using current and historic Normalized Difference Vegetation Index data from the Landsat archive and LF’s new base map suite of products (LF 2016 Remap), LF maps current year herbaceous cover compared to historic averages. The result is updated Existing Vegetation Cover, Existing Vegetation Height, and Fire Behavior Fuel Model layers that reflect the current fire season herbaceous cover and resultant fuel availability. 

 
Eyes on Earth, host John Hult interviews Randy Swaty, (LANDFIRE Ecologist), about the multi-agency federal program’s value, and about recent efforts to remap the United States to improve the LANDFIRE product suite.

Listen to this engaging interview produced by the team at EROS.
The LF Team presented to a group of TNC employees in the the Midwest Division on June 30. To accompany our presentation, we created this 1-pager that summarizes (just a few ways) LF data can be leveraged for conservation actions in the Midwest. 
Download the 1-pager here. 
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SAVE THE DATE:

What's new with the Wildfire Risk to Communities website? 
September 2020 | Details and registration link coming soon

LANDFIRE Remap in the Northeastern U.S.
October 21, 2020 | Details and registration link coming soon

New to our Webinar Library 
Recorded June 17, 2020
Good Reading...LF at work
New Publication: Enhancing Wildfire Spread Modelling by Building a Gridded Fuel Moisture Content Product with Machine Learning; Tyler C. McCandless, Branko Kosovic, and William Petzke; Machine Learning: Science and Technology in press https://doi.org/10.1088/2632-2153/aba480; July 2020

This study details how the authors built and trained complex machine learning models to build a high resolution, gridded fuel moisture content dataset from satellite observations for the entire Conterminous U.S. They measured the impacts of soil saturation and plant dynamics by using the National Water Model and estimating total evapotranspiration, soil moisture content and land use. LF land cover data was used in this model. The Fuel Moisture Content (FMC) gridded product based on the random forest runs operationally daily over CONUS and can be assimilated into the Weather Research and Forecast (WRF) fire model for more accurate wildland fire spread predictions. Their findings may be used to inform operational wildland fire-behavior (WRF-Fire) and may improve predictions of wildland fire spread.

Pictured below: Forest Whitewater - Baldy Complex wildfire, Gila National Forest, New Mexico, USA. Photo by Kari Greer. Credit USFS Gila National Forest.
LANDFIRE Business Leads
Henry Bastian
DOI Business Lead
Frank Fay
USFS Business Lead
Tim Hatten
USGS Project Manager
Jim Smith
TNC-LF Project Lead
Birgit Peterson
USGS-LF Technical Lead

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The LANDFIRE Program is a cooperative agreement between the USDA Forest Service, agencies of the Department of the Interior, and The Nature Conservancy. In accordance with Federal law and U.S. Department of Agriculture policy, the Program is prohibited from discriminating on the basis of race, color, national origin, sex, age, or disability.