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The LANDFIRE (LF) Program investigates ways to ensure LF products remain relevant, useful, and accessible to the user community through improvements and innovations. Improvements and innovations are enhancements to current data production methods as well as the advancement of new scientific methods and information sources.
Learn how LF strives to produce the best data available at a national scale with the latest topics in improvements and innovations:
|BpS Settings Review
LF models and descriptions represent how Biophysical Settings (BpS) looked and worked prior to major European settlement. Learn more...
LF scientists are exploring the use of lidar data for canopy structure mapping. Incorporating lidar data into vegetation mapping methods has shown to be promising, however it is still being investigated. Learn more...
|LF Modeling Dynamic-Fuels with an Index (LF MoD-FIS) - Southeast U.S.
In order to improve the functionality of the fuel products, LF has proposed the use of the Drought Based Fuel Dynamic (LF_DBFD) system. The LF_DBFD system systematically transitions surface fuel models based on seasonal conditions, by addressing fuel loading and fuelbed depth. Learn more...
|LF Modeling Dynamic-Fuels with an Index (LF MoD-FIS) - Southwest U.S.
In an effort to capture the inter-annual variability in herbaceous growth and the corresponding impact on available fuels, LF has developed a method to seasonally modulate fuel model data in the Great Basin and Southwest regions. Learn more...
|SCLASS into LF Total Fuels Change Toolbar
Succession Class (SCLASS) was added as a new functionality to the LF Total Fuel Change Toolbar (LFTFCT). The SCLASS addition will be helpful for those who use ArcMap to create fuel layers because fuel and succession class mapping rules can be translated into spatial layers. Learn more...
This LF innovation describes a tiling and compositing approach using Landsat data in order to produce better change detection maps. Learn more...
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