LANDFIRE's (LF) Biophysical Settings (BPS) product (https://www.landfire.gov/bps.php) represents the vegetation system that may have been dominant on the landscape prior to Euro-American settlement. BPS is based on both the current biophysical environment and an approximation of the historical disturbance regime. Map units are based on NatureServe's Ecological Systems classification and represent the natural plant communities that may have been present during the reference period. Each BPS map unit is matched with a model of vegetation succession and both serve as key inputs to the LANDSUM landscape succession model (Keane et al. 2006). The actual time period for this data set is determined by historical context provided by the fire regime, vegetation system dynamics modeling, and the recent field and geospatial inputs used to create it. Weather data from the Daily Surface Weather and Climatological Summaries database [(DAYMET) https://daymet.ornl.gov/) were compiled from 1980 to 1997. LF uses BPS to depict reference conditions of vegetation systems across landscapes and should not be regarded as a representation of existing vegetation. LF Remap BPS is unchanged from LF Nationals BPS except for updates made to water, barren and snow classes (additions or removal), so that not vegetated cover types within the spatial BPS product matches LF existing vegetation and fuel products.

LANDFIRE's (LF) Annual Disturbance (Dist) product provides temporal and spatial information related to landscape change. Dist depicts areas that have experienced a disturbance within a given year of 4.5 hectares (11 acres) or larger, along with cause and severity. Information sources include national fire mapping programs such as Monitoring Trends in Burn Severity (MTBS), Burned Area Reflectance Classification (BARC), and Rapid Assessment of Vegetation Condition after Wildfire (RAVG), local user/agency contributed data (LF Events Geodatabase), and remotely sensed Landsat imagery. Composite Landsat image pairs from the current year, prior year, and following year are spectrally compared to determine where change occurred and its corresponding severity. Additionally, vegetation indices (Normalized Differenced Vegetation Index [NDVI] and Normalized Burn Ratio [NBR]) serve as inputs into the Multi-Index Integrated Change Algorithm (MIICA) (Jin et al. 2013); MIICA outputs and differenced products (e.g., dNDVI and dNBR) are used to locate change. Predictive modeling based on the previous 10 years of disturbance data provides an additional dataset useful for locating disturbance. Image analysts use the aforementioned datasets separately or in combination to isolate true change from false change (e.g., change caused by stark differences in phenology rather than a true disturbance event). The accuracy of the final product is often related to the quality of the Landsat image composite. Areas with persistent cloud cover are particularly challenging (e.g., the northeast US). Fire caused disturbances sourced from MTBS may contain data gaps where clouds, smoke, water or Landsat7 SLC-off stripes exist. Models trained from pre-fire and post-fire Landsat data are used to fill the gaps. The result is continuous severity and extent information for all MTBS fire disturbances. MTBS pixels derived from gap filling techniques, such as modeling, are noted as such in their corresponding attribute table. Smaller fires that do not meet the size criteria set forth by MTBS) may be attributed as a Burned Area Essential Climate Variable (BAECV), which are only produced for the lower 48 states. Causality and severity information assigned to a disturbance are prioritized by source, with the highest priorities reserved for fire mapping programs (MTBS, BARC and RAVG) followed by user-contributed events contained in the LF Events Geodatabase, and lastly, Landsat image based change.

LANDFIRE's (LF) Annual Disturbance (Dist) product provides temporal and spatial information related to landscape change. Dist depicts areas that have experienced a disturbance within a given year of 4.5 hectares (11 acres) or larger, along with cause and severity. Information sources include national fire mapping programs such as Monitoring Trends in Burn Severity (MTBS), Burned Area Reflectance Classification (BARC), and Rapid Assessment of Vegetation Condition after Wildfire (RAVG), local user/agency contributed data (LF Events Geodatabase), and remotely sensed Landsat imagery. Composite Landsat image pairs from the current year, prior year, and following year are spectrally compared to determine where change occurred and its corresponding severity. Additionally, vegetation indices (Normalized Differenced Vegetation Index [NDVI] and Normalized Burn Ratio [NBR]) serve as inputs into the Multi-Index Integrated Change Algorithm (MIICA) (Jin et al. 2013); MIICA outputs and differenced products (e.g., dNDVI and dNBR) are used to locate change. Predictive modeling based on the previous 10 years of disturbance data provides an additional dataset useful for locating disturbance. Image analysts use the aforementioned datasets separately or in combination to isolate true change from false change (e.g., change caused by stark differences in phenology rather than a true disturbance event). The accuracy of the final product is often related to the quality of the Landsat image composite. Areas with persistent cloud cover are particularly challenging (e.g., the northeast US). Fire caused disturbances sourced from MTBS may contain data gaps where clouds, smoke, water or Landsat7 SLC-off stripes exist. Models trained from pre-fire and post-fire Landsat data are used to fill the gaps. The result is continuous severity and extent information for all MTBS fire disturbances. MTBS pixels derived from gap filling techniques, such as modeling, are noted as such in their corresponding attribute table. Smaller fires that do not meet the size criteria set forth by MTBS) may be attributed as a Burned Area Essential Climate Variable (BAECV), which are only produced for the lower 48 states. Causality and severity information assigned to a disturbance are prioritized by source, with the highest priorities reserved for fire mapping programs (MTBS, BARC and RAVG) followed by user-contributed events contained in the LF Events Geodatabase, and lastly, Landsat image based change.

Slope was produced from the IA DEM using ESRIs Slope tool. Output measurement for slope was both Degrees and Percent Rise (2 files produced).

Slope was produced from the IA DEM using ESRIs Slope tool. Output measurement for slope was both Degrees and Percent Rise (2 files produced).

LANDFIRE's (LF) Remap Vegetation Condition Class (VCC) is a reclassification and categorization of the LF Remap Vegetation Departure (VDep) product. VCC indicates the general level to which current vegetation is different from the simulated historical reference condition. Therefore, VCC is a derivative of VDep; the VDep product indicates how different current vegetation is compared to the estimated historical reference condition, and is based on change to species composition, structure, and canopy closure. To learn more about VCC and VDep go to https://www.landfire.gov/fireregime.php. Condition classes for VCC are defined in two ways; the original 3 category system from Fire Regime Condition Class Guidebook (FRCC Guidebook), and a newer 6 category system that provides additional precision. For the original 3 category system, the VDep value is reclassified as: Condition Class I: VDep value from 0 to 33 (Low Departure), Class II: VDep value between 34 - 66 (Moderate Departure), and Condition Class III: VDep value from 67 to 100 (High Departure). The 6 category system provides more resolution to VCC and is collapsible to the 3 category system. The 6 VCC categories are defined as: Condition Class I.A: VDep between 0 and 16 (Very Low Departure), Condition Class I.B: VDep between 17 and 33 (Low to Moderate Departure); Condition Class II.A: VDep between 34 and 50 (Moderate to Low Departure); Condition Class II.B: VDep between 51 and 66 (Moderate to High Departure); Condition Class III.A: VDep between 67 and 83 (High to Moderate Departure), and Condition Class III.B: VDep between 84 and 100 (High Departure).

LANDFIRE's (LF) Remap Vegetation Condition Class (VCC) is a reclassification and categorization of the LF Remap Vegetation Departure (VDep) product. VCC indicates the general level to which current vegetation is different from the simulated historical reference condition. Therefore, VCC is a derivative of VDep; the VDep product indicates how different current vegetation is compared to the estimated historical reference condition, and is based on change to species composition, structure, and canopy closure. To learn more about VCC and VDep go to https://www.landfire.gov/fireregime.php. Condition classes for VCC are defined in two ways; the original 3 category system from Fire Regime Condition Class Guidebook (FRCC Guidebook), and a newer 6 category system that provides additional precision. For the original 3 category system, the VDep value is reclassified as: Condition Class I: VDep value from 0 to 33 (Low Departure), Class II: VDep value between 34 - 66 (Moderate Departure), and Condition Class III: VDep value from 67 to 100 (High Departure). The 6 category system provides more resolution to VCC and is collapsible to the 3 category system. The 6 VCC categories are defined as: Condition Class I.A: VDep between 0 and 16 (Very Low Departure), Condition Class I.B: VDep between 17 and 33 (Low to Moderate Departure); Condition Class II.A: VDep between 34 and 50 (Moderate to Low Departure); Condition Class II.B: VDep between 51 and 66 (Moderate to High Departure); Condition Class III.A: VDep between 67 and 83 (High to Moderate Departure), and Condition Class III.B: VDep between 84 and 100 (High Departure).

LANDFIRE's (LF) Annual Disturbance (Dist) product provides temporal and spatial information related to landscape change. Dist depicts areas that have experienced a disturbance within a given year of 4.5 hectares (11 acres) or larger, along with cause and severity. Information sources include national fire mapping programs such as Monitoring Trends in Burn Severity (MTBS), Burned Area Reflectance Classification (BARC), and Rapid Assessment of Vegetation Condition after Wildfire (RAVG), local user/agency contributed data (LF Events Geodatabase), and remotely sensed Landsat imagery. Composite Landsat image pairs from the current year, prior year, and following year are spectrally compared to determine where change occurred and its corresponding severity. Additionally, vegetation indices (Normalized Differenced Vegetation Index [NDVI] and Normalized Burn Ratio [NBR]) serve as inputs into the Multi-Index Integrated Change Algorithm (MIICA) (Jin et al. 2013); MIICA outputs and differenced products (e.g., dNDVI and dNBR) are used to locate change. Predictive modeling based on the previous 10 years of disturbance data provides an additional dataset useful for locating disturbance. Image analysts use the aforementioned datasets separately or in combination to isolate true change from false change (e.g., change caused by stark differences in phenology rather than a true disturbance event). The accuracy of the final product is often related to the quality of the Landsat image composite. Areas with persistent cloud cover are particularly challenging (e.g., the northeast US). Fire caused disturbances sourced from MTBS may contain data gaps where clouds, smoke, water or Landsat Seven SLC-off stripes exist. Models trained from pre-fire and post-fire Landsat data are used to fill the gaps. The result is continuous severity and extent information for all MTBS fire disturbances. MTBS pixels derived from gap filling techniques, such as modeling, are noted as such in their corresponding attribute table. Smaller fires that do not meet the size criteria set forth by MTBS) may be attributed as a Burned Area Essential Climate Variable (BAECV), which are only produced for the lower 48 states. Causality and severity information assigned to a disturbance are prioritized by source, with the Highest priorities reserved for fire mapping programs (MTBS, BARC and RAVG) followed by user-contributed events contained in the LF Events Geodatabase, and lastly, Landsat image based change.

LANDFIRE's (LF) Annual Disturbance (Dist) product provides temporal and spatial information related to landscape change. Dist depicts areas that have experienced a disturbance within a given year of 4.5 hectares (11 acres) or larger, along with cause and severity. Information sources include national fire mapping programs such as Monitoring Trends in Burn Severity (MTBS), Burned Area Reflectance Classification (BARC), and Rapid Assessment of Vegetation Condition after Wildfire (RAVG), local user/agency contributed data (LF Events Geodatabase), and remotely sensed Landsat imagery. Composite Landsat image pairs from the current year, prior year, and following year are spectrally compared to determine where change occurred and its corresponding severity. Additionally, vegetation indices (Normalized Differenced Vegetation Index [NDVI] and Normalized Burn Ratio [NBR]) serve as inputs into the Multi-Index Integrated Change Algorithm (MIICA) (Jin et al. 2013); MIICA outputs and differenced products (e.g., dNDVI and dNBR) are used to locate change. Predictive modeling based on the previous 10 years of disturbance data provides an additional dataset useful for locating disturbance. Image analysts use the aforementioned datasets separately or in combination to isolate true change from false change (e.g., change caused by stark differences in phenology rather than a true disturbance event). The accuracy of the final product is often related to the quality of the Landsat image composite. Areas with persistent cloud cover are particularly challenging (e.g., the northeast US). Fire caused disturbances sourced from MTBS may contain data gaps where clouds, smoke, water or Landsat Seven SLC-off stripes exist. Models trained from pre-fire and post-fire Landsat data are used to fill the gaps. The result is continuous severity and extent information for all MTBS fire disturbances. MTBS pixels derived from gap filling techniques, such as modeling, are noted as such in their corresponding attribute table. Smaller fires that do not meet the size criteria set forth by MTBS) may be attributed as a Burned Area Essential Climate Variable (BAECV), which are only produced for the lower 48 states. Causality and severity information assigned to a disturbance are prioritized by source, with the Highest priorities reserved for fire mapping programs (MTBS, BARC and RAVG) followed by user-contributed events contained in the LF Events Geodatabase, and lastly, Landsat image based change.

Slope was produced from the IA DEM using ESRIs Slope tool. Output measurement for slope was both Degrees and Percent Rise (2 files produced).