The RAVG program provides assessments of vegetation conditions (burn severity) following large wildland fires on forested National Forest System (NFS) lands.
Scope
RAVG analysis is routinely conducted for wildland fires that include at least 1,000 acres of forested National Forest System (NFS) lands. (Since 2016, the threshold has been 500 acres for fires in the Eastern and Southern NFS regions.) Although many more smaller fires occur each year, these large fires account for the majority of the area burned.
The RAVG process was developed and first implemented in NFS Region 5 (California). It was adapted by GTAC for nationwide implementation in 2007. Under current protocols, RAVG products for qualified fires are made available within approximately 45 days after fire containment, provided that suitable imagery is available.
Process
RAVG products are generated using a two-date change detection process and regression equations that relate imagery-derived burn severity indices to field-based burn severity measures. RAVG analysis starts with a pair of moderate-resolution multi-spectral images (e.g., Landsat imagery), one from before the fire and one from after the fire. The image pair is used to derive a burn-severity index called the Relative Differenced Normalized Burn Ratio (RdNBR, Miller and Thode 2007), which is sensitive to vegetation mortality resulting from the wildfire event.
The RAVG program relies primarily on imagery from Landsat sensors (Landsat 8 and 9 Operational Land Imager (OLI) and, previously, Landsat 7 Enhanced Thematic Mapper (ETM+) and Landsat 5 Thematic Mapper (TM)) and from the European Space Agency's Sentinel-2 MultiSpectral Instrument (MSI). Other multi-spectral sensors can be used provided they have sufficient resolution and the necessary spectral bands. The preferred bands are the near infrared (NIR) and short-wave infrared (SWIR, around 2.2 micrometers), which are ideal for detecting the change from healthy green vegetation to dead vegetation, bare soil and ash. The two bands are used to calculate three indices: the Normalized Burn Ratio (NBR, one for each image), the Differenced NBR (dNBR, the change in NBR from the pre-fire image to the post-fire image) and the Relative dNBR (RdNBR, a modified dNBR that accounts for pre-fire vegetation density).
Regression equations are used to determine burn severity measures from RdNBR. The regression equations are based on field data (tree mortality data by species and size class) collected from many fires in the Sierra Nevada and northern California, and contemporary Landsat imagery. The burn severity measures are percent change (loss) in basal area (BA), percent change in canopy cover (CC), and a standardized burn severity metric called the Composite Burn Index (CBI). Thematic (classified) versions of each metric are then created from the continuous products.
Summary tables and maps are produced by integrating the burn metric raster data with existing vegetation and ownership data. The vegetation data are derived from the Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) Existing Vegetation Type (EVT) layer, recoded into eight broad vegetation classes for RAVG purposes. An ownership layer is used to identify the following four classes: USFS (non-wilderness), USFS wilderness, non-USFS (non-wilderness) and non-USFS wilderness.
Products
RAVG products include the following for each wildfire:
- Geospatial products, including imagery and derived data
- Satellite imagery (Landsat or similar)
- Pre-fire scene (spatial subset)
- Post-fire scene (spatial subset)
- Normalized burn ratio and related indices
- Pre-fire normalized burn ratio (NBR)
- Post-fire NBR
- Differenced NBR (dNBR)
- Relative dNBR (RdNBR)
- Burn severity measures derived from pre- to post-fire change
- Percent basal area loss (continuous and 4- and 7-class classified versions)
- Percent canopy cover loss (continuous and 5-class classified versions)
- Composite burn index (continuous and 4-class classified versions)
- EVT-based vegetation classes
- RAVG vegetation class (8 classes based on forest type and canopy density)
- RAVG tree tree/non-tree layer (7 of the 8 RAVG vegetation classes collapsed into a single class)
- Satellite imagery (Landsat or similar)
- User-friendly visualizations
- PDF map (burn severity measure and post-fire imagery)
- Google Earth map (KMZ) with burn metrics and imagery
- Summary table of affected area by vegetation class, ownership class, and burn severity class
- Ancillary data
- Fire perimeter (shapefile)
- Masked areas, if any (shapefile)
- Metadata (text)
Additional details about each product follow. Formulas for derived raster data are included in the metadata for each fire.
- Burn severity measures. The primary geospatial products are raster datasets (TIFF format) representing burn severity measures.
- Percent basal area (BA) loss represents the change in live basal area relative to the pre-fire condition. For the continuous version, values range from 0 to 100%. The 7-class version (BA-7) includes the following classes:
- Class 1: 0%
- Class 2: 0% - < 10%
- Class 3: 10% - < 25%
- Class 4: 25% - < 50%
- Class 5: 50% - < 75%
- Class 6: 75% - < 90%
- Class 7: 90% - 100%
- A 4-class version (BA-4) is created by recoding the classes:
- Class 1: 0%
- Class 2: 0% - < 25%
- Class 3: 25% - < 75%
- Class 4: 75% - 100%
- Note that a different recoding is used for the four BA loss classes in the PDF maps and tabular summaries:
- Class 1: 0% - < 25%
- Class 2: 25% - < 50%
- Class 3: 50% - < 75%
- Class 4: 75% - 100%
- Percent canopy cover (CC) loss represents the change in canopy cover relative to the pre-fire condition. For the continuous version, values range from 0 to 100%. The 5-class version (CC-5) consists of the following classes:
- Class 1: 0%
- Class 2: 0% - < 25%
- Class 3: 25% - < 50%
- Class 4: 50% - < 75%
- Class 5: 75% - 100%
- The Composite Burn Index (CBI) is a standardized fire severity rating based on a composite of effects to the understory vegetation (grass, shrub layers), midstory trees and overstory trees. Values range from 0 (unchanged) to 3 (highest severity). The classified product included in the RAVG dataset has the following four classes:
- Class 1 = unchanged (CBI: 0 - < 0.1)
- Class 2 = low severity (CBI: 0.1 - < 1.25)
- Class 3 = moderate severity (CBI: 1.25 - < 2.25)
- Class 4 = high severity (CBI: 2.25 - 3.0)
- Note: In all of the burn condition raster datasets, areas that are masked due to clouds, cloud shadows, smoke, active fire, or other reasons, are indicated with either -9999 (for continuous data) or 9 (for classified data).
- Percent basal area (BA) loss represents the change in live basal area relative to the pre-fire condition. For the continuous version, values range from 0 to 100%. The 7-class version (BA-7) includes the following classes:
- Other raster data include a subset of the multi-spectral imagery (e.g., pre- and post-fire Landsat imagery) used for the assessment, the associated indices (pre-fire NBR, post-fire NBR, dNBR, and RdNBR), the RAVG vegetation classes, and a RAVG tree/non-tree dataset.
- The burn boundary (perimeter) and masked areas, if any, are supplied in vector form (shapefiles).
- A map (PDF) of the burned area portrays the post-fire imagery and classified burn severity.
- A Google Earth file (KMZ) allows for interactive exploration of the perimeter, classified burn severity and imagery in the context of high-resolution imagery and other data available in the Google Earth application.
- A spatial summary table (Excel) lists affected area (acres) by vegetation class, ownership class and burn severity class.
Applications
RAVG products are intended primarily for use in assessing fire-related reforestation needs. RAVG data help staff on local units prioritize areas for further assessment and support reforestation funding requests and decisions. They facilitate post-fire vegetation management decision-making by reducing planning and implementation costs. RAVG data also serve a variety of related Agency objectives, such as wildlife habitat analysis and salvage harvest planning.
Note: The RAVG regression equations are not calibrated to non-forest vegetation. RAVG burn severity measures should be interpreted in light of existing (pre-fire) vegetation.
Related programs
RAVG is one of three post-fire programs at GTAC. The others are the Burned Area Emergency Response (BAER) Imagery Support program and the Monitoring Trends in Burn Severity (MTBS) program. Although the three programs have many similarities, they differ in their methods and protocols, as well as in their intended audiences.
- The BAER Imagery Support program supports BAER teams performing emergency assessments and soil stabilization treatments immediately following select wildfires. It is a cooperative effort between GTAC and the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. Its objective is to provide rapid delivery of satellite imagery, Burned Area Reflectance Classification (BARC) data, and related geospatial data to Forest Service and Department of the Interior (DOI) BAER teams. The BARC is a satellite-imagery-derived map that helps the BAER team prioritize its work and serves as the primary input to the final soil burn severity map produced by the BAER team. The BARC is derived from the Differenced Normalized Burn Ratio (dNBR). BAER Imagery Support is considered an emergency assessment; analysts typically deliver the program’s products to BAER teams within hours of receiving useable post-fire imagery. The BAER program’s first priority is to address emergency soil stabilization needs to prevent further damage to life, property, and natural and cultural resources.
- MTBS is a multi-year project designed to consistently map the burn severity and perimeters of large fires across all lands of the United States since 1984. The data generated by MTBS are used to identify national trends in burn severity, providing information necessary to monitor the effectiveness and effects of the National Fire Plan and the Healthy Forests Restoration Act. The Wildland Fire Leadership Council (WFLC), a multi-agency oversight group responsible for implementing and coordinating the National Fire Plan and Federal Wildland Fire Management Policy and Program Review, sponsors MTBS. The project is conducted through a partnership between EROS and GTAC. The MTBS project maps burn severity using the dNBR. The RdNBR is used to guide the selection of burn severity thresholds. The majority of fires mapped under the MTBS program are extended assessments--based on post-fire imagery acquired near the following peak of green, usually from the year after the fire--allowing the products to capture the effects of delayed vegetation mortality.
Changes
Various aspects of RAVG processes, products and scope have changed over time and are subject to change in the future. Users are encouraged to review the metadata included in each RAVG data bundle for descriptions of included data.