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RdNBR is a remotely sensed index of the pre- to post-fire change in vegetation greenness, in this case the growing seasons in the year prior to and the year after the year in which the fire occurred. The mean composite scene selection method utilizes all valid pixels in all Landsat scenes over a specified date range to calculate the fire severity index. The CBI is a standardized field measure of vegetation burn severity (Key and Benson 2006), which here is predicted from a remotely sensed fire severity index using regression equations developed between CBI field plot data and the remote index, RBR (Parks et al 2019). The dataset featured provides an estimation of fire severity of past fires, with fire severity defined here as fire-induced change to vegetation. The dataset is limited to fires included in CAL FIRE’s Historic Wildland Fire Perimeters database and therefore is subject to the same limitations in terms of missing or erroneous data.,

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Purpose: This viewer is for the general public to see fuels reduction projects approved and completed under the CalVTP.,

These polygons depict vegetation management projects implemented under the CalVTP programmatic EIR. They can be fuel breaks in non-WUI or WUI or vegetation treatment projects for ecological restoration.

Purpose: This viewer is for the general public to see planned vegetation management projects under the CalVTP. These projects are only planned and have not been approved or scheduled for implementation.,

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These polygons depict vegetation management projects implemented under the CalVTP programmatic EIR. They can be fuel breaks in non-WUI or WUI or vegetation treatment projects for ecological restoration.

Purpose: This viewer is for the general public to see fuels reduction projects approved and completed under the CalVTP.,