These data represent tree diameter, species, mortality status, and plot attributes from 164 plots in Sequoia and Kings Canyon national parks, California. Plots were matched with local records of recent fire history to determine burn status and year burned if applicable.

These data represent tree diameter, species, mortality status, and plot attributes from 164 plots in Sequoia and Kings Canyon national parks, California. Plots were matched with local records of recent fire history to determine burn status and year burned if applicable.

These data represent tree diameter, species, mortality status, and plot attributes from 164 plots in Sequoia and Kings Canyon national parks, California. Plots were matched with local records of recent fire history to determine burn status and year burned if applicable.

We established a network of 121 plots distributed within the 2020 SQF, 2020 Rattlesnake, and 2021 KNP complex fire footprints (extracted from Fire and Resource Assessment Program (FRAP), https://frap.fire.ca.gov), as well as outside the fire perimeters to provide an unburned comparison. These plots were combined from two projects: a fire and fuels study (F&F) and the USGS sequoia research program (SRP), a related study of sequoia grove condition. All plots were visited in the summer of 2022, and thus we captured dynamics 1 and 2 years post-fire. Plots were restricted to conifer forest types, informed by a Sequoia and Kings Canyon national parks (SEKI) vegetation classification geospatial layer. F&F plots (102 in total) were stratified by elevation bands (1500-1917, 1917-2333, 2333-2750 m) and satellite-derived metrics of fire severity. SRP plots (19 in total) were placed in both burned and unburned giant sequoia groves. In all, 45 plots were located across eleven giant sequoia groves, with the remaining 76 plots located outside of groves.

We established a network of 121 plots distributed within the 2020 SQF, 2020 Rattlesnake, and 2021 KNP complex fire footprints (extracted from Fire and Resource Assessment Program (FRAP), https://frap.fire.ca.gov), as well as outside the fire perimeters to provide an unburned comparison. These plots were combined from two projects: a fire and fuels study (F&F) and the USGS sequoia research program (SRP), a related study of sequoia grove condition. All plots were visited in the summer of 2022, and thus we captured dynamics 1 and 2 years post-fire. Plots were restricted to conifer forest types, informed by a Sequoia and Kings Canyon national parks (SEKI) vegetation classification geospatial layer. F&F plots (102 in total) were stratified by elevation bands (1500-1917, 1917-2333, 2333-2750 m) and satellite-derived metrics of fire severity. SRP plots (19 in total) were placed in both burned and unburned giant sequoia groves. In all, 45 plots were located across eleven giant sequoia groves, with the remaining 76 plots located outside of groves.

This data set provides high-resolution surface reflectance, thermal imagery, burn severity metrics, and LiDAR-derived structural measures of forested areas in the Sierra Nevada Mountains, California, USA, collected before and after the August 2013 Rim and September 2014 King mega forest fires. Pre-fire data were paired with post-fire collections to assess pre- and post-fire landscape characteristics and fire severity. Field estimates of fire severity were collected to compare with derived remote sensing indices. Reflectance measurements for the spectroscopic AVIRIS and MASTER sensors are distributed as multi-band geotiffs for each megafire and acquisition date. Derived operational metric products for each sensor are provided in individual GeoTIFFs. GeoTIFFs produced from LiDAR point data depict first order topographic indices and summary statistics of vertical vegetation structure.

Provided are data containing condition assessments on individual giant sequoia (Sequoiadendron giganteum; SEGI) stems and post-fire regeneration counts within Board Camp, Suwanee, New Oriole Lake, Homer’s Nose, and a subset of Redwood Mountain and Dillonwood groves of Sequoia and Kings Canyon national parks, respectively. Stem data contain condition-related attributes (e.g., spatial location, diameter breast height, status - live or dead, percent canopy that is live, scorched or torched). Regeneration plots are located using a spatially-balanced sampling design (Generalized Random Tessellation Stratified - 'GRTS'). Each regeneration plot is a fixed radius circle (11.35 meters or 17.84 meters) and contain count data of giant sequoia seedlings.

Provided are data containing condition assessments on individual giant sequoia (Sequoiadendron giganteum; SEGI) stems and post-fire regeneration counts within Board Camp, Suwanee, New Oriole Lake, Homer’s Nose, and a subset of Redwood Mountain and Dillonwood groves of Sequoia and Kings Canyon national parks, respectively. Stem data contain condition-related attributes (e.g., spatial location, diameter breast height, status - live or dead, percent canopy that is live, scorched or torched). Regeneration plots are located using a spatially-balanced sampling design (Generalized Random Tessellation Stratified - 'GRTS'). Each regeneration plot is a fixed radius circle (11.35 meters or 17.84 meters) and contain count data of giant sequoia seedlings.

Provided are data containing condition assessments on individual giant sequoia (Sequoiadendron giganteum; SEGI) stems and post-fire regeneration counts within Board Camp, Suwanee, New Oriole Lake, Homer’s Nose, and a subset of Redwood Mountain and Dillonwood groves of Sequoia and Kings Canyon national parks, respectively. Stem data contain condition-related attributes (e.g., spatial location, diameter breast height, status - live or dead, percent canopy that is live, scorched or torched). Regeneration plots are located using a spatially-balanced sampling design (Generalized Random Tessellation Stratified - 'GRTS'). Each regeneration plot is a fixed radius circle (11.35 meters or 17.84 meters) and contain count data of giant sequoia seedlings.

This vector point feature layer represents the ignition points from SEKI fire history from 1921 through 2024. Ignition locations for fires are typically mapped with GPS units or estimated on USGS Topo Quads by helicopter, field personnel, or fire lookouts. These locations are reported first locally (i.e. to dispatch) for operational response and then to national reporting systems. The locations in this dataset are imported from these various national reporting systems. DI-1202 Individual Fire Reports Historically, NPS fires were reported manually on DI-1202 Individual Fire Report Forms. Many locations in this dataset are from these DI-1202 records and their accuracy is variable. Where ignition points were not given on DI-1202 records, the ignition point was generated from the centroid of the fire history polygon. Shared Applications Computer System (SACS) Although the paper DI-1202 is the official fire record, many fire locations on DI-1202s were actually extracted from SACS. SACS was a computer system hosted by NIFC in Boise, Idaho for DOI agencies (NPS, FWS, and BIA) to electronically submit data from their DI-1202 forms. With this system, locations of fires were first recorded on paper, then uploaded, then annually downloaded to this dataset. Wildland Fire Management Information System (WFMI) WFMI replaced SACS as the primary fire reporting system in the 2000s for DOI because it tied into additional fire information systems. With the WFMI system, locations of fires were generated locally by fire personnel, uploaded into WFMI, and then annually downloaded into this dataset. Integrated Reporting of Wildland Fire Information (IRWIN) and Interagency Fire Occurrence Reporting Modules (InFORM) In 2018, NPS began the transition to InFORM, built on IRWIN. InFORM and IRWIN integrate and share data across disparate systems, reducing duplicative digital data entry. This system is tied to computer aided dispatch (CAD), so that fire locations are always up to date with whatever ground personnel have reported. With this system, locations of fires are automatically synced with IRWIN and then annually downloaded to this dataset. Other Notes For fires that originated outside the park boundaries, no ignition location is shown. The ignition location of record is kept internally by SEKI fire GIS staff due to the errors resulting from the SACS to WFMI conversion. These locations are the internal locations and not the locations shown on the 1202 report. WFMI was replaced by INFORM in 2020 but no official integrated dataset was complete by the time this dataset was processed. This data can be used for a variety of purposes including fire planning, operational applications, burned area recovery applications.