This dataset contains lidar digital elevation models (DEMs). The lidar data were collected before (2016) and after (2021) the Grizzly Creek Fire, which occurred in 2020. The 2016 lidar was collected during a series of flights between 10 June and 7 October 2016. The 2021 lidar flight was conducted in full on 24 August 2021. The files are named with the following convention: Vendor_Year_Resolution_merged_Watershed. The vendor is either Merrick (2016 data) or Sanborn (2021), the year is either 2016 or 2021, the resolution is 1 meter in both cases, and the watershed is labeled as HUC1, HUC2, HUC3_N_side, or HUC3_S_side. Additionally, the files from the individual vendors were uploaded to two separate compressed folders: Merrick_2016_1m_merged_HUCx.zip and Sanborn_2021_1m_merged_HUCx.zip.

This release includes lidar point cloud and Wolman pebble count data for a debris-flow deposit in Glenwood Canyon, CO. The data, FullDepositRegion.las (las 1.2), were collected with a terrestrial laser scanner and includes the full deposit and portions of the slope and drainage that generated the debris flow. This .las file includes point cloud data up to 250 m upslope of the deposit, though the data are sparse at distances greater than 60 m from the deposit due to slope geometry and shadowing. The data TrainingRegion.txt includes an 83 m^2 subregion of the .las point cloud that has been manually divided into granular materials >6.3 cm (clast) and <6.3 cm (matrix) in size along the intermediate particle axis. Each particle >6.3 cm in size received an index that was applied to all points belonging to that particle as described in the column header details. The PebbleCount.csv data contains 150 particle size measurements collected at the debris-flow front, obtained with a gravelometer (<18 cm) or measuring tape (>18 cm).

This release includes lidar point cloud and Wolman pebble count data for a debris-flow deposit in Glenwood Canyon, CO. The data, FullDepositRegion.las (las 1.2), were collected with a terrestrial laser scanner and includes the full deposit and portions of the slope and drainage that generated the debris flow. This .las file includes point cloud data up to 250 m upslope of the deposit, though the data are sparse at distances greater than 60 m from the deposit due to slope geometry and shadowing. The data TrainingRegion.txt includes an 83 m^2 subregion of the .las point cloud that has been manually divided into granular materials >6.3 cm (clast) and <6.3 cm (matrix) in size along the intermediate particle axis. Each particle >6.3 cm in size received an index that was applied to all points belonging to that particle as described in the column header details. The PebbleCount.csv data contains 150 particle size measurements collected at the debris-flow front, obtained with a gravelometer (<18 cm) or measuring tape (>18 cm).

Debris Flow, Precipitation, and Volume Measurements in the Grizzly Creek Burn Perimeter June 2021-September 2022 https://doi.org/10.5066/P9Z7RROL This data release contains data summarizing observations within and adjacent to the Grizzly Creek Fire, which burned from 10 August to 18 December 2020. This monitoring data summarizes precipitation, observations of debris flows, and the volume of sediment eroded during debris flows triggered during the summer monsoonal period in 2021 and 2022. Summary rainfall data 2021 (1a_Storm_matrix_2021_gr1mmhr.csv) are provided in a comma-separated value (CSV) file. These data represent the maximum measured rainfall intensities during the monsoon months of 2021 (June-Sept). The columns in the csv file are: Date (m/dd/yy), Name (11 columns have unique gage names), Max 15 min (this is the maximum 15-minute rainfall intensity in mm/h for the unique gauge), Maximum Value for All Gages (this is the maximum rainfall intensity for all of the gauges in units of either mm/h or in/15 min), Peak 15-minute Intensity (in/15 min) (this is the total inches of rainfall in 15 minutes), Debris Flow (this can be 0 indicating no debris flow response, or 1 indicating a debris flow response). Note that we only display gauges that record data sufficient to produce a 15-minute rainfall intensity. Gauges with longer recording rates (e.g., 1 hour) cannot be used to compute the 15-minute rainfall intensity and are not displayed in this table. A null value (‘n/a’) populates the entries where the rain gauge did not measure a 15-minute rainfall intensity greater than 1 mm/hr. Time series rainfall data from the gauges are provided in the child item: Precipitation Data Grizzly Creek Burn Perimeter. Summary rainfall data 2022 (1b_Storm_matrix_2022_gr1mmhr.csv) are provided in a comma-separated value (CSV) file. These data represent the maximum measured rainfall intensities during the monsoon months of 2022 (June-Sept). The columns in the csv file are: Date (m/dd/yy), Name (7 columns have unique gage names), Max 15 min (this is the maximum 15-minute rainfall intensity in mm/h), Peak 15-minute Intensity (in/15 min) (this is the total inches of rainfall in 15 minutes), Debris Flow (this can be 0 indicating no debris flow response, or 1 indicating a debris flow response). Note that we only display gauges that record data sufficient to produce a 15-minute rainfall intensity. Gauges with longer recording rates (e.g., 1 hour) cannot be used to compute the 15-minute rainfall intensity and are not displayed in this table. A null value (‘n/a’) populates the entries where the rain gauge did not measure a 15-minute rainfall intensity greater than 1 mm/hr. Time series rainfall data from the gauges are provided in the child item: Precipitation Data Grizzly Creek Burn Perimeter. Debris Flow Observation data 2021 (2a_All_Verification_2021.csv) are provided in a comma-separated value (CSV) file. The columns in the csv file are: Year (yyyy), State, Fire Name, Fire_ID (index for the fire developed during the USGS debris flow hazard assessment), Fire_SegID (a specific index assigned by the USGS debris flow hazard assessment to the channel segment that produced the debris flow), Site Name (the name of the nearest milemarker on interstate 70), ObservationDate_mmddyyyy, ObservationLatitude_DD, ObservationLongitude_DD, DebrisFlowResponse (this can be 0 indicating no debris flow response, or 1 indicating a debris flow response), SourceOfObservation (name of the observer), StormDate_mmddyyyy, GaugeName, GaugeLatitude_DD, GaugeLongitude_DD, GaugeDist_km (distance from watershed of the debris flow observation to the nearest rain gage in km), StormAccum_mm (the total rainfall during a storm in millimeters), StormDuration_hr (the total duration of a storm in hours), Peak_I15_mm/h (the maximum 15 minute rainfall intensity in mm/h), Peak_I30_mm/h (the maximum 30 minute rainfall intensity in mm/h), Peak_I60_mm/h (the maximum 60 minute rainfall intensity in

Lidar-derived surface elevation data for Glen Alps, Southcentral Alaska, collected August 17, 2024, Raw Data File 2025-19, releases classified point cloud, digital surface model (DSM), digital terrain model (DTM), and intensity model of the Glen Alps area, Municipality of Anchorage (MOA), Southcentral Alaska, during leaf-on conditions. The survey provides summer 'snow off' surface elevations to derive snow depth information using a separately collected winter 'snow-on' elevation surface. Ground control data were collected on March 25, 2024, and aerial lidar data were collected on August 17, 2024, and subsequently merged and processed using a suite of geospatial processing software. This data collection is released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/31704).

The Alaska Division of Geological & Geophysical Surveys (DGGS) used aerial lidar to produce a classified point cloud, digital surface model (DSM), digital terrain model (DTM), and intensity model of a mountain slope adjacent to Speel Arm near Port Snettisham, Southeast Alaska, during near snow-free ground conditions on September 7, 2019. The survey provides snow-free surface elevations for deriving snow depth distribution models with repeat surveys during snow-covered conditions. Aerial lidar and ground control data were collected on September 7, 2019, and subsequently processed in a suite of geospatial processing software. These products are released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/30730).

Lidar-derived surface elevation data for Dickason Highlands, Southcentral Alaska, collected August 14, 2024, Raw Data File 2025-12, releases classified point cloud, digital terrain model (DTM), and an intensity model of of Dickason Highlands, Southcentral Alaska, during leaf-on conditions. The survey provides surface elevations for detailed bedrock and surficial geologic mapping and for potentially active fault investigations. Ground control data were collected July 20, 2024, and aerial lidar data were collected August 14, 2024, and subsequently merged and processed using a suite of geospatial processing software. This data collection is released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/31536).

Lidar-derived elevation data for the Twentymile River watershed, Southcentral Alaska, collected August-October 2022, Raw Data File 2023-3, uses aerial lidar to produce a classified point cloud, digital surface model (DSM), digital terrain model (DTM), and intensity model of the Twentymile River watershed, Southcentral Alaska, during snow-free ground conditions from August to October 2022. The survey provides snow-free surface elevations for trail planning and assessing avalanche hazards, among other objectives. Ground control data were collected on August 31, 2022, and aerial lidar data were collected on multiple days from August 29 to October 14, 2022, and subsequently processed in a suite of geospatial processing software. These products are released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/30959).

These lidar data are derived from two airborne lidar surveys: a 2016 Los Angeles Region Imagery Acquisition Consortium (LARIAC) survey, and a 2019 National Center for Airborne Laser Mapping (NCALM) survey. These data were reclassified in order to improve the classification of ground points, and to make the classification of both datasets as consistent as possible. The NCALM data had their position shifted slightly to more closely align with the LARIAC data. The data are organized into two "Child Items": Reclassified lidar point clouds from 2016 LARIAC collection near Malibu, California and Reclassified lidar point clouds from 2019 NCALM collection near Malibu, California. The point clouds are available as ~1 square kilometer tiles with 25 m buffer overlaps to avoid edge effects in further processing. The naming convention includes the name of the original data collection and some reference UTM coordinates.

These lidar data are derived from two airborne lidar surveys: a 2016 Los Angeles Region Imagery Acquisition Consortium (LARIAC) survey, and a 2019 National Center for Airborne Laser Mapping (NCALM) survey. These data were reclassified in order to improve the classification of ground points, and to make the classification of both datasets as consistent as possible. The NCALM data had their position shifted slightly to more closely align with the LARIAC data. The data are organized into two "Child Items": Reclassified lidar point clouds from 2016 LARIAC collection near Malibu, California and Reclassified lidar point clouds from 2019 NCALM collection near Malibu, California. The point clouds are available as ~1 square kilometer tiles with 25 m buffer overlaps to avoid edge effects in further processing. The naming convention includes the name of the original data collection and some reference UTM coordinates.