SnowEx23 Bonanza Creek Experimental Forest Terrestrial Lidar Scans Raw V001

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This data set contains unprocessed point cloud data created from terrestrial lidar scans (TLS) collected during the SnowEx 2023 campaign from the Bonanza Creek Experimental Forest near Fairbanks, Alaska. Data were collected in October 2022 (snow-off) and March 2023 (snow-on). Digital terrain models (DTMs) derived from the raw point cloud data are available as the SnowEx23 Bonanza Creek Experimental Forest Terrestrial Lidar Scans, Version 1 (SNEX23_BCEF_TLS) data set

SnowEx23 Airborne Lidar-Derived 0.5M Snow Depth and Canopy Height V001

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This data set provides digital terrain models, snow depth, and canopy height, acquired by a scanning lidar system and derived from Point Cloud Digital Terrain Models (PCDTMs) from two regions of Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer’s Loop/Creamer’s Field) and a coastal tundra environment in the North Slope region of the northern Alaska coastal plain (Arctic coastal plain and Upper Kuparuk Toolik). The raw data from which these data are derived are available as SnowEx23 Airborne Lidar Scans Raw, Version 1.

SnowEx23 Airborne Lidar Scans Raw V001

공공데이터포털

This data set provides raw lidar data from two regions of Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer’s Loop/Creamer’s Field) and a coastal tundra environment in the North Slope region of the northern Alaska coastal plain (Arctic coastal plain and Upper Kuparuk Toolik). Processed data, including digital terrain models, snow depth, and canopy height derived from Point Cloud Digital Terrain Models (PCDTMs) are available as SnowEx23 Airborne Lidar-Derived 0.25M Snow Depth and Canopy Height, Version 1.

SnowEx20-21 QSI Lidar DEM 3m UTM Grid V001

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This data set is part of the SnowEx 2020 and SnowEx 2021 campaigns and provides bare Earth digital elevation models (DEM) acquired by a scanning lidar system at a 3.0 m spatial resolution, and derived from point cloud digital terrain models. DEMs are available for September 2021 and from multiple areas in Colorado, Idaho, and Utah. These data were produced alongside Vegetation Height and Snow Depth data sets.

SnowEx20-21 QSI Lidar DEM 0.5m UTM Grid V001

공공데이터포털

This data set is part of the SnowEx 2021 campaign and provides bare Earth digital elevation models (DEM) acquired by a scanning lidar system at a 0.5 m spatial resolution, and derived from point cloud digital terrain models. DEMs are available for September 2021 and from multiple areas in Colorado, Idaho, and Utah. These data were produced alongside Vegetation Height and Snow Depth data sets.

SnowEx17 Boise State University Terrestrial Laser Scanner (TLS) Point Cloud V001

공공데이터포털

This data set contains terrestrial laser scanner (TLS) point cloud data collected as part of the 2017 SnowEx campaign in Grand Mesa, Colorado. Data were collected under both snow-off (September 2016) and snow-on (February 2017) conditions, at both open and forested locations. Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i). These TLS data can be used to determine snow depth and explore the interactions between snow and vegetation.

SnowEx Mores Creek Summit (MCS) Airborne LiDAR Survey Raw V001

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The data set described here provides raw lidar data collected as part of a multi-year effort to monitor monthly snow distribution over a 35 km² region of the Mores Creek Headwaters in the Boise Mountains of central Idaho between 2021 and 2024. Data acquisition in 2021 overlapped temporally with the NASA SnowEx 2021 field campaign. Digital terrain models (DTM), digital surface models (DSM) snow depth models, and canopy height models (CHM) derived from these point cloud data are available as SnowEx Mores Creek Summit (MCS) Airborne LiDAR Survey, Version 1.

SnowEx20 Boise State University Terrestrial Laser Scanner (TLS) Point Cloud V001

공공데이터포털

This data set contains terrestrial laser scanner (TLS) point cloud data collected as part of the 2020 SnowEx campaign in Grand Mesa, Colorado. Data were collected under both snow-off (September 2019) and snow-on (February 2020) conditions, at both open and forested locations. Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i). These TLS data can be used to determine snow depth and explore the interactions between snow and vegetation.

SnowEx17 Boise State University Raw Terrestrial Laser Scanner (TLS) Point Cloud V001

공공데이터포털

This data set contains raw, unprocessed terrestrial laser scanner (TLS) point cloud data collected as part of the 2017 SnowEx campaign in Grand Mesa, Colorado. Data were collected in the fall (September 2016) and winter (February 2017). Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i).

ABoVE: Terrestrial Lidar Scanning Forest-Tundra Ecotone, Brooks Range, Alaska, 2016

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This dataset provides terrestrial lidar scanning (TLS) point cloud data collected at 10 research plots along the forest-tundra ecotone (FTE) in the Brooks Range of Alaska, south of Chandalar Shelf and Atigun Pass on the east side of the Dalton Highway. Data were collected in mid-June 2016. Data were acquired for each plot from multiple scan positions with a Leica ScanStation C10 green wavelength laser instrument. After processing the point spacing is < 1 cm. TLS enables resolution of 3-dimensional landscape features that can be used to derive ecologically important metrics of canopy structure and surface topography at high spatial resolution.