Average percent coverage and standard deviation of each canopy stratum from subplots at each aspen site during the SNF study in the Superior National Forest, Minnesota

Biophysical parameters (DBH, shrub diameter, growth format, frequency) for selected sites within the Superior National Forest, MN, during 1988-89

Biophysical parameters (DBH, NPP, biomass, bark area index, LAI, subcanopy LAI) by study site for Aspen and Spruce in the Superior National Forest, MN (SNF)

This is a combined data set of canopy, subcanopy and understory composition by vegetation species and study site ID

This data set contains two files (.txt format). One file provides ground-based biophysical measurements and above-ground net primary productivity (ANPP) estimates for 31 black spruce (Picea mariana) and 30 quaking aspen (Populus tremuloides) stands in Superior National Forest (SNF) in northeastern Minnesota, U.S.A. (-92 W 48 N). The measurements were obtained during a 1983-1984 intensive field campaign. Non-destructive measurements were made in over 100 forest plots covering a 50 x 50 km area. Trees sacrificed for biomass and annual increment measurements were taken outside the plots. The second file provides climate data from nearby weather stations for the period 1976-1986. The data set provides stand structural measurements (diameter at breast height, tree height, crown depth, and stem density), above-ground biomass, leaf area index, bark area index, and ANPP estimates. ANPP data are based on a combination of allometric relationships and annual tree-ring (radial) increments for the 5-year period 1979-1983. In the spruce stands, above-ground biomass ranged from 700-15,100 g/m2, LAI varied between 0.5-4.3, and ANPP ranged from 39-572 g/m2/yr. In comparison, above-ground biomass among aspen stands ranged from 600-22,000 g/m2, LAI varied between 1.3-4.0, and ANPP ranged from 213-1,199 g/m2/yr. The purpose of the SNF campaign was to investigate the ability of remote sensing to provide estimates of ecosystem biophysical properties. In addition to the results presented herein, satellite, aircraft, and helicopter observations and other ground measurements for the study sites are available from the ORNL DAAC Superior National Forest (SNF) Project web site [http://daac.ornl.gov/SNF/snf.shtml]. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1997.

SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented as list format)

SNF study site count of the number of trees over 2 meters, broken down by species code; see also SNF Plant Species Codes

This dataset provides annual maps of aboveground biomass (AGB, Mg/ha) for forests in Washington, Oregon, Idaho, and western Montana, USA, for the years 2000-2016, at a spatial resolution of 30 meters. Tree measurements were summarized with the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS) to estimate AGB in field plots contributed by stakeholders, then lidar was used to predict plot-level AGB using the Random Forests machine learning algorithm. The machine learning outputs were used to predict AGB from Landsat time series imagery processed through LandTrendr, climate metrics generated from 30-year climate normals, and topographic metrics generated from a 30-m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM). The non-forested pixels were masked using the PALSAR 2009 forest/nonforest mask.

SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented in table format)

Site characterization parameters (canopy density, litter components, soil characterization: color, moisture, components) for selected sites within the Superior National Forest, MN during 1988-89