This is a map of various vegetation canopy structure metrics derived from high-density airborne LiDAR scans collected in August - September 2015 and 2019. The different raster bands represent statistical summaries of the normalized LiDAR point cloud. In the normalized point cloud, ground elevations

This dataset is a styled basemap depicting vegetation canopy structure variables in the Upper Gunnison domain overlaid on high-resolution topography, optimized for fast display on web maps and mobile devices. The underlying datasets are available as part of Release 3 of the RMBL Spatial Data Platfor

This dataset represents a 1/3 m resolution vegetation canopy height model for the upper East River Watershed in Western Colorado. Source datasets include August 2015 and August 2019 discrete-return LiDAR point clouds collected by Quantum Geospatial for terrain mapping purposes on behalf of the Color

The data comprise a long-term study of alpine plant community dynamics in the Gunnison National Forest of Colorado. The data comprise annual census data for all plants (including seedlings) in each of 50 2x2m plots, including information on size, reproduction, life stage, and mortality, with all pla

The purpose of this work was to quantify trends in water quality, total nitrogen deposition, vegetation, and land-use trends for the Continental United States (CONUS). This dataset contains gap-filled daily and yearly in-stream carbon (C) and nitrogen (N) concentrations, discharge, and calculated ex

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, Snow Telemetry (SNOTEL) sites and East River Watershed in Colorado locations. Fluxnet sites considered in th

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, Snow Telemetry (SNOTEL) sites and East River Watershed in Colorado locations. Fluxnet sites considered in th

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, Snow Telemetry (SNOTEL) sites and East River Watershed in Colorado locations. Fluxnet sites considered in th

In an outdoor garden at Irwin, Colorado, we established glacier lily plants in open-bottomed PVC pots that protected them from gopher attack. The initial cohorts were excavated from field sites as mature corms of unknown age. Later cohorts were grown from seed, so their ages are known. Each spring s

This is a vegetation canopy height map from the 2018 NEON AOP dataset. It was derived from the NEON Lidar-based digital surface model and the re-processed SDP NEON DEM. Pixels with low NDVI or inside building footprints were set to a value of zero.

This is a hydrologically corrected digital elevation model derived from the 2018 NEON AOP dataset. It represents the height above sea level for impervious objects attached to the ground, such as buildings, but not vegetation. Bridges and culverts have been "cut" to allow flow, and areas of suface wa

This is a hydrologically corrected digital elevation model derived from the 2018 NEON AOP dataset. It represents the height above sea level for impervious objects attached to the ground, such as buildings, but not vegetation. Bridges and culverts have been "cut" to allow realistic surface flow for h

This is a digital surface model from the 2018 NEON AOP dataset. It represents the height above sea level for objects attached to the ground, such as buildings. This version of the data includes the elevation of buildings and other non-vegetation objects such as bridges. Areas of deciduous vegetation

This is a digital surface model from the 2018 NEON AOP dataset. It represents the height above sea level for objects attached to the ground, such as buildings. This version of the data includes the elevation of buildings and other non-vegetation objects such as bridges, but areas of vegetation refle

This is a digital surface model from the 2018 NEON AOP dataset. It represents the height above sea level for objects attached to the ground, such as buildings and trees. This version of the data includes the elevation of the tops of deciduous vegetation, consistent with the data collection interval

1m Resolution bare-earth Digital Elevation Model for the Upper East River Derived from 2018 NEON AOP Data. This version has been re-processed to remove artifacts associated with sharp ridges and dense vegetation, and was based on original data from NEON: Goulden T ; Hass B ; Brodie E ; Chadwick K D