Upper East sub-basins are delineated as area contributing flow to SFA 2016 stream gage locations. Shapefile attributes include sub-basin ID, name, area (m2 and km2) and codes for spatial contributions to EBC and PH used by Carroll et al. (2018). Geospatial reference is UTM 1983 zone 13. JPEG image p

The depth of floodplain fine sediment was measured at 1,601 points along the East River near Crested Butte, Colorado spanning a study reach approximately 800 m in length in 2016 and 2017. These depths are being used to estimate the volume of floodplain sediment present along the study reach, convert

This dataset comprises paired environmental and genomic data for soil samples collected across meander-bound floodplains G (ERMG), L (ERML) and Z (ERMZ). A total of 96 soil samples (32 per floodplain) from the ~ 10-25 cm layer were collected in September 2015, during base flow conditions. An additio

Locations and descriptions of the sites where field sampling was conducted during the 2018 National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) imaging spectroscopy and lidar surveys in Gunnison County, Colorado. The sampling sites were located across East River, Washin

Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest near Crested Butte, CO with remotely sensed data including imaging spectroscopy. The flight box design encompassed the waters

This map represents the estimated on-road and off-road travel time in minutes from Crested Butte via the fastest travel means available (snowmobiles excluded). Estimates apply for winter (snow-on) conditions. This map was generated with the cost distance GRASS GIS module (r.cost) using estimated tra

This map represents the estimated on-road and off-road travel time in minutes from Crested Butte via the fastest travel means available (snowmobiles excluded). Estimates apply for summer (snow-off) conditions after all roads have been opened to vehicle traffic. This map was generated with the cost d

This is a landcover map derived from the 2018 NEON AOP dataset for the upper east river. 1=needle-leaf trees and shrubs 2=deciduous trees and shrubs 3=deciduous meadow and subshrub ( 0.5m) 4=bare rock, soil, gravel and asphalt 5=water 6=snow 7=buildings Source data includes NEON LiDAR and imaging sp

This map represents estimated watersheds for stream segments derived from a hydrologically corrected digital elevation model. The flow lines were derived in GRASS GIS using a single direction algorithm that does not allow channel braiding. Each watershed is identified by a unique integer that matche

This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in GRASS GIS using a multi-direction algorithm that allows channel braiding. Each stream segment is identified by a unique integer. Stream lines were delineated for drainage

This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in the GRASS GIS module r.watershed using a multi-flow direction algorithm that allows channel braiding. Each stream segment is identified by a unique integer.

This map represents estimated flow accumulation from a hydrologically corrected digital elevation model. The map was derived in GRASS GIS using a single flow-direction (D8) algorithm that does not allow channel braiding. Values represent the area (in square meters) of land that contributes flow to a

This map represents the estimated binary presence of surface water during the NEON Airborne Observation Platform campaign in July 2018. Values of 1 represent open water, values of 0 represent no water present. Surface water was mapped using imaging spectrometer data from the AOP, and combined with a

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 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

This is a bare-earth digital elevation model from the 2018 NEON AOP dataset. Areas outside the boundaries of the Upper East River domain were filled with data interpolated from the 3m 2018 Airborne Snow Observatory DEM. The ASO DEM was harmonized with the NEON DEM and filtered to remove small pits a

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

The National Hydrography Dataset (NHD) represents the water drainage network of the United States with features such as rivers, streams, canals, lakes, ponds, coastline, dams, and stream gages. This data was downloaded directly from the usgs.gov National Map downloader site. The data was then clippe