Mountain Snowpack, Climate Metrics, and Conifer Forest Monitoring
Integrates satellite remote sensing, LiDAR, and machine learning downscaling to track snowmelt timing, growing degree days, and conifer forest responses to climate variability in subalpine Colorado.
Knowledge Graph (226 nodes, 661 connections)
Research Primer
Background
Mountain forests in the Gunnison Basin are shaped by a tight coupling between snow, climate, and the conifer species that dominate the landscape around the Rocky Mountain Biological Laboratory (RMBL). Engelmann spruce, subalpine fir, and lodgepole pine cover much of the Upper East River Watershed, where they store carbon, regulate streamflow into the Colorado River, and provide habitat for wildlife. As the regional climate warms and droughts lengthen, researchers are working to understand how these forests are responding — whether they are still growing, where they are stressed, and how disturbances such as bark beetle outbreaks and wildfire might reshape them. Monitoring these changes requires both careful ground measurements and new tools that can scale observations from a single tree to an entire watershed.
A few key concepts make this research easier to follow. Snow-free season length is the number of days each year when the ground is bare and trees can photosynthesize and grow; in subalpine forests, longer or shorter snow cover strongly controls how much energy and water trees receive. Growing degree days are a way of adding up daily warmth above a threshold (often 5°C) to estimate how much heat has accumulated for biological activity such as tree growth or insect development. Stand structure refers to how trees are arranged in a forest — their heights, diameters, spacing, and the layers of canopy, understory, and dead wood — and it influences fire behavior, beetle susceptibility, and habitat quality. The alpine treeline marks the upper elevational edge where forest gives way to tundra, an ecotone that is sensitive to climate shifts.
Methodologically, much recent work in the Gothic area relies on remote sensing from drones (unmanned aerial vehicles, or UAVs). Structure-from-motion photogrammetry stitches together many overlapping aerial photos to build a 3D model of the forest canopy, while individual tree detection algorithms pick out single trees from those models or from LiDAR point clouds. Allometric relationships — mathematical links between, for example, a tree's trunk diameter and its canopy size or biomass — let researchers translate what a drone sees from above into estimates of stem growth and carbon storage on the ground. Together these tools allow forest monitoring across rugged terrain that is difficult to sample on foot.
Foundational work
Because focused remote-sensing studies of conifer forests around Gothic are recent, the foundational literature here is largely drawn from applied forest management and from early student-led inventories at RMBL. Waring and Bucholz (Waring & Bucholz, 2023) synthesize decades of silvicultural science, framing forest management as a balance between resistance strategies that prevent change and resilience strategies that enable recovery after disturbance. Their synthesis establishes core principles relevant to the Gunnison Basin: that thinning dense stands can reduce tree mortality during bark beetle outbreaks, that complex multilayered canopies favor different insect groups than simple even-aged stands, and that stand structure and individual tree vigor are the levers managers most often use to influence forest health.
At the local scale, Phillips (Philips, 2022) provided one of the first detailed fuels and stand-structure inventories near RMBL, documenting how surface fuels, downed wood, and Douglas fir distribution vary across slopes at the Willey Conservation Easement. That study found the densely treed south slope contained most of the Douglas fir and showed fire scars from historical low-severity fire, while adjacent hayfields had almost no accumulated woody fuels — establishing a baseline picture of how topography and land-use history shape fuel loads in this landscape.
Key findings
A consistent message from recent RMBL studies is that the conifer forests around Gothic are under measurable stress. Hernandez (Hernandez, 2023) used repeat remote-sensing surveys to show that conifer volume in the Gothic townsite decreased by nearly 48,000 cubic meters between 2021 and 2023, with mean tree height also declining over two years. Different stands responded differently to environmental drivers: topographic wetness emerged as the most important predictor of growth in a random forest model, while snow-free season length had significant effects in some stands but not others. This patchy response suggests that local terrain, not just regional climate, governs which parts of the forest are gaining or losing biomass.
Work by Luedtke (Luedtke, 2024) on Engelmann spruce reinforces and extends these results by linking what drones see from above to what is happening inside tree stems. Field measurements of trunk diameter related predictably to UAV estimates of canopy size once stand density was accounted for, and canopy growth correlated moderately with basal area growth in both the 2021–2022 and 2022–2023 periods. Importantly, canopy growth in one year was a stronger predictor of stem growth in the following year than of growth in the same year — a lagged relationship that has practical implications for using aerial imagery to estimate forest carbon storage at landscape scales.
Golla (Golla, 2023) added a water-balance perspective by comparing transpiration among Engelmann spruce, subalpine fir, and lodgepole pine in the Upper East River Watershed. Species identity alone explained nearly 29 percent of the variance in transpiration rates, with spruce and fir running warmer canopies and transpiring less than lodgepole pine. Environmental factors — especially snow persistence and slope — contributed more to transpiration variability than stand structure did, and longer snow duration was associated with warmer, less actively transpiring canopies. Together with the silvicultural principles compiled by Waring and Bucholz (Waring & Bucholz, 2023), these findings point toward a forest in which both species composition and snow regime determine how trees use water during increasingly dry summers.
Current frontier
All of the RMBL-based studies in this area have appeared since 2022, signaling that drone-based, watershed-scale conifer monitoring around Gothic is an emerging research program rather than an established one. The temporal trajectory is clear: Phillips (Philips, 2022) began with ground-based fuels inventories, Hernandez (Hernandez, 2023) and Golla (Golla, 2023) introduced repeated UAV surveys and species comparisons, and Luedtke (Luedtke, 2024) extended the toolkit by calibrating aerial canopy measurements against tree-ring increment cores. The frontier now lies in scaling these methods up — using calibrated allometric relationships and structure-from-motion models to estimate carbon storage and water use for entire stands and watersheds without needing to measure every tree on the ground.
New questions are also emerging about the mechanisms behind observed declines. Hernandez (Hernandez, 2023) explicitly noted that more work is needed to identify why conifer volume is falling, and Golla (Golla, 2023) highlighted the surprising importance of snow persistence over stand structure in shaping transpiration. Future studies are likely to integrate satellite-based snow disappearance tracking, finer-scale climate downscaling, and individual tree detection so that growth, mortality, and water-use patterns can be linked to specific microclimates within complex mountain terrain.
Open questions
Several important questions remain unresolved. What is driving the recent decrease in conifer volume around Gothic — drought, insects, age structure, or some combination — and is the trend widespread or concentrated in particular stands? How will lengthening snow-free seasons interact with species-specific water-use strategies to determine which conifers persist as conditions dry? Can drone-derived canopy measurements, combined with the lagged canopy–stem growth relationship documented by Luedtke (Luedtke, 2024), be used to forecast carbon storage a year or more in advance? And how should silvicultural guidance from broader syntheses such as Waring and Bucholz (Waring & Bucholz, 2023) be adapted to the high-elevation, mixed-conifer forests of the Gunnison Basin, where management history and disturbance regimes differ from the systems where those principles were first developed? Answering these questions over the next decade will require sustained monitoring plots, repeated UAV flights, and careful pairing of remote sensing with traditional field measurements.
References
Golla, B. (2023). The Influence of Forest Structure and Composition on Transpiration Rates Among Drought-Stressed Conifer Species in the Upper East River Watershed. →
Hernandez, D. (2023). Analysis of growth patterns in Conifer stands present in Gothic town. →
Luedtke, A. (2024). Stem and canopy growth analysis in Picea Engelmannii with UAVs and field measurements. →
Phillips, M. (2022). Forest Fuels and Management Considerations at the Willey Conservation Easement, Colorado. →
Waring, K. M., & Bucholz, E. (2023). Silviculture. →
Concept (14) →
growing degree days
Temperature accumulation metric calculated using averaging method with base temperature, used to predict insect phenology and plant development
snow-free season length
freezing temperature spectrum
orthomosaic
alpine treeline
The biogeographic transition zone between subalpine forest and alpine tundra, representing the elevational limit of individual trees with an upright g...
individual tree detection
Automated algorithms for identifying and delineating individual trees from LiDAR point cloud data
crossing distance
topographic shading
braided channels
northness
Show 4 more concepts
stand structure
The horizontal and vertical distribution of components of a forest stand including the height, diameter, crown layers, and stems of trees, shrubs, her...
parent-child spatial relationships
allometric relationships
Mathematical relationships that describe how tree dimensions and biomass scale with each other
structure from motion photogrammetry
Technique using overlapping images from different perspectives to construct 3D models of forest structure
Protocol (20) →
Random Forest climate downscaling
Machine learning approach using Random Forest algorithms to downscale coarse resolution climate data to higher spatial resolution using topographic pr...
Forest inventory plot sampling
Uses full-waveform LiDAR returns processed through adaptive deconvolution and individual tree detection algorithms to map forest structure metrics inc...
Satellite-based snow disappearance tracking
Time-series analysis of Landsat and Sentinel satellite imagery to determine seasonal snow disappearance dates using Normalized Difference Snow Index w...
NEON Airborne Observation Platform
High-resolution airborne hyperspectral and lidar data collection and analysis to classify land cover types and derive vegetation parameters for hydrol...
NEON AOP digital elevation modeling
Creation of digital surface model from 2018 NEON Airborne Observation Platform dataset representing height above sea level for objects attached to the...
snow-free growing degree day calculation
Temperatures above 5°C summed only for days estimated to be free of snow to measure energy available for biological processes.
degree-day models
Calculation of cumulative growing degree days from weather station data using species-specific base temperatures, correlated with biological events th...
Single-direction watershed delineation
Flow lines derived in GRASS GIS using a single direction algorithm from hydrologically corrected digital elevation model to delineate watersheds drain...
reciprocal transplant experiment (Animalia)
Experimental transplantation of completed mason bee nests from low to high elevation sites to test effects of season length and climate on offspring d...
PRISM climate data
Extraction of environmental variables from spatial data platform using zonal functions to calculate average climate values within tree polygon boundar...
Show 10 more protocols
UAV RGB orthomosaic generation
UAV flights using DJI Mavic 2 Pro collecting RGB images with 3cm ground sample distance. Images processed via Structure from Motion in Agisoft Metasha...
bilinear resampling
Resampling of 0.6m resolution imagery to 1m grid resolution using bilinear interpolation.
airborne LiDAR scanning
High-density airborne LiDAR scans collected in August-September 2015 and 2019 to generate normalized point clouds.
ITCSegment algorithm
Region-growing algorithm that iteratively incorporates LiDAR points into candidate tree canopies starting from seed locations identified as local heig...
Convolutional neural networks species classification (Plantae)
CNN training using image patches for pixel-based tree and shrub species classification at alpine treeline.
Linear regression gap filling
Statistical method used to fill missing data areas using relationships between 2018 and 2019 snow depths or snow depth to elevation relationships.
Bayesian spatial record linkage for multi-temporal LiDAR (Plantae)
A two-stage Bayesian hierarchical approach that identifies unique individuals across LiDAR scans by modeling observed locations as noisy transformatio...
UTM coordinate mapping
Records the UTM Y Coordinate for every pixel using the WGS84 UTM Zone 13N Coordinate System (EPSG:32613).
NDVI calculation from NAIP imagery
Calculation of Normalized Differential Vegetation Index from 4-band aerial imagery using (NIR-Red)/(NIR+Red) formula.
cost distance analysis
Map generated with the cost distance GRASS GIS module (r.cost) using estimated travel speeds as the cost function.
Publication (5) →
Analysis of growth patterns in Conifer stands present in Gothic town
Stem and canopy growth analysis in Picea Engelmannii with UAVs and field measurements
The Influence of Forest Structure and Composition on Transpiration Rates Among Drought-Stressed Conifer Species in the Upper East River Watershed
Forest Fuels and Management Considerations at the Willey Conservation Easement, Colorado
Silviculture
Dataset (125) →
Plant and carbon data, snowmelt manipulation experiment, Rocky Mountain Biological Laboratory (RMBL), 2023
These data are from a 2023 snowmelt manipulation experiment in Vera Meadow at the Rocky Mountain Biological Laboratory. We experimentally advanced the...
Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 4
This dataset provides Daymet Version 4 data as gridded estimates of daily weather parameters for North America, Hawaii, and Puerto Rico. Daymet variab...
Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 4 R1
This dataset provides Daymet Version 4 R1 data as gridded estimates of daily weather parameters for North America, Hawaii, and Puerto Rico. Daymet var...
Data from "A Bayesian Record Linkage Approach to Applications in Tree Demography Using Overlapping LiDAR Scans"
Processed LiDAR data and environmental covariates from 2015 and 2019 LiDAR scans in the Vicinity of Snodgrass Mountain (Western Colorado, USA), in a g...
Snow-free Growing Degree-days Early Season Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated spring snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunni...
Air Temperature Growing Degree-days Early Season Timeseries
These are maps of annual accumulated spring snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, deri...
Snow-free Freezing Degree-days Annual Mean (2002-2021)
This is a map of accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum te...
Snow-free Growing Degree-days 0-60 Days Post Snow Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison dom...
Snow-free Growing Degree-days Late Season Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated fall snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunniso...
Snowpack Proportional Reduction in Early Season Growing Degree Days (2002-2021)
This is a map of the influence of snow on the energy available for plant growth (growing degree days, GDD) in spring and early summer for the Uppe...
Show 115 more datasets
Snowpack Proportional Reduction in Growing Degree Days (2002-2021)
This is a map of the influence of snow on the energy available for plant growth (growing degree days, GDD) for the Upper Gunnison domain, derived ...
Snow-free Growing Degree-days 0-60 Days Post Snow Mean (2002-2021)
This is a map of accumulated snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived from daily ...
Snow-free Growing Degree-days Late Season Mean (2002-2021)
This is a map of accumulated fall snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived from d...
Snow-free Growing Degree-days Annual Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison dom...
Snow-free Freezing Degree-days 0-60 Days Post Snow Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, deriv...
Snow-free Growing Degree-days Annual Mean (2002-2021)
This is a map of accumulated snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived from daily ...
Snow-free Freezing Degree-days 0-60 Days Post Snow Mean (2002-2021)
This is a map of accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum te...
Snow-free Freezing Degree-days Late Season Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated fall snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunni...
Snow-free Freezing Degree-days Late Season Mean (2002-2022)
This is a map of accumulated fall snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, derived from...
Snow-free Freezing Degree-days Early Season Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated spring snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunni...
Snow-free Freezing Degree-days Annual Standard Deviation (2002-2021)
This is a map of temporal variability in accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, deriv...
Snow-free Freezing Degree-days Early Season Mean (2002-2021)
This is a map of accumulated spring snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, derived fr...
Air Temperature Growing Degree-days Late Season Standard Deviation (2002-2022)
This is a map of temporal variability in accumulated fall growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from...
Sindewald et al - Identifying alpine treeline species using high-resolution WorldView-3 multispectral imagery and convolutional neural networks dataset
The dataset contains region of interest (ROI) polygons for six treeline species found in Rocky Mountain National Park, CO. The tree and shrub species ...
Post survey report for AOP Assignable Asset collection of Crested Butte, CO
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over...
Air Temperature Growing Degree-days Early Season Standard Deviation (2002-2022)
This is a map of temporal variability in accumulated growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from dail...
Post survey report for AOP Assignable Asset collection of Crested Butte, CO
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over...
Snow-free Growing Degree-days Late Season Timeseries
These are maps of accumulated fall snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived from ...
Snow-free Growing Degree-day 0-60 Days Post Snow Timeseries
These are maps of annual accumulated snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived fro...
Snow-free Freezing Degree-days 0-60 days Post-snow Timeseries
These are maps of annual accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily mi...
Air Temperature Freezing Degree-days Early Season Timeseries
These are maps of annual accumulated spring snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, de...
Snowpack Proportional Reduction in Late Season Growing Degree Days (2002-2021)
This is a map of the influence of snow on the energy available for plant growth (growing degree days, GDD) in late summer and fall for the Upper G...
1 m Resolution topographic aspect "westness" for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR data
<p>This is a 1 m resolution map of the relative "westness" of topographic aspect, computed from the cosine of the topographic aspect using the equatio...
Hydrologically Corrected (cut) 1m Digital Elevation Model for the Upper East River Domain
<p>This is a hydrologically corrected digital elevation model derived from the 2018 NEON AOP dataset. It represents the height above sea level for imp...
Hydrologically Corrected (cut and burned) 1m Digital Elevation Model for the Upper East River Domain
This is a hydrologically corrected digital elevation model derived from the 2018 NEON AOP dataset. It represents the height above sea level for imperv...
Multi-direction Flow Accumulation for the Upper East River Domain
This dataset represents estimated flow accumulation from a hydrologically corrected digital elevation model. The map was derived in GRASS GIS using a ...
Multi-direction Stream Flowlines for the Upper East River Domain
<p>This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in the GRASS GIS mod...
Bare Earth Potential Solar Radiation on Day of Year 80 for the Upper East River Derived from 2018 NEON AOP Data
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 80 (spring equinox), taking into account shading from...
Bare-earth Potential Solar Radiation on Day of Year 265 for the Upper East River Derived from 2018 NEON AOP Data
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 265 (fall equinox), taking into account shading from ...
Bare-earth Potential Solar Radiation on Day of Year 172 for the Upper East River Derived from 2018 NEON AOP Data
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 172 (summer solstice), taking into account shading fr...
Bare Earth Potential Solar Radiation on Day of Year 355 for the Upper East River Derived from 2018 NEON AOP Data
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 355 (winter solstice), taking into account shading fr...
Subcanopy Potential Solar Radiation on Day of Year 172 for the Upper East River Derived from 2018 NEON AOP Data
<p>This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 172 (summer solstice), taking into account shading ...
Subcanopy Potential Solar Radiation on Day of Year 265 for the Upper East River Derived from 2018 NEON AOP Data
<p>This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 265 (fall equinox), taking into account shading fro...
Subcanopy Potential Solar Radiation on Day of Year 355 for the Upper East River Derived from 2018 NEON AOP Data
<p>This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 355 (winter solstice), taking into account shading ...
1 m Resolution topographic aspect "southness" for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR
<p>This is a 1 m resolution map of the relative "southness" of topographic aspect, computed from the cosine of the topographic aspect using the equati...
Landscape Flowering Phenology Field Data for Sites in the Vicinity of Crested Butte, CO.
This dataset represents field observations of reproductive development (flowering phenology) in 135 species of flowering plants collected at 12 fiel...
Snowpack Onset Day of Year Yearly Timeseries
This dataset represents an estimate of the day of year (i.e. , "Julian Day") of the onset of the seasonal snowpack. Specifically these are...
Air Temperature Freezing Degree-days Annual Timeseries
These are maps of annual accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum temp...
Air Temperature Growing Degree-days Annual Timeseries
These are maps of accumulated growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from daily maximum temperature m...
Air Temperature Growing Degree-days Late Season Timeseries
These are maps of annual accumulated fall growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from daily maximum t...
Snow-free Freezing Degree-days Late Season Timeseries
These are maps of annual accumulated fall snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, deri...
Snow-free Freezing Degree-days Early Season Timeseries
These are maps of annual accumulated spring snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, de...
Snow-free Growing Degree-days Annual Timeseries
These are maps of annual accumulated snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived fro...
Snow-free Growing Degree-days Early Season Timeseries
These are maps of annual accumulated spring snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, deri...
Air Temperature Freezing Degree-days Annual Mean (2002-2021)
This is a map of accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum temperature ...
Air Temperature Freezing Degree-days Annual Standard Deviation (2002-2021)
This is a map of variability in accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minim...
Air Temperature Freezing Degree-days Early Season Mean (2002-2021)
This is a map of spring accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum tempe...
Air Temperature Freezing Degree-days Early Season Standard Deviation (2002-2021)
This is a map of temporal variability in spring accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived ...
Air Temperature Freezing Degree-days Late Season Standard Deviation (2002-2021)
This is a map of temporal variability in fall accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived fr...
Air Temperature Growing Degree-days Annual Standard Deivation (2002-2021)
This is a map of temporal variability in accumulated growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from dail...
Air Temperature Growing Degree-days Early Season Mean (2002-2022)
This is a map of accumulated growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from daily maximum temperature ma...
Air Temperature Growing Degree-days Late Season Mean (2002-2022)
This is a map of accumulated fall growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from daily maximum temperatu...
Snow-free Growing Degree-days Early Season Mean (2002-2021)
This is a map of accumulated spring snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived from...
Snowpack Proportional Reduction in Freezing Degree Days (2002-2021)
This is a map of the influence of snow on growing season freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain,...
Snowpack Proportional Reduction in Early Season Freezing Degree Days (2002-2021)
This is a map of the influence of spring snow on early season freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison do...
Snowpack Proportional Reduction in Late Season Freezing Degree Days (2002-2021)
This is a map of the influence of fall snow on late season freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domai...
Post survey report for AOP Assignable Asset collection of Crested Butte, CO
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over...
Sindewald et al - Identifying alpine treeline species using high-resolution WorldView-3 multispectral imagery and convolutional neural networks dataset
The dataset contains region of interest (ROI) polygons for six treeline species found in Rocky Mountain National Park, CO. The tree and shrub species ...
1 m Resolution topographic slope for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR data.
This is a 1 m resolution map of topographic slope (measured in degrees) computed using a 3*3 pixel kernel and Horn's formula. It is derived from a 1m ...
Snowpack Onset Day of Year Mean (1993 - 2022)
This dataset represents an estimate of the mean day of year (i.e., "Julian Day") of the onset of the seasonal snowpack. Specifically these a...
Air Temperature Freezing Degree-days Late Season Timeseries
These are map of annual fall accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum ...
1m Resolution NDVI for the Upper Gunnison Basin derived from October 2017 NAIP Imagery
This is a 1m resolution map of Normalized Differential Vegetation Index (NDVI) derived from resampled 0.6m 4-band orthoimagery collected as part of th...
1 m Resolution 4-band orthoimagery for the Upper Gunnison Basin derived from October 2017 NAIP imagery
This is a 1m resolution map of Normalized Differential Vegetation Index (NDVI) derived from resampled 0.6m 4-band orthoimagery collected as part of th...
1 m Resolution NDVI for the Upper Gunnison Basin derived from September 2019 NAIP Imagery
This is a 1m resolution map of Normalized Differential Vegetation Index (NDVI) derived from resampled 0.6m 4-band orthoimagery collected as part of th...
1 m Resolution 4-band orthomosaic for the Upper Gunnison Basin derived from September 2019 NAIP Imagery
<p>This is a 1m resolution aerial imagery orthomosaic resampled from 0.6m 4-band orthoimagery collected on September 14th 2019 as part of the USDA Nat...
Snowpack Persistence Day of Year Mean (1993 - 2022)
This dataset represents an estimate of the mean day of year (i.e., "Julian Day") of the persistence of the seasonal snowpack from 1993 - 2022. ...
Air Temperature Freezing Degree-days Late Season Mean (2002-2021)
This is a map of fall accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum tempera...
Snowpack Duration Yearly Timeseries
These maps represent annual estimates of the number of days of continuous seasonal snowpack from 1993 - 2022. The maps are derived from estimates ...
Snowpack Persistence Day of Year Standard Deviation (1993-2022)
This dataset represents an estimate of interannual variability in the day of year (i.e., "Julian Day") of the persistence of the seasonal snowpack...
Single-direction Stream Flowlines for the Upper East River Domain
<p>This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in GRASS GIS using a...
Average 2m Air Temperature Monthly Timeseries
These are maps of monthly averages of daily average air temperature for the Upper Gunnison domain measured in degrees C. Estimates were derived fr...
Maximum 2m Air Temperature Monthly Timeseries
These are maps of monthly averages of daily maximum air temperature for the Upper Gunnison domain measured in degrees C. Estimates were derived fr...
Minimum 2m Air Temperature Monthly Timeseries
These are maps of monthly averages of daily minimum air temperature for the Upper Gunnison domain measured in degrees C. Estimates were derived fr...
Air Temperature Growing Degree-days Annual Mean (2002-2021)
This is a map of accumulated growing potential (growing degree days, GDD) for the Upper Gunnison domain, derived from daily maximum temperature ma...
Single-direction Flow Accumulation Map for the Upper East River Domain
<p>This map represents estimated flow accumulation from a hydrologically corrected digital elevation model. The map was derived in GRASS GIS using a s...
Leaf-on 1m Digital Surface Model for the Upper East River Domain
<p>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 a...
Subcanopy Potential Solar Radiation on Day of Year 80 for the Upper East River Derived from 2018 NEON AOP Data
<p>This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 265 (fall equinox), taking into account shading fro...
Quality-controlled and Gap-filled 1m Digital Elevation Model for the Upper East River Domain
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 w...
Vegetation Structure Maps for the Upper East River Domain Derived from 2015 and 2019 LiDAR Data
<p>This is a map of various vegetation canopy structure metrics derived from high-density airborne LiDAR scans collected in August - September 2015 an...
Snow-free Freezing Degree-days Annual Timeseries
These are maps of annual accumulated freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum temp...
Single-direction Major Streams for the Upper East River Domain
<p>This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in GRASS GIS using a...
Drone ortho basemap of the Gothic Townsite, May 25th 2019
This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in sunny conditions on M...
Drone ortho basemap of the Gothic Townsite, November 15th, 2019
<qgis stylecategories="AllStyleCategories" maxscale="0" minscale="1e+08" hasscalebasedvisibilityflag="0" version="3.18.1-Zürich">This is a visible (RG...
Drone ortho basemap of the Gothic Townsite, August 27th 2019
This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in Sunny conditions on A...
Drone ortho basemap of the Gothic Townsite, September 25th, 2019
This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in Sunny conditions on S...
Drone ortho basemap of the Gothic Townsite, July 22nd 2019
This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in cloudy conditions on ...
Drone ortho basemap of the Gothic Townsite, June 17th, 2019
This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in sunny conditions on J...
Styled 2019 snow depth basemap of the Upper East River domain
<p>This is a styled basemap showing snow depth on April 7th 2019 derived from repeat LiDAR data collection by the Airborne Snow Observatory. This data...
1m Digital Elevation Model with Buildings Derived from the 2018 NEON AOP Dataset
<p>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 a...
Leaf-off 1m Digital Surface Model of the Upper East River Domain
<p>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 a...
Styled 2018 snow depth basemap of the Upper East River domain
<p>This is a styled basemap showing snow depth on March 31st, 2018 derived from repeat LiDAR data collection by the Airborne Snow Observatory. This da...
1 m Resolution WGS84 UTM Zone 13N X Coordinate for the Upper Gunnison Domain
<p>This map records the UTM X Coordinate (measured in meters) for every pixel in the Upper Gunnison Domain, as measured using the WGS84 UTM Zone 13N C...
1 m Resolution WGS84 UTM Zone 13N Y Coordinate for the Upper Gunnison Domain
<p>This map records the UTM Y Coordinate (in meters) for every pixel in the Upper Gunnison Domain, as measured using the WGS84 UTM Zone 13N Coordinate...
Snowpack Duration Mean (Water Year 1993 - 2022)
This dataset represents an estimate of the mean number of days of continuous seasonal snowpack from 1993 - 2022. This map is derived from estimates ...
Quality-controlled 1m Digital Elevation Model for the Upper East River Domain
<p>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 re...
Styled canopy structure basemap of the Upper Gunnison domain
<p>This dataset is a styled basemap depicting vegetation canopy structure variables in the Upper Gunnison domain overlaid on high-resolution topograph...
Gothic Colorado WInter 2022 Snow Depth Lidar
Gothic Colorado Winter 2022 Snow Depth Lidar from Jan7, Jan 26, and Feb 14 2022. Additionally, includes snow off.
Small Sub-watersheds of the Upper East River Domain
<p>This map represents estimated watersheds for stream segments derived from a hydrologically corrected digital elevation model. The flow lines were d...
1 m Resolution Canopy Height Estimates for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR Data
This is a map of vegetation canopy height above the ground for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Height is measured in...
Large Sub-watersheds of the Upper East River Domain
<p>This map represents estimated watersheds for stream segments derived from a hydrologically corrected digital elevation model. The flow lines were d...
3 m Resolution Understory Cover for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR Data
<p>This is a map of vegetation understory cover or density for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Cover is measured as ...
1 m Resolution Digital Elevation Model for the Upper Gunnison Domain derived from 2015 and 2019 LiDAR Data
<p>This is a 1 m resolution Digital Elevation Model (DEM) for the Upper Gunnison River domain derived from public LiDAR datasets. The primary data sou...
Winter Travel Time from Crested Butte for the Upper East River Domain
<p>This map represents the estimated on-road and off-road travel time in minutes from Crested Butte via the fastest travel means available (snowmobile...
Summer Travel Time from Gothic for the Upper East River Domain
<p>This map represents the estimated on-road and off-road travel time in minutes from Crested Butte via the fastest travel means available (snowmobile...
3 m Resolution 20th Percentile Canopy Height Estimates for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR Data
This is a map of 20th percentile canopy height above the ground for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Height is measur...
1 m Resolution Basic Landcover Map for the Upper Gunnison Domain Derived from NAIP Imagery and LiDAR
<p>This is 1 meter resolution landcover map developed for the RMBL Spatial Data Platform. Source datasets include 2017 and 2019 4-band imagery from th...
A composite high resolution canopy height map for the Upper East River domain
<p>This dataset represents a 1/3 m resolution vegetation canopy height model for the upper East River Watershed in Western Colorado. Source datasets ...
Basic High-resolution Landcover Map for the Upper East River Domain
<p>This is a landcover map derived from the 2018 NEON AOP dataset for the upper east river. </p><p>1=needle-leaf trees and shrubs 2=deciduous trees an...
Maximum 2m Air Temperature Daily Timeseries
These are maps of daily maximum air temperature for the Upper Gunnison domain measured in degrees C. Estimates were derived from weather station a...
Minimum 2m Air Temperature Daily Timeseries
These are maps of daily minimum air temperature for the Upper Gunnison domain measured in degrees C. Estimates were derived from weather station a...
Quality-controlled Vegetation Canopy Height Model for the Upper East River Domain
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-proce...
3 m Resolution 80th Percentile Canopy Height Estimates for the Upper Gunnison Basin Derived from 2015 and 2019 LIDAR Data
<p>This is a map of 20th percentile canopy height above the ground for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Height is mea...
Mask for the Upper Gunnison SDP Domain at 3 m resolution
This is a 3m resolution binary map representing areas within the Upper Gunnison Domain of the RMBL Spatial Data Platform.
Styled slope and aspect basemap of the Upper Gunnison domain
<p>This dataset is a styled basemap depicting topographic slope and aspect of Upper Gunnison domain using a rainbow color scale with contour lines, op...
Surface Water Map at 1m Resolution for the Upper East River Domain
<p>This map represents the estimated binary presence of surface water during the NEON Airborne Observation Platform campaign in July 2018. Values of 1...