US-Bar: Bartlett Experimental Forest
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Tower_team: | |
PI: | Andrew Richardson Andrew.Richardson@nau.edu - Northern Arizona University |
FluxContact: | David Hollinger dyhollinger@gmail.com - USDA Forest Service |
Technician: | Andrew Ouimette apouimette@gmail.com - USDA Forest Service |
Lat, Long: | 44.0646, -71.2881 |
Elevation(m): | 272 |
Network Affiliations: | AmeriFlux, Phenocam |
Vegetation IGBP: | DBF (Deciduous Broadleaf Forests: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.) |
Climate Koeppen: | Dfb (Warm Summer Continental: significant precipitation in all seasons ) |
Mean Annual Temp (°C): | 5.61 |
Mean Annual Precip. (mm): | 1245.77 |
Flux Species Measured: | CO2, H, H2O |
Years Data Collected: | 2004 - Present |
Years Data Available: | AmeriFlux BASE 2004 - 2024 Data Citation AmeriFlux FLUXNET 2004 - 2022 Data Citation |
Data Use Policy: | AmeriFlux CC-BY-4.0 Policy1 |
Description: | The Bartlett Experimental Forest (448170 N, 71830 W) is located within the White Mountains National Forest in north-central New Hampshire, USA. The 1050 ... The Bartlett Experimental Forest (448170 N, 71830 W) is located within the White Mountains National Forest in north-central New Hampshire, USA. The 1050 ha forest extends across an elevational range from 200 to 900 m a.s.l. It was established in 1931 and is managed by the USDA Forest Service Northeastern Research Station in Durham, NH. The climate is humid continental with short, cool summers (mean July temperature, 19.8C) and long, cold winters (mean January temperature, 9.8C). Annual precipitation averages 130 cm and is distributed evenly throughout the year. Soils are developed from glacial till and are predominantly shallow, well-drained spodosols. At lowto mid-elevation, vegetation is dominated by northern hardwoods (American beech, Fagus grandifolia; sugar maple, Acer saccharum; yellow birch, Betula alleghaniensis; with some red maple, Acer rubrum and paper birch, Betula papyrifera). Conifers (eastern hemlock, Tsuga canadensis; eastern white pine, Pinus strobus; red spruce, Picea rubens) are occasionally found intermixed with the more abundant deciduous species but are generally confined to the highest (red spruce) and lowest (hemlock and pine) elevations. In 2003, the site was adopted as a NASA North American Carbon Program (NACP) Tier-2 field research and validation site. A 26.5 m high tower was installed in a low-elevation northern hardwood stand in November, 2003, for the purpose of making eddy covariance measurements of the forest–atmosphere exchange of CO2, H2O and radiant energy. Continuous flux and meteorological measurements began in January, 2004, and are ongoing. Average canopy height in the vicinity of the tower is approximately 20–22 m. In the tower footprint, the forest is predominantly classified into red maple, sugar maple, and American beech forest types. Leaf area index in the vicinity of the tower is 3.6 as measured by seasonal litterfall collection, and 4.5 as measured by the optically based Li-Cor LAI-2000 instrument. Further site information: http://www.fs.fed.us/ne/durham/4155/bartlett.htm See MoreShow Less |
URL: | http://www.fs.fed.us/ne/durham/4155/bartlett.htm |
Research Topics: | — |
Acknowledgment: | Research at the Bartlett Experimental Forest tower is supported by the USDA Forest Service's Northern Research Station and the National Science Foundation (grant DEB-1114804). |
- This site’s data can also be used under the more restrictive AmeriFlux Legacy Policy.
The AmeriFlux Legacy Policy must be followed if this site’s data are combined with data from sites that require the AmeriFlux Legacy Policy.


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US-Bar: Bartlett Experimental Forest
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Use the information below for citation of this site. See the Data Policy page for more details.
DOI(s) for citing US-Bar data
Data Use Policy: AmeriFlux CC-BY-4.0 License
This site’s data can also be used under the more restrictive AmeriFlux Legacy Policy.
The AmeriFlux Legacy Policy must be followed if US-Bar data are combined with data from sites that require the AmeriFlux Legacy Policy.
- AmeriFlux BASE: https://doi.org/10.17190/AMF/1246030
Citation: Andrew Richardson, David Hollinger (2025), AmeriFlux BASE US-Bar Bartlett Experimental Forest, Ver. 7-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246030 - AmeriFlux FLUXNET: https://doi.org/10.17190/AMF/2006969
Citation: Andrew Richardson, David Hollinger (2024), AmeriFlux FLUXNET-1F US-Bar Bartlett Experimental Forest, Ver. 4-6, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/2006969
Find global FLUXNET datasets, like FLUXNET2015 and FLUXNET-CH4, and their citation information at fluxnet.org.
To cite BADM when downloaded on their own, use the publications below for citing site characterization. When using BADM that are downloaded with AmeriFlux BASE and AmeriFlux FLUXNET products, use the DOI citation for the associated data product.
Publication(s) for citing site characterization
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US-Bar: Bartlett Experimental Forest
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US-Bar: Bartlett Experimental Forest
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AmeriFlux Images | Add Image |

US-Bar: Bartlett Experimental Forest
US-Bar: Eddy flux tower
Keywords: —
Location: New Hampshire, United States
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US-Bar Eddy flux tower
US-Bar tower seen from the NEON tower PhenoCam (https://phenocam.nau.edu/webcam/sites/bartlettir/)
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Location: New Hampshire, United States
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2016.US.Bar.Sitevisit.IMG_7118
2016.US.Bar.Sitevisit.IMG_7118
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US-Bar: Bartlett Experimental Forest
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MODIS NDVI
The time series shows the 16-day Normalized Difference Vegetation Index (NDVI) average from the MOD13Q1 data product.
Use the slider below the time series to zoom in and out.
To view / download these data and other MOD13Q1 products for this site, visit MODIS/Terra Vegetation Indices.
For other related products, visit MODIS/VIIRS Fixed Sites Subsets Tool.
Citation:
ORNL DAAC. 2018. Terrestrial Ecology Subsetting & Visualization Services (TESViS) Fixed Sites Subsets. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1567
MODIS NDVI subsetted data is not yet available for this site.
For a complete list of AmeriFlux sites, visit ORNL DAAC's MODIS/VIIRS Fixed Sites Subsets Tool.
PhenoCam Images and Derived Time Series Data
PhenoCams are high-resolution digital cameras that take repeated images of studied ecosystems and provide quantitative information about the canopy phenology. The PhenoCam Network coordinates the camera installation and data reporting/analyses across sites in the Americas, providing automated, near-surface remote sensing of canopy phenology across a range of ecosystems and climate zones. Use of PhenoCam images / data should follow the PhenoCam Data Use Policy .
PhenoCam sites for US-Bar:
Use the links below to explore camera images and interactive timeseries for these sites.
Citation:
B. Seyednasrollah, A. M. Young, K. Hufkens, T. Milliman, M. A. Friedl, S. Frolking, and A. D. Richardson. Tracking vegetation phenology across diverse biomes using version 2.0 of the phenocam dataset. Scientific Data, 6(1):222, 2019. doi:10.1038/s41597-019-0229-9Camera Imagery
Milliman, T., B. Seyednasrollah, A.M. Young, K. Hufkens, M.A. Friedl, S. Frolking, A.D. Richardson, M. Abraha, D.W. Allen, M. Apple, M.A. Arain, J.M. Baker, D. Baldocchi, C.J. Bernacchi, J. Bhattacharjee, P. Blanken, D.D. Bosch, R. Boughton, E.H. Boughton, R.F. Brown, D.M. Browning, N. Brunsell, S.P. Burns, M. Cavagna, H. Chu, P.E. Clark, B.J. Conrad, E. Cremonese, D. Debinski, A.R. Desai, R. Diaz-Delgado, L. Duchesne, A.L. Dunn, D.M. Eissenstat, T. El-Madany, D.S.S. Ellum, S.M. Ernest, A. Esposito, L. Fenstermaker, L.B. Flanagan, B. Forsythe, J. Gallagher, D. Gianelle, T. Griffis, P. Groffman, L. Gu, J. Guillemot, M. Halpin, P.J. Hanson, D. Hemming, A.A. Hove, E.R. Humphreys, A. Jaimes-Hernandez, A.A. Jaradat, J. Johnson, E. Keel, V.R. Kelly, J.W. Kirchner, P.B. Kirchner, M. Knapp, M. Krassovski, O. Langvall, G. Lanthier, G.l. Maire, E. Magliulo, T.A. Martin, B. McNeil, G.A. Meyer, M. Migliavacca, B.P. Mohanty, C.E. Moore, R. Mudd, J.W. Munger, Z.E. Murrell, Z. Nesic, H.S. Neufeld, W. Oechel, A.C. Oishi, W.W. Oswald, T.D. Perkins, M.L. Reba, B. Rundquist, B.R. Runkle, E.S. Russell, E.J. Sadler, A. Saha, N.Z. Saliendra, L. Schmalbeck, M.D. Schwartz, R.L. Scott, E.M. Smith, O. Sonnentag, P. Stoy, S. Strachan, K. Suvocarev, J.E. Thom, R.Q. Thomas, A.K. Van den berg, R. Vargas, J. Verfaillie, C.S. Vogel, J.J. Walker, N. Webb, P. Wetzel, S. Weyers, A.V. Whipple, T.G. Whitham, G. Wohlfahrt, J.D. Wood, J. Yang, X. Yang, G. Yenni, Y. Zhang, Q. Zhang, and D. Zona. 2019. PhenoCam Dataset v2.0: Digital Camera Imagery from the PhenoCam Network, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1689
Green Chromatic Coordinate Time Series
Seyednasrollah, B., A.M. Young, K. Hufkens, T. Milliman, M.A. Friedl, S. Frolking, A.D. Richardson, M. Abraha, D.W. Allen, M. Apple, M.A. Arain, J. Baker, J.M. Baker, D. Baldocchi, C.J. Bernacchi, J. Bhattacharjee, P. Blanken, D.D. Bosch, R. Boughton, E.H. Boughton, R.F. Brown, D.M. Browning, N. Brunsell, S.P. Burns, M. Cavagna, H. Chu, P.E. Clark, B.J. Conrad, E. Cremonese, D. Debinski, A.R. Desai, R. Diaz-Delgado, L. Duchesne, A.L. Dunn, D.M. Eissenstat, T. El-Madany, D.S.S. Ellum, S.M. Ernest, A. Esposito, L. Fenstermaker, L.B. Flanagan, B. Forsythe, J. Gallagher, D. Gianelle, T. Griffis, P. Groffman, L. Gu, J. Guillemot, M. Halpin, P.J. Hanson, D. Hemming, A.A. Hove, E.R. Humphreys, A. Jaimes-Hernandez, A.A. Jaradat, J. Johnson, E. Keel, V.R. Kelly, J.W. Kirchner, P.B. Kirchner, M. Knapp, M. Krassovski, O. Langvall, G. Lanthier, G.l. Maire, E. Magliulo, T.A. Martin, B. McNeil, G.A. Meyer, M. Migliavacca, B.P. Mohanty, C.E. Moore, R. Mudd, J.W. Munger, Z.E. Murrell, Z. Nesic, H.S. Neufeld, T.L. O'Halloran, W. Oechel, A.C. Oishi, W.W. Oswald, T.D. Perkins, M.L. Reba, B. Rundquist, B.R. Runkle, E.S. Russell, E.J. Sadler, A. Saha, N.Z. Saliendra, L. Schmalbeck, M.D. Schwartz, R.L. Scott, E.M. Smith, O. Sonnentag, P. Stoy, S. Strachan, K. Suvocarev, J.E. Thom, R.Q. Thomas, A.K. Van den berg, R. Vargas, J. Verfaillie, C.S. Vogel, J.J. Walker, N. Webb, P. Wetzel, S. Weyers, A.V. Whipple, T.G. Whitham, G. Wohlfahrt, J.D. Wood, S. Wolf, J. Yang, X. Yang, G. Yenni, Y. Zhang, Q. Zhang, and D. Zona. 2019. PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1674
GeoNEX Data Products
GeoNEX led by NASA Earth eXchange (NEX) is a collaborative effort for generating Earth monitoring products from the new generation of geostationary satellite sensors. GeoNEX has produced a suite of geostationary data products including surface reflectance, land surface temperature, surface solar radiation, and many others.
The GeoNEX Common Grid locates GeoNEX data in the geographic (latitude/longitude) projection. Pixels (grid cells) are created at regular 0.005°, 0.01°, and 0.02° resolutions.
GeoNEX pixels below cover the area 0.06° x 0.06° around and including site US-Bar, 44.0646, -71.2881.
Click a square in the grid at left to display its data below.
Coordinates for selected GeoNEX Pixel
Graph controls:
- Zoom: click-drag
- Pan: shift-click-drag
- Restore zoom level: double-click
- Use the slider below the time series to zoom in and out.
All download requests will be logged.
NDVI: Normalized Difference Vegetation Index
Resolution: 0.01° x 0.01° & 10 minutes
Coordinates for pixel:
NIRv Near-Infrared Reflectance of vegetation
Resolution: 0.01° x 0.01° & 10 minutes
Coordinates for pixel:
DSR: Surface downward shortwave radiation
Resolution: 0.01° x 0.01° & Hourly
Coordinates for pixel:
LST: Land Surface Temperature
Resolution: 0.02° x 0.02° & Hourly
Coordinates for pixel:
Citation
This material can be used without obtaining permission from NASA. NASA should be acknowledged as the source of this material.
Subset Data Citation:
- Hashimoto, H., Wang, W., Park, T., Khajehei, S., Ichii, K., Michaelis, A.R., Guzman, A., Nemani, R.R., Torn, M., Yi, K., Brosnan, I.G. (in preparation). Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles.
Relevant Science Publication Citation:
GeoNEX Surface Reflectance for Vegetation Indices (NDVI & NIRv)- Wang, W., Wang, Y., Lyapustin, A., Hashimoto, H., Park, T., Michaelis, A., & Nemani, R. (2022). A novel atmospheric correction algorithm to exploit the diurnal variability in hypertemporal geostationary observations. Remote Sensing, 14(4), 964.
- Li, R., Wang, D., Wang, W., & Nemani, R. (2023). A GeoNEX-based high-spatiotemporal-resolution product of land surface downward shortwave radiation and photosynthetically active radiation. Earth System Science Data, 15(3), 1419-1436.
- Jia, A., Liang, S., & Wang, D. (2022). Generating a 2-km, all-sky, hourly land surface temperature product from Advanced Baseline Imager data. Remote Sensing of Environment, 278, 113105.
US-Bar: Bartlett Experimental Forest
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AmeriFlux Publications | Add Publication |
Year | Publication |
---|---|
2022 | Teets, A., Moore, D. J., Alexander, M. R., Blanken, P. D., Bohrer, G., Burns, S. P., Carbone, M. S., Ducey, M. J., Fraver, S., Gough, C. M., Hollinger, D. Y., Koch, G., Kolb, T., Munger, J. W., Novick, K. A., Ollinger, S. V., Ouimette, A. P., Pederson, N., Ricciuto, D. M., Seyednasrollah, B., Vogel, C. S., Richardson, A. D. (2022) Coupling Of Tree Growth And Photosynthetic Carbon Uptake Across Six North American Forests, Journal Of Geophysical Research: Biogeosciences, 127(4), . https://doi.org/10.1029/2021JG006690 |
2021 | Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., Zona, D. (2021) Representativeness Of Eddy-Covariance Flux Footprints For Areas Surrounding Ameriflux Sites, Agricultural And Forest Meteorology, 301-302, 108350. https://doi.org/10.1016/j.agrformet.2021.108350 |
2020 | Xu, B., Arain, M. A., Black, T. A., Law, B. E., Pastorello, G. Z., Chu, H. (2020) Seasonal Variability Of Forest Sensitivity To Heat And Drought Stresses: A Synthesis Based On Carbon Fluxes From North American Forest Ecosystems, Global Change Biology, 26(2), 901-918. https://doi.org/10.1111/gcb.14843 |
2019 | Guerrieri, R., Belmecheri, S., Ollinger, S. V., Asbjornsen, H., Jennings, K., Xiao, J., Stocker, B. D., Martin, M., Hollinger, D. Y., Bracho-Garrillo, R., Clark, K., Dore, S., Kolb, T., Munger, J. W., Novick, K., Richardson, A. D. (2019) Disentangling The Role Of Photosynthesis And Stomatal Conductance On Rising Forest Water-Use Efficiency, Proceedings Of The National Academy Of Sciences, 116(34), 16909-16914. https://doi.org/10.1073/pnas.1905912116 |
2018 | Helliker, B. R., Song, X., Goulden, M. L., Clark, K., Bolstad, P., Munger, J. W., Chen, J., Noormets, A., Hollinger, D., Wofsy, S., Martin, T., Baldocchi, D., Euskirchenn, E., Desai, A., Burns, S. P. (2018) Assessing The Interplay Between Canopy Energy Balance And Photosynthesis With Cellulose δ18o: Large-Scale Patterns And Independent Ground-Truthing, Oecologia, . https://doi.org/10.1007/s00442-018-4198-z |
2018 | Fer, I. and Kelly, R. and Moorcroft, P. R. and Richardson, A. D. and Cowdery, E. M. and Dietze, M. C. (2018) Linking Big Models To Big Data: Efficient Ecosystem Model Calibration Through Bayesian Model Emulation, Biogeosciences, 15(19), 5801-5830. https://doi.org/10.5194/bg-15-5801-2018 |
2018 | Ouimette, A. P., Ollinger, S. V., Richardson, A. D., Hollinger, D. Y., Keenan, T. F., Lepine, L. C., Vadeboncoeur, M. A. (2018) Carbon Fluxes And Interannual Drivers In A Temperate Forest Ecosystem Assessed Through Comparison Of Top-Down And Bottom-Up Approaches, Agricultural And Forest Meteorology, 256-257, 420-430. https://doi.org/10.1016/j.agrformet.2018.03.017 |
2017 | Porras, R. C., Hicks Pries, C. E., McFarlane, K. J., Hanson, P. J., Torn, M. S. (2017) Association With Pedogenic Iron And Aluminum: Effects On Soil Organic Carbon Storage And Stability In Four Temperate Forest Soils, Biogeochemistry, 133(3), 333-345. https://doi.org/10.1007/s10533-017-0337-6 |
2016 | Wolf, S., Keenan, T.F., Fisher, J.B., Baldocchi, D.D., Desai, A.R., Richardson, A.D., Scott, R.L., Law, B.E., Litvak, M.E., Brunsell, N.A., Peters, W., van der Laan-Luijkx, I.T. (2016) Warm spring reduced carbon cycle impact of the 2012 US summer drought, Proceedings of the National Academy of Sciences, 113(21), 5880-5885. https://doi.org/10.1073/pnas.1519620113 |
2016 | Zscheischler, J., Fatichi, S., Wolf, S., Blanken, P., Bohrer, G., Clark, K., Desai, A., Hollinger, D., Keenan, T., Novick, K.A., Seneviratne, S.I. (2016) Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes, Journal of Geophysical Research - Biogeosciences, 121(8), 2186-2198. https://doi.org/10.1002/2016JG003503 |
2016 | Novick, K. A., Ficklin, D. L., Stoy, P. C., Williams, C. A., Bohrer, G., Oishi, A., Papuga, S. A., Blanken, P. D., Noormets, A., Sulman, B. N., Scott, R. L., Wang, L., Phillips, R. P. (2016) The Increasing Importance Of Atmospheric Demand For Ecosystem Water And Carbon Fluxes, Nature Climate Change, 6(11), 1023-1027. https://doi.org/10.1038/nclimate3114 |
2015 | Toomey, M., Friedl, M. A., Frolking, S., Hufkens, K., Klosterman, S., Sonnentag, O., Baldocchi, D. D., Bernacchi, C. J., Biraud, S. C., Bohrer, G., Brzostek, E., Burns, S. P., Coursolle, C., Hollinger, D. Y., Margolis, H. A., McCaughey, H., Monson, R. K., Munger, J. W., Pallardy, S., Phillips, R. P., Torn, M. S., Wharton, S., Zeri, M., Richardson, A. D. (2015) Greenness Indices From Digital Cameras Predict The Timing And Seasonal Dynamics Of Canopy-Scale Photosynthesis, Ecological Applications, 25(1), 99-115. https://doi.org/http://doi.org/10.1890/14-0005.1 |
2013 | McFarlane, K. J., Torn, M. S., Hanson, P. J., Porras, R. C., Swanston, C. W., Callaham, M. A., Guilderson, T. P. (2013) Comparison Of Soil Organic Matter Dynamics At Five Temperate Deciduous Forests With Physical Fractionation And Radiocarbon Measurements, Biogeochemistry, 112(1-3), 457-476. https://doi.org/10.1007/s10533-012-9740-1 |
2013 | Keenan, T. F., Hollinger, D. Y., Bohrer, G., Dragoni, D., Munger, J. W., Schmid, H. P., Richardson, A. D. (2013) Increase In Forest Water-Use Efficiency As Atmospheric Carbon Dioxide Concentrations Rise, Nature, 499(7458), 324-327. https://doi.org/10.1038/nature12291 |
2007 | Jenkins, J., Richardson, A., Braswell, B., Ollinger, S., Hollinger, D., Smith, M. (2007) Refining Light-Use Efficiency Calculations For A Deciduous Forest Canopy Using Simultaneous Tower-Based Carbon Flux And Radiometric Measurements, Agricultural And Forest Meteorology, 143(1-2), 64-79. https://doi.org/10.1016/j.agrformet.2006.11.008 |
2007 | Richardson, A. D., Jenkins, J. P., Braswell, B. H., Hollinger, D. Y., Ollinger, S. V., Smith, M. (2007) Use Of Digital Webcam Images To Track Spring Green-Up In A Deciduous Broadleaf Forest, Oecologia, 152(2), 323-334. https://doi.org/10.1007/s00442-006-0657-z |
2005 | Ollinger, S. V., Smith, M. (2005) Net Primary Production And Canopy Nitrogen In A Temperate Forest Landscape: An Analysis Using Imaging Spectroscopy, Modeling And Field Data, Ecosystems, 8(7), 760-778. https://doi.org/10.1007/s10021-005-0079-5 |
2002 | Smith, M., Ollinger, S. V., Martin, M. E., Aber, J. D., Hallett, R. A., Goodale, C. L. (2002) Direct Estimation Of Aboveground Forest Productivity Through Hyperspectral Remote Sensing Of Canopy Nitrogen, Ecological Applications, 12(5), 1286-1302. https://doi.org/10.2307/3099972 |
US-Bar: Bartlett Experimental Forest
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BADM for This Site
Access the Biological, Ancillary, Disturbance and Metadata (BADM) information and data for this site.
BADM contain information for many uses, such as characterizing a site’s vegetation and soil, describing disturbance history, and defining instrumentation for flux processing. They complement the flux/met data.
- Download BADM for this site*
- View Site General Info for this site (Overview tab)*
- Use Online Editor to update Site General Info or DOI Authorship
- Update information about submitted data (Variable Information tool)
- More BADM resources
* Online updates are shown on the Overview tab real time. However, downloaded BADM files will not reflect those updates until they have been reviewed for QA/QC.
US-Bar: Bartlett Experimental Forest
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
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- MODIS
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Wind Roses
Wind Speed (m/s)
Navigation
- Wind Speed Scale: Per Site
- Wind Direction Scale (%): Per Site
- Wind Speed Scale: Non-Linear
- Wind Direction Scale (%): AmeriFlux