US-RGG: Glenn County Rice Farm

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US-RGG: Glenn County Rice Farm

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US-RGG: Glenn County Rice Farm

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Search Images for this Site Images found : 2

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Day 1, new flux tower in Rice Field (Glenn County, CA)
**Description:**
Picture taken at setup date (11/12/2020).
Keywords: —
**Credit:** Sebastien Biraud
**Site ID:** US-RGG
**Location:** United States
**Image Date:** 2020/11/11
**Journal:** —
**Article Title:** —
**Copyright Permissions:** —
**Right to Use:** Open use

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Site Picture for US-RGG
**Description:**
Picture taken at setup date (11/11/2020).
Keywords: —
**Credit:** Sebastien Biraud
**Site ID:** US-RGG
**Location:** California, United States
**Image Date:** 2020/11/11
**Journal:** —
**Article Title:** —
**Copyright Permissions:** —
**Right to Use:** Open use

View in Original Size
To download, right-click photo (Mac: control-click) and choose Save Image As

US-RGG: Glenn County Rice Farm

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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.

Includes all pixels that have acceptable quality

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

Read more on how to cite these MODIS products. Data come from NASA’s MODIS instruments installed on satellites Terra and Aqua, which scan the entire Earth’s surface every one to two days.

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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-RGG:

glennrice

Use the links below to explore camera images and interactive timeseries for these sites.

PhenoCam site: glennrice

Green Chromatic Coordinate Time Series

ROI: AG_1000

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/s41597-019-0229-9

Camera 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

Beta: This AmeriFlux GeoNEX Products feature is in beta. If you spot any issues, please help us out by emailing geonex-feedback@lbl.gov with a description and/or screenshot of the issue. Thanks in advance!

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 .

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.

GeoNEX Surface Downward Solar Radiation (DSR):

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.

GeoNEX Land Surface Temperature (LST):

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-RGG: Glenn County Rice Farm

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Search Publications for this Site Publications Found: 0

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US-RGG: Glenn County Rice Farm

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BADM for This Site

Access the Biological, Ancillary, Disturbance and Metadata (BADM) information and data for this site.

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US-RGG: Glenn County Rice Farm

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Tower_team:
PI:	Michael Schuppenhauer mschuppenhauer@lbl.gov - Arva Intelligence Corp.
PI:	Sebastien C. Biraud SCBiraud@lbl.gov - Lawrence Berkeley National Laboratory
FluxContact:	Stephen W. Chan SWChan@lbl.gov - Lawrence Berkeley National Laboratory
Lat, Long:	39.5944, -122.0253
Elevation(m):	36
Network Affiliations:	AmeriFlux, Phenocam
Vegetation IGBP:	CRO (Croplands: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type.)
Climate Koeppen:	Csa (Mediterranean: mild with dry, hot summer)
Mean Annual Temp (°C):	16
Mean Annual Precip. (mm):	610
Flux Species Measured:	CO2, CH4, H2O
Years Data Collected:	2020 - 2021
Years Data Available:	No data available
Data Use Policy:	AmeriFlux CC-BY-4.0 Policy¹
Description:	Commercially farmed, mid-grain japonica rice variety, field in Glenn County, California. Part of a multi-year, ground-truthing field study under the DOE ... Commercially farmed, mid-grain japonica rice variety, field in Glenn County, California. Part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project (https://arpa-e.energy.gov/news-and-media/blog-posts/smartfarm-changing-whats-possible-agriculture). Field is approx. 12 ha in size (1,300 ft by 400 ft), part of a 80+ acre site in several checks with commercial rice over rice rotation on silty clay loam. See More Show Less
URL:	—
Research Topics:	Sustainability of bioenergy crops and residues; Reduction of vegetation and fallow season GHG emissions
Acknowledgment:	This work was funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com/) in collaboration with Lawrence Berkeley National Laboratory (LBNL).

US-RGG: Glenn County Rice Farm

US-RGG: Glenn County Rice Farm

DOI(s) for citing US-RGG data

Publication(s) for citing site characterization

Acknowledgments

Resources

US-RGG: Glenn County Rice Farm

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US-RGG: Glenn County Rice Farm

Day 1, new flux tower in Rice Field (Glenn County, CA)

Site Picture for US-RGG

US-RGG: Glenn County Rice Farm

US-RGG: Glenn County Rice Farm

BADM for This Site

US-RGG: Glenn County Rice Farm

No wind rose data is available at this time.