US-Tx3: Riesel Farm Aspirational Agriculture

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Use the information below for citation of this site. See the Data Policy page for more details.

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US-Tx3: Riesel Farm Aspirational Agriculture

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US-Tx3: Riesel Farm Aspirational Agriculture

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Riesel Farm Aspirational Agriculture site
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**Credit:** Aline Jaimes
**Site ID:** US-Tx3
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US-Tx3: Riesel Farm Aspirational Agriculture

Overview
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Remote Sensing Data
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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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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-Tx3:

tworfaa

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

PhenoCam site: tworfaa

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.

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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-Tx3: Riesel Farm Aspirational Agriculture

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US-Tx3: Riesel Farm Aspirational Agriculture

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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-Tx3: Riesel Farm Aspirational Agriculture

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Tower_team:
PI:	Binayak Mohanty bmohanty@tamu.edu - Texas A&M University
DataManager:	Beomseok Chun cbsuk97@tamu.edu - Texas A&M University
Technician:	Kyle Tiner kyle.tiner@ars.usda.gov - USDA
Lat, Long:	31.4777, -96.8883
Elevation(m):	167
Network Affiliations:	AmeriFlux, LTAR, 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:	Cfa (Humid Subtropical: mild with no dry season, hot summer)
Mean Annual Temp (°C):	18.95
Mean Annual Precip. (mm):	914
Flux Species Measured:	CO2, H, H2O, Other
Years Data Collected:	2016 - Present
Years Data Available:	No data available
Data Use Policy:	AmeriFlux Legacy Policy
Description:	This tower site is located just 2½ miles from Riesel town’s center. It is a 840-acre Agricultural Research Service experimental watershed facility nicknamed ... This tower site is located just 2½ miles from Riesel town’s center. It is a 840-acre Agricultural Research Service experimental watershed facility nicknamed the Riesel Watersheds. The tower is located in a crop field grown under best management practices See More Show Less
URL:	http://two.tamu.edu/sites/primary/rfaa.aspx
Research Topics:	The Texas Water Observatory (TWO) is a distributed network of field observatories in Brazos River corridor and was developed to better understand hydrologic ... The Texas Water Observatory (TWO) is a distributed network of field observatories in Brazos River corridor and was developed to better understand hydrologic flow across natural and manmade reservoirs in the critical zone. The network monitors and measures groundwater, soil water, surface water, and atmospheric water at multiple locations across space and through time. See More Show Less
Acknowledgment:	This research was supported by grants to the Texas Water Observatory from the US Department of Agriculture - Agricultural Research Service (USDA-ARS) and the Texas A&M University Research and Development Fund.

US-Tx3: Riesel Farm Aspirational Agriculture

US-Tx3: Riesel Farm Aspirational Agriculture

DOI(s) for citing US-Tx3 data

Publication(s) for citing site characterization

Acknowledgments

Resources

US-Tx3: Riesel Farm Aspirational Agriculture

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US-Tx3: Riesel Farm Aspirational Agriculture

Riesel Farm Aspirational Agriculture site

US-Tx3: Riesel Farm Aspirational Agriculture

US-Tx3: Riesel Farm Aspirational Agriculture

BADM for This Site

US-Tx3: Riesel Farm Aspirational Agriculture

No wind rose data is available at this time.