Technical Notes
Apr 23, 2020

Correcting the Edge Effect for Sensor Spatial Response in Evapotranspiration Estimation through Remote Sensing

Publication: Journal of Irrigation and Drainage Engineering
Volume 146, Issue 7

Abstract

Recent advances in remote-sensing technology using multispectral images provide a powerful tool to estimate crop-water evapotranspiration (ET) at the watershed scale with large spatial and temporal precision. However, most current sensors onboard operational satellites that capture radiances from the thermal infrared (TIR) spectral region are still constrained by limited spatial resolution, which creates a potential error called the edge effect. This consists of information intrusion from surrounding areas that crosses the boundary of the region of interest due to coarse pixel resolution. To reduce this error, a buffer zone is defined as a fixed distance from the field boundary, and the information contained in this zone is excluded from the sample. This study evaluates the optimal buffer distance needed to minimize the bias associated with the aggregated edge effect in annual ET estimates when using Landsat-7 enhanced thematic mapper plus (ETM+) data. Theoretical and statistical analyses indicate that a buffer of 2-TIR pixel equivalent distance ensures that the remaining field area contain radiances free of edge effects with 98.4% confidence. However, the analysis shows that in a circular turfgrass field of 50.9 ha, this process would eliminate half of the area. The analysis using annual ET data shows that applying a buffer distance of 0.75 TIR pixel is sufficient to mitigate the cumulative edge effect while preserving field representative valuable data. Although this analysis was based on Landsat-7 ETM+ images, the results could also be applied to annual ET maps with different thermal infrared pixel sizes.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

Some or all data, models, or code generated or used during the study are available from the corresponding author by request:
Region of interest pixel data (evapotranspiration, coordinates).
Region of interest descriptive statistics and histograms for pixel evapotranspiration data.

Acknowledgments

The authors acknowledge funding from the New Mexico Office of State Engineer, Rio Grande Basin Initiative, New Mexico’s Governor Water Innovation Fund II, NMSU-Agricultural Experimental Station, and the USDA-AFRI Water Rio Grande Conservation Project.

References

Allen, R. G., M. Tasumi, and R. Trezza. 2007. “Satellite based energy balance for mapping evapotranspiration with internalized calibration.” J. Irrig. Drain. Eng. 133 (4): 380–394. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(380).
Bastiaanssen, W. G. M. 1995. “Regionalization of surface flux densities and moisture indicators in composite terrain: A remote sensing approach under clear skies in Mediterranean climates.” Ph.D. dissertation, Winand Staring Centre for Integrated Land, Landbouwuniversiteit te Wageningen.
Clark, B., R. Soppe, D. Lal, B. Thoreson, W. Bastiaanssen, and G. Davids. 2007. “Variability of crop coefficients in space and time–Examples from California.” In Proc., 4th Int. Conf. on Irrigation and Drainage U.S. Committee on Irrigation and Drainage, edited by A. J. Clemmens and S. S. Anderson. Denver: US Committee on Irrigation and Drainage.
Jones, H. G., and X. R. R. Sirault. 2014. “Scaling of thermal images at different spatial resolution: The mixed pixel problem.” Agronomy 4 (3): 380–396. https://doi.org/10.3390/agronomy4030380.
Kohiyama, M., and F. Yamazaki. 2005. “Image fluctuation model for damage detection using middle-resolution satellite imagery.” Int. J. Remote Sens. 26 (24): 5603–5627. https://doi.org/10.1080/01431160500213896.
Malm, N. R. 2003. “Climate guide: Las Cruces, 1892-2000.” Accessed March 31, 2019. https://aces.nmsu.edu/pubs/research/weather_climate/RR749.pdf.
Markham, B. L. 1985. “The Landsat sensors’ spatial responses.” IEEE Trans. Geosci. Remote Sens. 23 (Nov): 864–875. https://doi.org/10.1109/TGRS.1985.289472.
New Mexico Geospatial Data Acquisition Coordination Committee. 2005. “Strauss, NW quarter 31106 RGB.” 2005 digital orthophotography. Accessed February 27, 2008. http://rgis.unm.edu/.
Piñón-Villarreal, A. R., Z. A. Samani, A. S. Bawazir, M. P. Bleiweis, R. Skaggs, and V. V. Tran. 2010. Estimating water use through satellite remote sensing. Las Cruces, NM: Water Resources Research Institute.
Rodríguez-Galiano, V. F., E. Pardo-Igúzquiza, M. Chica-Olmo, and J. P. Rigol Sánchez. 2011. “Increasing the spatial resolution of thermal infrared images using cokriging.” In Vol. 3 of Proc., 1st Conf. on Spatial Statistics Procedia Environmental Sciences, 117–122. Enschede, Netherlands: Elsevier.
Ryan, R. E., V. Zanoni, M. Pagnutti, B. Davis, B. Markham, and J. Storey. 2003. “Parameters describing Earth observing remote sensing systems.” Accessed July 20, 2017. http://www.commission1.isprs.org/isprs_ceos_workshop/.
Samani, Z., A. S. Bawazir, M. P. Bleiweiss, R. Skaggs, J. Longworth, V. D. Tran, and A. Piñon. 2009. “Using remote sensing to evaluate the spatial variability of evapotranspiration and crop coefficient in the lower Rio Grande Valley, New Mexico.” Irrig. Sci. 28 (1): 93–100. https://doi.org/10.1007/s00271-009-0178-8.
Samani, Z., R. Skaggs, A. Bawazir, M. P. Bleiweiss, V. Tran, and A. Piñón. 2012. “Remote sensing of agricultural water use in New Mexico: From theory to practice.” New Mexico Acad. Sci. New Mexico J. Sci. 47 (1): 1–17.
Tasumi, M., R. G. Allen, R. Trezza, and J. L. Wright. 2007. “Satellite-based energy balance to assess within-population variance of crop coefficient curves.” J. Irrig. Drain. Eng. 131 (1): 94–109. https://doi.org/10.1061/(ASCE)0733-9437.
van der Meer, F. D., and S. M. de Jong. 2001. Imaging spectrometry: Basic principles and prospective applications. Dordrecht, Netherlands: Springer.
Weisstein, E. W. 2017. “Gaussian function: MathWorld wolfram.” Accessed July 27, 2017. http://mathworld.wolfram.com/GaussianFunction.html.
Zhou, G., and N. S.-N. Lam. 2008. “Reducing edge effects in the classification of high resolution imagery.” Photogramm. Eng. Remote Sens. 74 (4): 431–441. https://doi.org/10.14358/PERS.74.4.431.

Information & Authors

Information

Published In

Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 146Issue 7July 2020

History

Received: Apr 8, 2019
Accepted: Jan 30, 2020
Published online: Apr 23, 2020
Published in print: Jul 1, 2020
Discussion open until: Sep 23, 2020

Permissions

Request permissions for this article.

Authors

Affiliations

Aldo R. Piñón-Villarrea, Ph.D., M.ASCE [email protected]
Assistant Professor, David L. Hirschfeld Dept. of Engineering, Angelo State Univ., ASU Station #11056, San Angelo, TX 76909-1056 (corresponding author). Email: [email protected]
Zohrab A. Samani, Ph.D., M.ASCE [email protected]
P.E.
Professor, Dept. of Civil Engineering, New Mexico State Univ., MSC 3CE, P.O. Box 30001, Las Cruces, NM 88003-0083. Email: [email protected]
A. Salim Bawazir, Ph.D., M.ASCE [email protected]
Associate Professor, Dept. of Civil Engineering, New Mexico State Univ., MSC 3CE, P.O. Box 30001, Las Cruces, NM 88003-0057; Member, ReNUWIt, Urban Water Engineering Research Center, Stanford Univ., Y2E2, 473 Via Ortega, Room 311, Stanford, CA 94305. Email: [email protected]
Retired; formerly, Affiliated Staff, Dept. of Entomology, Plant Pathology, and Weed Science, New Mexico State Univ., MSC 3BE, P.O. Box 30001, Las Cruces, NM 88003-0083. ORCID: https://orcid.org/0000-0003-0723-6350. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share