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Advances in Meteorology
Volume 2018, Article ID 4525021, 12 pages
https://doi.org/10.1155/2018/4525021
Research Article

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

1Department of Agricultural and Biosystems Engineering, South Dakota State University, Brookings, SD, USA
2Instituto Nacional de Investigaciones Agrícolas, Forestales y Pecuarias (INIFAP), Blvd. Prof. José Santos Valdez, No. 1200 Pte, Col. Centro, Matamoros, COAH, Mexico
3Minnesota Department of Agriculture, St. Paul, MN, USA
4Iowa Soybean Association, Ankeny, IA, USA

Correspondence should be addressed to Arturo Reyes-González; xm.bog.pafini@orutra.seyer

Received 25 August 2017; Accepted 26 December 2017; Published 1 February 2018

Academic Editor: Jan Friesen

Copyright © 2018 Arturo Reyes-González et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. F. Heermann and K. H. Solomon, “Efficiency and uniformity,” Design and operation of farm irrigation systems, vol. 5, pp. 108–119, 2007. View at Google Scholar
  2. N. K. Gontia and K. N. Tiwari, “Estimation of crop coefficient and evapotranspiration of wheat (Triticum aestivum) in an irrigation command using remote sensing and GIS,” Water Resources Management, vol. 24, no. 7, pp. 1399–1414, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. H. V. Parmar and N. K. Gontia, “Remote sensing based vegetation indices and crop coefficient relationship for estimation of crop evapotranspiration in Ozat-II canal command,” Journal of Agrometeorology, vol. 18, no. 1, pp. 137–139, 2016. View at Google Scholar · View at Scopus
  4. E. Adamala, Y. A. Rajwade, and Y. V. K. Reddy, “Estimation of wheat crop evapotranspiration using NDVI vegetation index,” Journal of Applied and Natural Science, vol. 8, no. 1, pp. 159–166, 2016. View at Google Scholar
  5. R. G. Allen, L. S. Pereira, D. Raes, and M. Smith, Crop evapotranspiration: Guide-lines for computing crop requirements, Irrigation and Drainage Paper no. 56, FAO, Rome, Italy, 1998.
  6. R. G. Allen, A. J. Clemmens, C. M. Burt, K. Solomon, and T. O'Halloran, “Prediction accuracy for projectwide evapotranspiration using crop coefficients and reference evapotranspiration,” Journal of Irrigation and Drainage Engineering, vol. 131, no. 1, pp. 24–36, 2005. View at Publisher · View at Google Scholar · View at Scopus
  7. M. E. Jensen and R. G. Allen, Evaporation, Evapotranspiration, and Irrigation Water Requirements, ASCE Manuals and reports on Engineering Practice: no 70, American Society of Civil Engineers, Reston, Virginia , USA, 2nd edition, 2016. View at Publisher · View at Google Scholar
  8. W. G. M. Bastiaanssen, E. J. M. Noordman, H. Pelgrum, G. Davids, B. P. Thoreson, and R. G. Allen, “SEBAL model with remotely sensed data to improve water-resources management under actual field conditions,” Journal of Irrigation and Drainage Engineering, vol. 131, no. 1, pp. 85–93, 2005. View at Publisher · View at Google Scholar · View at Scopus
  9. R. Allen, M. Tasumi, and R. Trezza, “Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—model,” Journal of Irrigation and Drainage Engineering, vol. 133, no. 4, pp. 380–394, 2007. View at Publisher · View at Google Scholar · View at Scopus
  10. J. Kjaersgaard, R. Allen, and A. Irmak, “Improved methods for estimating monthly and growing season ET using METRIC applied to moderate resolution satellite imagery,” Hydrological Processes, vol. 25, no. 26, pp. 4028–4036, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. A. Reyes-González, J. Kjaersgaard, T. Trooien, C. Hay, and L. Ahiablame, “Comparative Analysis of METRIC Model and Atmometer Methods for Estimating Actual Evapotranspiration,” International Journal of Agronomy, vol. 2017, pp. 1–16, 2017. View at Publisher · View at Google Scholar
  12. C. M. U. Neale, H. Jayanthi, and J. L. Wright, “Irrigation water management using high resolution airborne remote sensing,” Irrigation and Drainage Systems, vol. 19, no. 3-4, pp. 321–336, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. E. P. Glenn, C. M. U. Neale, D. J. Hunsaker, and P. L. Nagler, “Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems,” Hydrological Processes, vol. 25, no. 26, pp. 4050–4062, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. J. W. Rouse, R. H. Haas, J. A. Schell, and D. W. Deering, “Monitoring vegetation systems in the Great Plains with ERTS,” in Third ERTS symposium, pp. 309–317, NASA, Washington DC, USA, 10-14 December 1973.
  15. E. P. Glenn, P. L. Nagler, and A. R. Huete, “Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing,” Surveys in Geophysics, vol. 31, no. 6, pp. 531–555, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. C. Romero-Trigueros, P. A. Nortes, J. J. Alarcón et al., “Effects of saline reclaimed waters and deficit irrigation on Citrus physiology assessed by UAV remote sensing,” Agricultural Water Management, vol. 183, pp. 60–69, 2017. View at Publisher · View at Google Scholar · View at Scopus
  17. C. Toureiro, R. Serralheiro, S. Shahidian, and A. Sousa, “Irrigation management with remote sensing: evaluating irrigation requirement for maize under Mediterranean climate condition,” Agricultural Water Management, vol. 184, pp. 211–220, 2017. View at Publisher · View at Google Scholar · View at Scopus
  18. H. Lei and D. Yang, “Combining the crop coefficient of winter wheat and summer maize with a remotely sensed vegetation index for estimating evapotranspiration in the North China plain,” Journal of Hydrologic Engineering, vol. 19, no. 1, pp. 243–251, 2014. View at Publisher · View at Google Scholar · View at Scopus
  19. E. G. Kullberg, K. C. DeJonge, and J. L. Chávez, “Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients,” Agricultural Water Management, vol. 179, pp. 64–73, 2017. View at Publisher · View at Google Scholar
  20. C. M. U. Neale, W. C. Bausch, and D. F. Herman, “Development of reflectance-based crop coefficient for corn,” Transactions of the ASAE, vol. 32, no. 6, pp. 1891–1899, 1989. View at Google Scholar
  21. W. C. Bausch, “Remote sensing of crop coefficients for improving the irrigation scheduling of corn,” Agricultural Water Management, vol. 27, no. 1, pp. 55–68, 1995. View at Publisher · View at Google Scholar · View at Scopus
  22. J. Garatuza-Payan, A. Tamayo, C. Watts, and J. Rodriguez, “Estimating large area wheat evapotranspiration from remote sensing data,” in Proceedings of the IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium., pp. 380–382, Toulouse, France. View at Publisher · View at Google Scholar
  23. D. J. Hunsaker, P. J. Pinter Jr., E. M. Barnes, and B. A. Kimball, “Estimating cotton evapotranspiration crop coefficients with a multispectral vegetation index,” Irrigation Science, vol. 22, no. 2, pp. 95–104, 2003. View at Publisher · View at Google Scholar · View at Scopus
  24. M. Tasumi, R. G. Allen, R. Trezza, and J. L. Wright, “Satellite-based energy balance to assess within-population variance of crop coefficient curves,” Journal of Irrigation and Drainage Engineering, vol. 131, no. 1, pp. 94–109, 2005. View at Publisher · View at Google Scholar · View at Scopus
  25. B. Duchemin, R. Hadria, S. Erraki et al., “Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices,” Agricultural Water Management, vol. 79, no. 1, pp. 1–27, 2006. View at Publisher · View at Google Scholar · View at Scopus
  26. H. Jayanthi, C. M. U. Neale, and J. L. Wright, “Development and validation of canopy reflectance-based crop coefficient for potato,” Agricultural Water Management, vol. 88, no. 1-3, pp. 235–246, 2007. View at Publisher · View at Google Scholar · View at Scopus
  27. T. J. Trout, “Remote sensing of canopy cover in horticultural crops,” HortScience, vol. 43, no. 2, pp. 333–337, 2008. View at Google Scholar
  28. M. P. González-Dugo and L. Mateos, “Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops,” Agricultural Water Management, vol. 95, no. 1, pp. 48–58, 2008. View at Publisher · View at Google Scholar · View at Scopus
  29. I. Campos, C. M. U. Neale, A. Calera, C. Balbontín, and J. González-Piqueras, “Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.),” Agricultural Water Management, vol. 98, no. 1, pp. 45–54, 2010. View at Publisher · View at Google Scholar · View at Scopus
  30. B. Kamble, A. Kilic, and K. Hubbard, “Estimating crop coefficients using remote sensing-based vegetation index,” Remote Sensing, vol. 5, no. 4, pp. 1588–1602, 2013. View at Publisher · View at Google Scholar · View at Scopus
  31. A. Reyes-González, C. Hay, J. Kjaersgaard, and C. M. U. Neale, “Use of remote sensing to generate crop coefficient and estimate actual crop evapotranspiration,” in ASABE Annual international meeting, New Orleans LA, USA, 2015.
  32. E. Farg, S. M. Arafat, M. S. Abd El-Wahed, and A. M. El-Gindy, “Estimation of Evapotranspiration ETc and Crop Coefficient Kc of Wheat, in south Nile Delta of Egypt Using integrated FAO-56 approach and remote sensing data,” Egyptian Journal of Remote Sensing and Space Science, vol. 15, no. 1, pp. 83–89, 2012. View at Publisher · View at Google Scholar · View at Scopus
  33. S. Vanino, G. Pulighe, P. Nino, C. de Michele, S. F. Bolognesi, and G. D'Urso, “Estimation of evapotranspiration and crop coefficients of tendone vineyards using multi-sensor remote sensing data in a mediterranean environment,” Remote Sensing, vol. 7, no. 11, pp. 14708–14730, 2015. View at Publisher · View at Google Scholar · View at Scopus
  34. H. Zhang, R. G. Anderson, and D. Wang, “Satellite-based crop coefficient and regional water use estimates for Hawaiian sugarcane,” Field Crops Research, vol. 180, pp. 143–154, 2015. View at Publisher · View at Google Scholar · View at Scopus
  35. SAGARPA, “Resumen Sector Agropecuario en la Región Lagunera,” Publicación especial el Siglo de Torreón, p. 24, 2016. View at Google Scholar
  36. R. P. Cano and M. M. C. Medina, “Tecnologia de produccion de nogal pecanero,” Libro Tecnico, vol. no. 3, p. 220, 2002. View at Google Scholar
  37. G. Levin, G. A. Cruz, D. Garcia, C. Garces-Restrepo, and S. Johnson, Performance of two transferred modules in the lagunera region: water relations, Research Report 23, vol. 23, nternational Water Management Institute, Colombo, Sri Lanka, 1998.
  38. W. C. Bausch, “Soil background effects on reflectance-based crop coefficients for corn,” Remote Sensing of Environment, vol. 46, no. 2, pp. 213–222, 1993. View at Publisher · View at Google Scholar · View at Scopus
  39. A. Bannari, D. Morin, F. Bonn, and A. R. Huete, “A review of vegetation indices,” International Journal of Remote Sensing , vol. 13, no. 1-2, pp. 95–120, 1995. View at Publisher · View at Google Scholar · View at Scopus
  40. A. Reyes-González, U. Figueroa, D. G. Reta, J. I. Sanchez, and J. G. Martinez, Estimación de la evapotranspiración actual utilizando sensors remotos y mediciones in situ, En la Comarca Lagunera, Mexico, 2012.
  41. ASCE-EWRI, “The ASCE Standardized Reference Evapotranspiration Equation. Report of the ASCE-EWRI Task Committee on Standardization of Reference Evapotranspiration,” Tech. Rep., ASCE, Reston, VA, USA, 2005. View at Google Scholar
  42. T. J. Jackson, D. Chen, M. Cosh et al., “Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans,” Remote Sensing of Environment, vol. 92, no. 4, pp. 475–482, 2004. View at Publisher · View at Google Scholar · View at Scopus
  43. P.-Y. Chen, G. Fedosejevs, M. Tiscareño-López, and J. G. Arnold, “Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: An example at corn fields in western Mexico,” Environmental Modeling & Assessment, vol. 119, no. 1-3, pp. 69–82, 2006. View at Publisher · View at Google Scholar · View at Scopus
  44. W. E. Thomason, S. B. Phillips, and F. D. Raymond, “Defining useful limits for spectral reflectance measures in corn,” Journal of Plant Nutrition, vol. 30, no. 8, pp. 1263–1277, 2007. View at Publisher · View at Google Scholar · View at Scopus
  45. R. K. Singh and A. Irmak, “Estimation of crop coefficients using satellite remote sensing,” Journal of Irrigation and Drainage Engineering, vol. 135, no. 5, pp. 597–608, 2009. View at Publisher · View at Google Scholar · View at Scopus
  46. C. H. W. de Souza, E. Mercante, J. A. Johann, R. A. C. Lamparelli, and M. A. Uribe-Opazo, “Mapping and discrimination of soya bean and corn crops using spectro-temporal profiles of vegetation indices,” International Journal of Remote Sensing, vol. 36, no. 7, pp. 1809–1824, 2015. View at Publisher · View at Google Scholar · View at Scopus
  47. F. Gao, M. C. Anderson, X. Zhang et al., “Toward mapping crop progress at field scales through fusion of Landsat and MODIS imagery,” Remote Sensing of Environment, vol. 188, pp. 9–25, 2017. View at Publisher · View at Google Scholar · View at Scopus
  48. N. Flood, “Continuity of reflectance data between landsat-7 ETM+ and landsat-8 OLI, for both top-of-atmosphere and surface reflectance: a study in the australian landscape,” Remote Sensing, vol. 6, no. 9, pp. 7952–7970, 2014. View at Publisher · View at Google Scholar · View at Scopus
  49. Y. Ke, J. Im, J. Lee, H. Gong, and Y. Ryu, “Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations,” Remote Sensing of Environment, vol. 164, pp. 298–313, 2015. View at Publisher · View at Google Scholar · View at Scopus
  50. D. P. Roy, V. Kovalskyy, H. K. Zhang et al., “Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity,” Remote Sensing of Environment, vol. 185, pp. 57–70, 2016. View at Publisher · View at Google Scholar · View at Scopus
  51. D. P. Roy, M. A. Wulder, T. R. Loveland et al., “Landsat-8: science and product vision for terrestrial global change research,” Remote Sensing of Environment, vol. 145, pp. 154–172, 2014. View at Publisher · View at Google Scholar · View at Scopus
  52. C. E. Holden and C. E. Woodcock, “An analysis of Landsat 7 and Landsat 8 underflight data and the implications for time series investigations,” Remote Sensing of Environment, vol. 185, pp. 16–36, 2016. View at Publisher · View at Google Scholar · View at Scopus
  53. J. Rocha, A. Perdigão, R. Melo, and C. Henriques, “Remote sensing based crop coefficients for water management in agriculture,Chapter 8,” INTECH, pp. 167–192, 2012. View at Google Scholar
  54. A. Reyes-González, T. Trooien, J. Kjaersgaard, C. Hay, and D. G. Reta-Sánchez, “Development of crop coefficients using remote sensing-based vegetation index and growing degree days,” in Proceedings of the ASABE Annual International Meeting, Orlando, Fla, USA, July 2016. View at Publisher · View at Google Scholar · View at Scopus
  55. E. B. Rafn, B. Contor, and D. P. Ames, “Evaluation of a method for estimating irrigated crop-evapotranspiration coefficients from remotely sensed data in Idaho,” Journal of Irrigation and Drainage Engineering, vol. 134, no. 6, pp. 722–729, 2008. View at Publisher · View at Google Scholar · View at Scopus
  56. R. G. Steel and J. H. Torrie, Principles and procedures of statistic: a biometrical approach, McGraw-Hill, NY, USA, 1980.
  57. A. Irmak, I. Ratcliffe, P. Ranade et al., “Estimation of land surface evapotranspiration with a satellite remote sensing procedure,” Great Plains Research, vol. 21, no. 1, pp. 73–88, 2011. View at Google Scholar · View at Scopus
  58. L. Rossato, R. C. S. Alvalá, N. J. Ferreira, and J. Tomasella, “Evapotranspiration estimation in the Brazil using NDVI data,” in Proceedings of the Remote Sensing for Agriculture, Ecosystems, and Hydrology VII, Belgium, September 2005. View at Publisher · View at Google Scholar · View at Scopus
  59. M. Mahour, V. Tolpekin, A. Stein, and A. Sharifi, “A comparison of two downscaling procedures to increase the spatial resolution of mapping actual evapotranspiration,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 126, pp. 56–67, 2017. View at Publisher · View at Google Scholar · View at Scopus
  60. M. P. Gonzalez-Dugo, C. M. U. Neale, L. Mateos et al., “A comparison of operational remote sensing-based models for estimating crop evapotranspiration,” Agricultural and Forest Meteorology, vol. 149, no. 11, pp. 1843–1853, 2009. View at Publisher · View at Google Scholar · View at Scopus
  61. R. S. Murray, P. L. Nagler, K. Morino, and E. P. Glenn, “An empirical algorithm for estimating agricultural and riparian evapotranspiration using MODIS enhanced vegetation index and ground measurements of ET. II. application to the lower Colorado river, U.S.,” Remote Sensing, vol. 1, no. 4, pp. 1125–1138, 2009. View at Publisher · View at Google Scholar · View at Scopus
  62. S. C. Zipper and S. P. Loheide, “Using evapotranspiration to assess drought sensitivity on a subfield scale with HRMET, a high resolution surface energy balance model,” Agricultural and Forest Meteorology, vol. 197, pp. 91–102, 2014. View at Publisher · View at Google Scholar · View at Scopus
  63. G. B. Senay, M. Friedrichs, R. K. Singh, and N. M. Velpuri, “Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin,” Remote Sensing of Environment, vol. 185, pp. 171–185, 2016. View at Publisher · View at Google Scholar · View at Scopus
  64. USDA-NASS, Farm and Ranch Irrigation Survey, Table 22-Methods used in deciding when to irrigate USDA National Agricultural Statistics Service, 2013.
  65. J. C. Henggeler, M. D. Dukes, and B. Q. Mecham, “Chapter 13 Irrigation Scheduling,” in Irrigation, L. E. Stetson and B. Q. Mecham, Eds., pp. 491–564, Falls Church, VA, USA, 6th edition, 2011. View at Google Scholar