IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v27y1995i1p55-68.html
   My bibliography  Save this article

Remote sensing of crop coefficients for improving the irrigation scheduling of corn

Author

Listed:
  • Bausch, Walter C.

Abstract

No abstract is available for this item.

Suggested Citation

  • Bausch, Walter C., 1995. "Remote sensing of crop coefficients for improving the irrigation scheduling of corn," Agricultural Water Management, Elsevier, vol. 27(1), pages 55-68, April.
    • Handle: RePEc:eee:agiwat:v:27:y:1995:i:1:p:55-68
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0378-3774(95)01125-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Duchemin, B. & Hadria, R. & Erraki, S. & Boulet, G. & Maisongrande, P. & Chehbouni, A. & Escadafal, R. & Ezzahar, J. & Hoedjes, J.C.B. & Kharrou, M.H. & Khabba, S. & Mougenot, B. & Olioso, A. & Rodrig, 2006. "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, Elsevier, vol. 79(1), pages 1-27, January.
    2. French, Andrew N. & Hunsaker, Douglas J. & Sanchez, Charles A. & Saber, Mazin & Gonzalez, Juan Roberto & Anderson, Ray, 2020. "Satellite-based NDVI crop coefficients and evapotranspiration with eddy covariance validation for multiple durum wheat fields in the US Southwest," Agricultural Water Management, Elsevier, vol. 239(C).
    3. Li, Dazhi & Hendricks Franssen, Harrie-Jan & Han, Xujun & Jiménez-Bello, Miguel Angel & Martínez Alzamora, Fernando & Vereecken, Harry, 2018. "Evaluation of an operational real-time irrigation scheduling scheme for drip irrigated citrus fields in Picassent, Spain," Agricultural Water Management, Elsevier, vol. 208(C), pages 465-477.
    4. Jayanthi, Harikishan & Neale, Christopher M.U. & Wright, James L., 2007. "Development and validation of canopy reflectance-based crop coefficient for potato," Agricultural Water Management, Elsevier, vol. 88(1-3), pages 235-246, March.
    5. Mahmoud, Shereif H. & Gan, Thian Yew, 2019. "Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data," Agricultural Water Management, Elsevier, vol. 212(C), pages 35-47.
    6. Gonzalez-Dugo, M.P. & Mateos, L., 2008. "Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops," Agricultural Water Management, Elsevier, vol. 95(1), pages 48-58, January.
    7. Carpintero, E. & Mateos, L. & Andreu, A. & González-Dugo, M.P., 2020. "Effect of the differences in spectral response of Mediterranean tree canopies on the estimation of evapotranspiration using vegetation index-based crop coefficients," Agricultural Water Management, Elsevier, vol. 238(C).
    8. Sánchez, Nilda & Martínez-Fernández, José & Calera, Alfonso & Torres, Enrique & Pérez-Gutiérrez, Carlos, 2010. "Combining remote sensing and in situ soil moisture data for the application and validation of a distributed water balance model (HIDROMORE)," Agricultural Water Management, Elsevier, vol. 98(1), pages 69-78, December.
    9. Muhammad Athar Haroon & Jiahua Zhang & Fengmei Yao, 2016. "Drought monitoring and performance evaluation of MODIS-based drought severity index (DSI) over Pakistan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 1349-1366, November.
    10. Elshikha, Diaa Eldin M. & Hunsaker, Douglas J. & Waller, Peter M. & Thorp, Kelly R. & Dierig, David & Wang, Guangyao & Cruz, Von Mark V. & Katterman, Matthew E. & Bronson, Kevin F. & Wall, Gerard W. &, 2022. "Estimation of direct-seeded guayule cover, crop coefficient, and yield using UAS-based multispectral and RGB data," Agricultural Water Management, Elsevier, vol. 265(C).
    11. Drerup, Philipp & Brueck, Holger & Scherer, Heinrich W., 2017. "Evapotranspiration of winter wheat estimated with the FAO 56 approach and NDVI measurements in a temperate humid climate of NW Europe," Agricultural Water Management, Elsevier, vol. 192(C), pages 180-188.
    12. de Medeiros, Gerson A. & Arruda, Flavio B. & Sakai, Emilio & Fujiwara, Mamor, 2001. "The influence of crop canopy on evapotranspiration and crop coefficient of beans (Phaseolus vulgaris L.)," Agricultural Water Management, Elsevier, vol. 49(3), pages 211-224, August.
    13. Bastiaanssen, Wim G. M. & Molden, David J. & Makin, Ian W., 2000. "Remote sensing for irrigated agriculture: examples from research and possible applications," Agricultural Water Management, Elsevier, vol. 46(2), pages 137-155, December.
    14. Ray, S. S. & Dadhwal, V. K., 2001. "Estimation of crop evapotranspiration of irrigation command area using remote sensing and GIS," Agricultural Water Management, Elsevier, vol. 49(3), pages 239-249, August.
    15. Zhang, Yu & Han, Wenting & Zhang, Huihui & Niu, Xiaotao & Shao, Guomin, 2023. "Evaluating maize evapotranspiration using high-resolution UAV-based imagery and FAO-56 dual crop coefficient approach," Agricultural Water Management, Elsevier, vol. 275(C).
    16. Corbari, Chiara & Salerno, Raffaele & Ceppi, Alessandro & Telesca, Vito & Mancini, Marco, 2019. "Smart irrigation forecast using satellite LANDSAT data and meteo-hydrological modeling," Agricultural Water Management, Elsevier, vol. 212(C), pages 283-294.
    17. Pôças, I. & Calera, A. & Campos, I. & Cunha, M., 2020. "Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches," Agricultural Water Management, Elsevier, vol. 233(C).
    18. Toureiro, Célia & Serralheiro, Ricardo & Shahidian, Shakib & Sousa, Adélia, 2017. "Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition," Agricultural Water Management, Elsevier, vol. 184(C), pages 211-220.
    19. Er-Raki, S. & Chehbouni, A. & Guemouria, N. & Duchemin, B. & Ezzahar, J. & Hadria, R., 2007. "Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region," Agricultural Water Management, Elsevier, vol. 87(1), pages 41-54, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:27:y:1995:i:1:p:55-68. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.