IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v207y2018icp44-52.html
   My bibliography  Save this article

Estimating cotton water consumption using a time series of Sentinel-2 imagery

Author

Listed:
  • Rozenstein, Offer
  • Haymann, Nitai
  • Kaplan, Gregoriy
  • Tanny, Josef

Abstract

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management. Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance. In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse. Kc was estimated as the ratio between reference evapotranspiration and the measured cotton evapotranspiration. In addition, a time series of Sentinel-2 imagery was processed to produce 22 vegetation indices (VIs) based on the sensor’s unique spectral bands. Empirical Kc – VI models were derived and ranked according to their prediction error. In accordance with previous studies, we found a strong correlation between the normalized difference vegetation index (NDVI) and Kc (R2 = 0.94), and yet, we also identified other spectral indices that are more strongly correlated to Kc. The indices that were found to be the most suitable for Kc prediction were based on the red and red-edge bands (MTCI, REP, and S2REP). This progress in estimating cotton water consumption using satellite imagery that are available at no cost is a leap forward towards the development of crop irrigation requirements models. Consequently, this work sets the scene for near-real-time irrigation decision support systems.

Suggested Citation

  • Rozenstein, Offer & Haymann, Nitai & Kaplan, Gregoriy & Tanny, Josef, 2018. "Estimating cotton water consumption using a time series of Sentinel-2 imagery," Agricultural Water Management, Elsevier, vol. 207(C), pages 44-52.
    • Handle: RePEc:eee:agiwat:v:207:y:2018:i:c:p:44-52
    DOI: 10.1016/j.agwat.2018.05.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377418304785
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2018.05.017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Jin, Xiuliang & Yang, Guijun & Xue, Xuzhang & Xu, Xingang & Li, Zhenhai & Feng, Haikuan, 2017. "Validation of two Huanjing-1A/B satellite-based FAO-56 models for estimating winter wheat crop evapotranspiration during mid-season," Agricultural Water Management, Elsevier, vol. 189(C), pages 27-38.
    2. 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.
    3. Battude, Marjorie & Al Bitar, Ahmad & Brut, Aurore & Tallec, Tiphaine & Huc, Mireille & Cros, Jérôme & Weber, Jean-Jacques & Lhuissier, Ludovic & Simonneaux, Vincent & Demarez, Valérie, 2017. "Modeling water needs and total irrigation depths of maize crop in the south west of France using high spatial and temporal resolution satellite imagery," Agricultural Water Management, Elsevier, vol. 189(C), pages 123-136.
    4. Kumar, Vipan & Udeigwe, Theophilus K. & Clawson, Ernest L. & Rohli, Robert V. & Miller, Donnie K., 2015. "Crop water use and stage-specific crop coefficients for irrigated cotton in the mid-south, United States," Agricultural Water Management, Elsevier, vol. 156(C), pages 63-69.
    5. Er-Raki, S. & Rodriguez, J.C. & Garatuza-Payan, J. & Watts, C.J. & Chehbouni, A., 2013. "Determination of crop evapotranspiration of table grapes in a semi-arid region of Northwest Mexico using multi-spectral vegetation index," Agricultural Water Management, Elsevier, vol. 122(C), pages 12-19.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. 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).
    2. Gregoriy Kaplan & Lior Fine & Victor Lukyanov & V. S. Manivasagam & Josef Tanny & Offer Rozenstein, 2021. "Normalizing the Local Incidence Angle in Sentinel-1 Imagery to Improve Leaf Area Index, Vegetation Height, and Crop Coefficient Estimations," Land, MDPI, vol. 10(7), pages 1-23, June.
    3. 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.
    4. Kaplan, Gregoriy & Fine, Lior & Lukyanov, Victor & Malachy, Nitzan & Tanny, Josef & Rozenstein, Offer, 2023. "Using Sentinel-1 and Sentinel-2 imagery for estimating cotton crop coefficient, height, and Leaf Area Index," Agricultural Water Management, Elsevier, vol. 276(C).
    5. Jun Ma & Jianpeng Zhang & Jinliang Wang & Vadim Khromykh & Jie Li & Xuzheng Zhong, 2023. "Global Leaf Area Index Research over the Past 75 Years: A Comprehensive Review and Bibliometric Analysis," Sustainability, MDPI, vol. 15(4), pages 1-30, February.
    6. Eliav Shtull-Trauring & Asher Azenkot & Nirit Bernstein, 2022. "Translational Platform for Increasing Water Use Efficiency in Agriculture: Comparative Analysis of Plantation Crops," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 571-587, January.
    7. Gregoriy Kaplan & Offer Rozenstein, 2021. "Spaceborne Estimation of Leaf Area Index in Cotton, Tomato, and Wheat Using Sentinel-2," Land, MDPI, vol. 10(5), pages 1-13, May.
    8. Rozenstein, Offer & Haymann, Nitai & Kaplan, Gregoriy & Tanny, Josef, 2019. "Validation of the cotton crop coefficient estimation model based on Sentinel-2 imagery and eddy covariance measurements," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    9. Teixeira, Antônio & Leivas, Janice & Struiving, Tiago & Reis, João & Simão, Fúlvio, 2021. "Energy balance and irrigation performance assessments in lemon orchards by applying the SAFER algorithm to Landsat 8 images," Agricultural Water Management, Elsevier, vol. 247(C).
    10. Rozenstein, Offer & Fine, Lior & Malachy, Nitzan & Richard, Antoine & Pradalier, Cedric & Tanny, Josef, 2023. "Data-driven estimation of actual evapotranspiration to support irrigation management: Testing two novel methods based on an unoccupied aerial vehicle and an artificial neural network," Agricultural Water Management, Elsevier, vol. 283(C).
    11. Pereira, L.S. & Paredes, P. & López-Urrea, R. & Hunsaker, D.J. & Mota, M. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for vegetable crops, an update of FAO56 crop water requirements approach," Agricultural Water Management, Elsevier, vol. 243(C).
    12. Munitz, Sarel & Schwartz, Amnon & Netzer, Yishai, 2019. "Water consumption, crop coefficient and leaf area relations of a Vitis vinifera cv. 'Cabernet Sauvignon' vineyard," Agricultural Water Management, Elsevier, vol. 219(C), pages 86-94.
    13. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. Campos, Isidro & Balbontín, Claudio & González-Piqueras, Jose & González-Dugo, Maria P. & Neale, Christopher M.U. & Calera, Alfonso, 2016. "Combining a water balance model with evapotranspiration measurements to estimate total available soil water in irrigated and rainfed vineyards," Agricultural Water Management, Elsevier, vol. 165(C), pages 141-152.
    4. Shao, Guomin & Han, Wenting & Zhang, Huihui & Liu, Shouyang & Wang, Yi & Zhang, Liyuan & Cui, Xin, 2021. "Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices," Agricultural Water Management, Elsevier, vol. 252(C).
    5. Mohamed Kharrou & Michel Le Page & Ahmed Chehbouni & Vincent Simonneaux & Salah Er-Raki & Lionel Jarlan & Lahcen Ouzine & Said Khabba & Ghani Chehbouni, 2013. "Assessment of Equity and Adequacy of Water Delivery in Irrigation Systems Using Remote Sensing-Based Indicators in Semi-Arid Region, Morocco," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4697-4714, October.
    6. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    7. Zhao, Tianxing & Zhu, Yan & Ye, Ming & Yang, Jinzhong & Jia, Biao & Mao, Wei & Wu, Jingwei, 2022. "A new approach for estimating spatial-temporal phreatic evapotranspiration at a regional scale using NDVI and water table depth measurements," Agricultural Water Management, Elsevier, vol. 264(C).
    8. Amazirh, Abdelhakim & Merlin, Olivier & Er-Raki, Salah & Bouras, Elhoussaine & Chehbouni, Abdelghani, 2021. "Implementing a new texture-based soil evaporation reduction coefficient in the FAO dual crop coefficient method," Agricultural Water Management, Elsevier, vol. 250(C).
    9. Diarra, A. & Jarlan, L. & Er-Raki, S. & Le Page, M. & Aouade, G. & Tavernier, A. & Boulet, G. & Ezzahar, J. & Merlin, O. & Khabba, S., 2017. "Performance of the two-source energy budget (TSEB) model for the monitoring of evapotranspiration over irrigated annual crops in North Africa," Agricultural Water Management, Elsevier, vol. 193(C), pages 71-88.
    10. Ouaadi, Nadia & Jarlan, Lionel & Khabba, Saïd & Le Page, Michel & Chakir, Adnane & Er-Raki, Salah & Frison, Pierre-Louis, 2023. "Are the C-band backscattering coefficient and interferometric coherence suitable substitutes of NDVI for the monitoring of the FAO-56 crop coefficient?," Agricultural Water Management, Elsevier, vol. 282(C).
    11. Zhang, Chao & Liu, Jiangui & Shang, Jiali & Dong, Taifeng & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2021. "Improving winter wheat biomass and evapotranspiration simulation by assimilating leaf area index from spectral information into a crop growth model," Agricultural Water Management, Elsevier, vol. 255(C).
    12. Yang, Xiaolin & Jin, Xinnan & Chu, Qingquan & Pacenka, Steven & Steenhuis, Tammo S., 2021. "Impact of climate variation from 1965 to 2016 on cotton water requirements in North China Plain," Agricultural Water Management, Elsevier, vol. 243(C).
    13. Hamze, Mohamad & Cheviron, Bruno & Baghdadi, Nicolas & Lo, Madiop & Courault, Dominique & Zribi, Mehrez, 2023. "Detection of irrigation dates and amounts on maize plots from the integration of Sentinel-2 derived Leaf Area Index values in the Optirrig crop model," Agricultural Water Management, Elsevier, vol. 283(C).
    14. Jin, Xiuliang & Yang, Guijun & Xue, Xuzhang & Xu, Xingang & Li, Zhenhai & Feng, Haikuan, 2017. "Validation of two Huanjing-1A/B satellite-based FAO-56 models for estimating winter wheat crop evapotranspiration during mid-season," Agricultural Water Management, Elsevier, vol. 189(C), pages 27-38.
    15. Komlan Koudahe & Aleksey Y. Sheshukov & Jonathan Aguilar & Koffi Djaman, 2021. "Irrigation-Water Management and Productivity of Cotton: A Review," Sustainability, MDPI, vol. 13(18), pages 1-21, September.
    16. Al Zayed, Islam Sabry & Elagib, Nadir Ahmed & Ribbe, Lars & Heinrich, Jürgen, 2016. "Satellite-based evapotranspiration over Gezira Irrigation Scheme, Sudan: A comparative study," Agricultural Water Management, Elsevier, vol. 177(C), pages 66-76.
    17. Gonçalves, Ivo Zution & Mekonnen, Mesfin M. & Neale, Christopher M.U. & Campos, Isidro & Neale, Michael R., 2020. "Temporal and spatial variations of irrigation water use for commercial corn fields in Central Nebraska," Agricultural Water Management, Elsevier, vol. 228(C).
    18. El-Naggar, A.G. & Hedley, C.B. & Horne, D. & Roudier, P. & Clothier, B.E., 2020. "Soil sensing technology improves application of irrigation water," Agricultural Water Management, Elsevier, vol. 228(C).
    19. Bispo, R.C. & Hernandez, F.B.T. & Gonçalves, I.Z. & Neale, C.M.U. & Teixeira, A.H.C., 2022. "Remote sensing based evapotranspiration modeling for sugarcane in Brazil using a hybrid approach," Agricultural Water Management, Elsevier, vol. 271(C).
    20. Jefferson Brooks & Ana Rivera & Miguel Chen Austin & Nathalia Tejedor-Flores, 2022. "A Machine Learning-Based Approach to Estimate Energy Flows of the Mangrove Forest: The Case of Panama Bay," Sustainability, MDPI, vol. 15(1), pages 1-20, December.

    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:207:y:2018:i:c:p:44-52. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.