Monitoring crop coefficient values with Sentinel-2 images to minimize irrigation water losses

M. Ferrer-Julià; S. Fernández-Casado; E. García-Meléndez

doi:10.1117/12.2600273

12 September 2021 Monitoring crop coefficient values with Sentinel-2 images to minimize irrigation water losses

M. Ferrer-Julià, S. Fernández-Casado, E. García-Meléndez

Proceedings Volume 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII; 1185615 (2021) https://doi.org/10.1117/12.2600273
Event: SPIE Remote Sensing, 2021, Online Only

Conference Poster

Abstract

Irrigation enterprises who manage the irrigated water distribution need to anticipate farmer’s demands to minimize the evaporation amounts from irrigation pools, as well as storing enough water to accomplish crop’s water needs at any time and farmer’s management approach. Crop coefficient Kc has proved to be essential when estimating evapotranspiration with FAO56 procedure, but it varies locally. The purpose of this study is to estimate the local corn crop coefficient with remote sensing to estimate the water crop needs in 164 plots in an area of the northwest of the Iberian Peninsula and to identify different farmer’s ways to manage the land. For this purpose, 25 images from Sentinel-2 were analyzed to create their NDVI images. Therefore, the temporal Kc values were estimated and a Kc-curve for each corn field was calculated. Results allowed to differentiate the four crop growth stages and their corresponding Kc values for the study area. Besides, the 164 corn fields were clustered into 31 groups according to their different Kc curves as a result of farmer’s management. Therefore, the method has proved to help in the future to anticipate the local irrigation needs of the corn crops and to improve the farmer’s assessment to reduce their water demands without diminishing their crop production.

Citation Download Citation

M. Ferrer-Julià, S. Fernández-Casado, and E. García-Meléndez "Monitoring crop coefficient values with Sentinel-2 images to minimize irrigation water losses", Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, 1185615 (12 September 2021); https://doi.org/10.1117/12.2600273

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