Spring Row Crops Productivity Prediction Using Normalized Difference Vegetation Index
| Autor: | Anastasiia Maliarchuk, P. V. Lykhovyd, Mykola Maliarchuk, Iryna Biliaieva, Raisa Vozhehova, Anatoliy Tomnytskyi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
lcsh:GE1-350
geography spatial monitoring geography.geographical_feature_category biology maize Sorghum biology.organism_classification lcsh:TD1-1066 Normalized Difference Vegetation Index Agronomy yield prediction Spring (hydrology) Environmental science sorghum soybean lcsh:Environmental technology. Sanitary engineering Productivity lcsh:Environmental sciences Ecology Evolution Behavior and Systematics General Environmental Science |
| Zdroj: | Journal of Ecological Engineering, Vol 21, Iss 6, Pp 176-182 (2020) |
| ISSN: | 2299-8993 |
| DOI: | 10.12911/22998993/123473 |
| Popis: | The results of statistical modelling for the yields prediction of spring row crops, namely, maize, sorghum and soybean, depending on the values of the remotely sensed normalized difference vegetation index (NDVI) at critical stages of the crops growth and development were presented. The spatial NDVI data obtained from the Sentinel-2 satellite were used to create the models. Quadratic regression analysis was applied to develop the yielding models based on true yield data of the crops obtained in the period of 2017 and 2018 at the experimental field of the Institute of Irrigated Agriculture of NAAS, Ukraine. The results of statistical modelling revealed that the method is suitable for precise yield prediction, and the best stages for NDVI screening and use in this purpose are different for the studied crops. The best accuracy of prediction could be obtained at the stage of tasselling (VT) or silking (R1) for maize (the mean absolute percentage error MAPE is 8.75%); at the stage of second trifoliate (V2) for soybean (MAPE is 3.75%), and at the stage of half bloom (S6) for sorghum (MAPE is 17.62%). The yield predictions by NDVI are reliable at a probability level of 95% (p < 0.05). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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