Paper
19 June 2015 Corn yield estimation in Serbia using MODIS 13Q1 product
Author Affiliations +
Proceedings Volume 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015); 95351D (2015) https://doi.org/10.1117/12.2192331
Event: Third International Conference on Remote Sensing and Geoinformation of the Environment, 2015, Paphos, Cyprus
Abstract
The aim of our study was to verify the accuracy and the usability of Moderate resolution imaging spectroradiometer (MODIS) 13Q1 product for corn yield estimation on a local level for 2014 year. Product 13Q1 consists of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) 16-day composites with 250 m spatial resolution. The estimation is based on ground truth data (sowing structures for 8 years) which was provided by local agricultural organization in Vojvodina, Serbia. The indices were used in linear regression, where the average yield for corn was the dependent variable, NDVI and EVI were independent variables. Average corn yield was estimated approximately 15 days before the beginning of the harvest and compared with official results. Depending on the used linear method, relative errors ranged from 0.6 % to 7.4 %. Overall, coefficients of determination (R2) ranged from 0.66 to 0.75 and were significant at 0.05. The smallest difference between official results for corn yield and our estimate when using NDVI was 0.59 t/ha, when using EVI the smallest difference was 0.07 t/ha. Paper showed that NDVI and EVI from MODIS follow linear relationship with average corn yield and can be used in estimation of crop yields in Serbia and also that EVI produces better prediction results than NDVI. The crop yield estimation can be used for similar cultivated plants in Serbia and for longer period dataset.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Miro Govedarica, Dušan Jovanović, and Filip Sabo "Corn yield estimation in Serbia using MODIS 13Q1 product", Proc. SPIE 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), 95351D (19 June 2015); https://doi.org/10.1117/12.2192331
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Cited by 4 scholarly publications.
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KEYWORDS
MODIS

Spatial resolution

Earth observing sensors

Landsat

Agriculture

Vegetation

Error analysis

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