Silage maize yield estimation by using planetscope, sentinel-2A and landsat 8 OLI satellite images

•Maize yield estimation by using PlanetScope, Sentinel 2 and Landsat satellite images.•Silage maize yield was estimated most accurately with Simple Ratio vegetation index calculated with satellite images acquired between DAS 73 and DAS 76.•The spatial resolution of satellite images does not affect o...

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Bibliographic Details
Published in:Smart agricultural technology 2023-08, Vol.4, p.100165, Article 100165
Main Authors: Tunca, Emre, Köksal, Eyüp Selim, Taner, Sakine Çetin
Format: Article
Language:English
Subjects:
Landsat
Maize
PlanetScope
Remote sensing
Sentinel 2
Yield estimation
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Summary:•Maize yield estimation by using PlanetScope, Sentinel 2 and Landsat satellite images.•Silage maize yield was estimated most accurately with Simple Ratio vegetation index calculated with satellite images acquired between DAS 73 and DAS 76.•The spatial resolution of satellite images does not affect on yield estimation. The early prediction of crop yield is a vital component of agricultural planning and policy decision-making. In order to achieve this, many countries utilize conventional techniques such as crop growth models that simulate agricultural applications. Alternatively, some approaches involve the spatio-temporal monitoring of vegetation conditions. In this study, we aimed to evaluate the potential for silage maize yield estimation using vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Soil-Adjustment Vegetation Index (SAVI), and Simple Ratio (SR), through the use of PlanetScope, Sentinel-2A, and Landsat 8 OLI satellite images. Linear regression was employed to examine the relationship between silage maize yield and calculated spectral vegetation indices (SVI) at various dates. The results revealed significant correlations between remotely sensed SVI and silage maize yield values for four large-scale plots. Specifically, it was found that silage maize yield could be estimated most accurately using SR between Days After Sowing (DAS) 73 and DAS 76 at a p-value of
ISSN:2772-3755
2772-3755
DOI:10.1016/j.atech.2022.100165