Published in Scientific Papers. Series "Management, Economic Engineering in Agriculture and rural development", Vol. 21 ISSUE 3
Written by Mayie M. AMER, Atef M. ELSBAAY

For the synoptic assessment of corn plants content of Ca, and K accurate monitoring of land surface dynamics using remote sensing is needed. We looked at a full resolution dataset from the Medium Resolution satellite Imaging (Sentinel-2) as an open source as an alternative to the costly high resolution the more widely used high-resolution satellite Imaging (Worldview2) data for vegetation monitoring. We compared Sentinel-2 image and Worldview 2 data acquired in 2018 with in situ measured hyperspectral data and metal concentrations in plant samples collected from fields in the study area for this purpose. The current research was conducted on the experimental site during the 2018 corn cropping season (Zea Mayz). Results indicated that: The Difference Vegetation Index (DVI), the Enhanced Vegetation Index (EVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Leaf Area Index (LAI) were the more sensitive indicators to Ca and K above ground corn plants content. These VIs had R² values more than 0.5 with the in-situ measurements for the both images. DVI, EVI, and GNDVI performed well in estimating plant dry matter Ca and K content with R² > 0.5, with a high significant level P-value < 0.001and LAI had a statistically significant impact with a P-value < 0.5 for WV2 image. The Sentinel-2 VIs performed well in estimating plant dry matter Ca and K content with R² values > 0.5, with a high significant level P-value 0.001. LAI had a statistically significant impact with a P-value < 0.5 with Ca concentration and P-value < 0.01 with K concentration. This study suggests that the moderate resolution satellite images can be used for corn plants Ca and K content.

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