Drones vs. Satellites: A comparative analysis of Low- and High-altitude imagery in cereal crop mapping

 The development of unmanned aerial vehicle (UAV) technology is significantly transforming crop management methods in precision agriculture, enabling high-resolution field mapping as well as the assessment of plants' physiological health and stress levels. The aim of the conducted research was to validate the Drought Monitoring System at the IUNG-PIB Agricultural Experimental Stations in terms of its effectiveness in detecting suboptimal crop conditions caused by agricultural drought. 

 Data acquisition was based on UAV flights performed at an altitude of 100 meters (AGL), utilizing a seven-sensor multispectral camera covering blue, green, red, Red Edge, near-infrared (NIR), long-wave infrared (LWIR), and panchromatic bands. The Normalized Difference Vegetation Index (NDVI) was primarily used for the quantitative and qualitative assessment of vegetation status. 

 The obtained high-resolution spectral imagery enabled a precise, non-destructive assessment of key agricultural crops, taking into account not only plant health status and fertilizer requirements but also the estimation of soil moisture and soil heterogeneity. It was demonstrated that UAV-based imagery allows for a more accurate delineation of drought-affected areas (including crop losses in triticale) compared to traditional in situ measurements. A direct comparative analysis of satellite imagery from the Sentinel-2 system and drone imagery recorded on the same date revealed stark divergences in spectral reflectance resulting from the secondary growth of the oat crop. Furthermore, the collected data was used to map Land Surface Temperature (LST) for the purpose of calculating Potential Evapotranspiration (ETP), as well as to test machine learning algorithms to quantify the percentage cover of weeds (e.g., Apera spica-venti). The application of the NDVI based on spectral data provides a reliable basis for monitoring dynamic changes in crops throughout the growing season.  

Author: Tytus Berbeć (IUNG-PIB)