This study compares the mapping accuracy of a non-RTK ultra-lightweight drone (DJI Mini2) with two survey-grade RTK-enabled drones (DJI Mavic3E and Phantom4) in three different sites. Flight parameters and weather conditions were the same on each site. The outputs were orthomosaics and digital surface models, whose accuracies were inspected by descriptive statistics and variance analysis tools. The data of the ultralight drone on the first site could not be processed due to strong wind, but its results for the second site (11 hectares) were comparable to those of survey-grade drones, i.e., the range and average of checkpoint errors for Mini2 were 0.17 m and 0.04 m, respectively, while those were 0.10 m and 0.02 m for Phantom4 and Mavic3E. In the third site (34 hectares), survey-grade drones produced accurate results with a checkpoint error range of 0.26 m, while that was 0.87 m for the ultralight drone, implying lower accuracy results. The results obtained suggest that ultralight drones under certain circumstances can produce reliable mapping products depending on weather conditions, the number and distribution of ground control points, and area size. Their biggest drawback is their vulnerability to wind, and in calm weather conditions, due to non-RTK error accumulation, their mapping accuracy degenerates as the area size increases.
Mostafa Arastounia (Tue,) studied this question.
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