Automatic extraction of plots from geo-registered UAS imagery of crop fields with complex planting schemes
Abstract
Complex planting schemes are common in experimental crop fields and can make it difficult to extract plots of interest from high-resolution imagery of the fields gathered by Unmanned Aircraft Systems (UAS). This prevents UAS imagery from being applied in High-Throughput Precision Phenotyping and other areas of agricultural research. If the imagery is accurately geo-registered, then it may be possible to extract plots from the imagery based on their map coordinates. To test this approach, a UAS was used to acquire visual imagery of 5 ha of soybean fields containing 6.0 m2 plots in a complex planting scheme. Sixteen artificial targets were setup in the fields before flights and different spatial configurations of 0 to 6 targets were used as Ground Control Points (GCPs) for geo-registration, resulting in a total of 175 geo-registered image mosaics with a broad range of geo-registration accuracies. Geo-registration accuracy was quantified based on the horizontal Root Mean Squared Error (RMSE) of targets used as checkpoints. Twenty test plots were extracted from the geo-registered imagery. Plot extraction accuracy was quantified based on the percentage of the desired plot area that was extracted. It was found that using 4 GCPs along the perimeter of the field minimized the horizontal RMSE and enabled a plot extraction accuracy of at least 70%, with a mean plot extraction accuracy of 92%. Future work will focus on further enhancing the plot extraction accuracy through additional image processing techniques so that it becomes sufficiently accurate for all practical purposes in agricultural research and potentially other areas of research.
Degree
M.S.E.
Advisors
Cherkauer, Purdue University.
Subject Area
Agronomy|Plant sciences|Remote sensing
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