Abstract
Agricultural researchers are embracing remote sensing tools to phenotype and monitor agriculture crops. Specifically, large quantities of data are now being collected on small plot research studies using Unoccupied Aerial Systems (UAS, aka drones), ground systems, or other technologies but data processing and analysis lags behind. One major contributor to current data processing bottlenecks has been the lack of publicly available software tools tailored towards remote sensing of small plots and usability for researchers inexperienced in remote sensing. To address these needs we created plot shapefile maker (R/UAS::plotshpcreate): an open source R function which rapidly creates ESRI polygon shapefiles to the desired dimensions of individual agriculture research plots areas of interest and associates plot specific information. Plotshpcreate was developed to utilize inputs containing experimental design, field orientation, and plot dimensions for easily creating a multi-polygon shapefile of an entire small plot experiment. Output shapefiles are based on the user inputs geolocation of the research field ensuring accurate overlay of polygons often without manual user adjustment. The output shapefile is useful in GIS software to extract plot level data tracing back to the unique IDs of the experimental plots. Plotshpcreate is available on GitHub (https://github.com/andersst91/UAStools).
Highlights
Remote sensing platforms geared towards automated high-throughput crop monitoring have become important tools with potential to drive gains in crop improvement and management (Araus et al, 2018)
Several softwares are beginning to provide automated polygon gridding functions tailored to small agricultural research plots there is still a need for an open source resource that incorporates (i) plot orientation, (ii) experimental design, (iii) automated attribute table with unique plot ID, and (iv) plot buffering
Plotshpcreate was developed based on a common style of seed preparation input files, meaning that if a plot consists of multiple planted rows, the input file must contain a row of data for each plot of the design/layout matrix with the same unique ID
Summary
Remote sensing platforms geared towards automated high-throughput crop monitoring have become important tools with potential to drive gains in crop improvement and management (Araus et al, 2018). Several softwares are beginning to provide automated polygon gridding functions tailored to small agricultural research plots there is still a need for an open source resource that incorporates (i) plot orientation, (ii) experimental design, (iii) automated attribute table with unique plot ID, and (iv) plot buffering. R/UAStools::plotshpcreate (File S1) is implemented as a software package function of R (Figure 1A), which constructs a multipolygon shapefile (.shp) of a research trial, with individual polygons defining specific research field plots. Plotshpcreate was developed based on a common style of seed preparation input files, meaning that if a plot consists of multiple planted rows, the input file must contain a row of data for each plot of the design/layout matrix (i.e., every range x row combination) with the same unique ID. There are ways to overcome this by adjusting plot dimensions and input file, but we will not discuss those methods
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