@conference {JRN55241,
	title = {A web interface for creating random, spatially balanced landscape monitoring designs},
	booktitle = {Society for Range Management},
	year = {2019},
	month = {02/2020},
	address = {Denver, Colorado},
	abstract = {In the monitoring and assessment of landscapes, randomly located sampling plots are often used to minimize sampling bias and enable inference to larger landscape units. In particular, spatially balanced random designs are more robust to spatial autocorrelation and therefore produce data usable for answering multiple management questions. The Generalized Random Tessellation Stratified (GRTS) approach is one technique for creating spatially balanced random designs in natural resources and has been widely adopted by multi-scale terrestrial and aquatic monitoring programs. While the parameters for a GRTS design are relatively simple to specify with stratification polygons and per-stratum sample sizes, generating a design from those inputs has historically required the ability to code using the R package spsurvey. As a result, technical skills have been a bottleneck for this statistical approach in resource monitoring programs. To remove this technological barrier, we have developed a web application, the {\textquotedblleft}Balanced Design Tool{\textquotedblright}, to create GRTS designs through a graphical interface. The tool prompts users to upload polygons describing their study area and stratification then to specify the number of points to draw per stratum before generating a spatially balanced design. Version 1.5, released in October 2019, added significant functionality. The point allocation process now supports three different approaches (manual, proportional by stratum area, and equally by stratum) through a more user-friendly interface. Users can now use an interactive, webmap to evaluate their designs without needing mapping software (e.g. ArcGIS). The final downloaded design now includes all the files (including an R script) to recreate the design and design documentation. With this tool, land managers can now create their own reproducible, spatially balanced designs to develop locally appropriate, statistically valid monitoring programs to suit a wide variety of objectives. Poster Pod 43, $\#$92.},
	author = {Nelson Stauffer and Sarah McCord and Jason W. Karl}
}
