“The Biogeography Branch’s Sampling Design Tool for ArcGIS provides users a means to efficiently sample a population, be it people, animals, objects or processes, in a GIS environment. The tool was created for sampling when the population and component sampling units are defined by known dimensions.
“The Sampling Design Tool was developed in response to a need by scientists developing sampling strategies in marine environments with limited data. The tool was produced as part of an iterative process of sampling design development, whereby existing data informs new design decisions. The objective of this process, and hence a product of this tool, is an optimal sampling design which can be used to achieve accurate, high-precision estimates of population metrics at a minimum of cost. Although NOAA’s Biogeography Branch focuses on marine habitats and some examples reflects this, the tool can be used to sample any type of population defined in space, be it coral reefs or corn fields.
“The Sampling Design Tool has two main functions: 1) to help select a sample from a population, and 2) to perform sample design analysis. When both of these functions are combined in an iterative manner, the tool effectively and simply achieves the goal of sample surveys — to obtain accurate, high-precision estimates of population metrics at a minimum of cost.
Key features of the tool include:
- Spatial sampling – sampling and incorporation of inherently spatial layers (e.g., benthic habitat maps, administrative boundaries), and evaluation of spatial issues (e.g., protected area effectiveness)
- Scalable data requirements – data requirements for sample selection can be as simple as a polygon defining the area to be surveyed to using existing sample data and a stratified sample frame for optimally allocating samples
- This is a screen capture of the main console of the Sampling Design Tool.
- Random selection – eliminates sampling biases and corresponding criticisms encountered when samples are selected non-randomly
- Multiple sampling designs – simple, stratified, and two-stage sampling designs
- Sample unit-based sampling – points or polygons are selected from a sample frame
- Area-based sampling – random points are generated within a polygon
- Analysis – previously collected data can be used to compute sample size requirements or efficiently allocate samples among strata
- Computations – mean, standard error, confidence intervals for sample data and inferences of population parameters with known certainty
- Output – geographic positions in output simplifies migration to global positioning systems, and sample size estimates and sample statistics can be exported to text files for record keeping