You are here: Home » Biogeography » Sampling Tool
Sampling Tool
ArcGIS 9.2 Sampling Tool Download
Tool Objective
Tool to derive sampling locations for fieldwork using multiple approaches and analyzing the results
Synopsis
The Biogeography Branch’s Sampling Tool 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 area-based sampling, that is, when the population and component sampling units are defined by known dimensions (e.g. area of habitat). Sample selection can be achieved using either a dataset defining all sample units or a defined sample area. The latter provides a means to perform probabilistic sampling when the definition of sampling units is impractical.
The Biogeography Branch’s Sampling 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.
Functionality
The choice of which design to use depends on sampling objectives, cost, expertise, and available data. Sampling design analysis is used to determine the appropriate number of samples required for specific sampling objectives. Four distinct definitions of a sampling objective can be used, including the coefficient of variation and a confidence interval. All definitions are related to an estimated or user-defined sample variance and a user-defined desired margin of error. Sample size requirements for a range of sampling objectives, such as different margins of error or confidence interval lengths, are provided. The results provide a quick and simple means to balance the advantages of increasing the number of samples with relaxing sampling objectives. Since sample requirements can be used as a sample design performance measure, results from multiple sampling designs can be used to compare design effectiveness.
Simple random sampling and stratified sampling designs are available, as well as a multi-stage sampling design capability. Both continuous and presence-absence data can be used. Data requirements for sample selection can be as simple as a polygon defining the area to be surveyed or as complex as a sample frame polygon dataset with strata definitions and sample variance estimates.
Contacts
Eric Finnen: Eric.finnen@noaa.gov
Charles Menza: Charles.menza@noaa.gov
NOAA/NOS/ Center for Coastal Monitoring and Assessment
1305 East West Highway, 9th floor
Silver Spring, MD 20910
Phone: (301)713-3028 Fax: (301)713-4384
For more information on NOAA’s Biogeography Branch see:
ccma.nos.noaa.gov/about/biogeography/