You are here:
USING GIS TO GENERATE SPATIALLY-BALANCED RANDOM SURVEY DESIGNS FOR NATURAL RESOURCE APPLICATIONS
Citation:
THEOBALD, D. M., D. L. STEVENS JR., D. WHITE, N. URQUHART, AND A. R. OLSEN. USING GIS TO GENERATE SPATIALLY-BALANCED RANDOM SURVEY DESIGNS FOR NATURAL RESOURCE APPLICATIONS. ENVIRONMENTAL MANAGEMENT. Springer-Verlag, New York, NY, 40:134-146, (2007).
Impact/Purpose:
Here we provide a short review of traditional probability- based survey designs and describe a recent approach termed spatially-balanced sampling.
Description:
Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because it provides the mathematical foundation for statistical inference. Here we provide a short review of traditional probability- based survey designs and describe a recent approach termed spatially-balanced sampling. We develop an implementation in a geographic information system (GIS), called the Reversed Randomized Quadrant-Recursive Raster algorithm. The implementation of this algorithm in GIS provide environmental managers a practical, useful tool to generate simple, efficient, and robust survey designs for natural resource applications. Moreover, factors to modify the sampling intensity, such as strata, gradients, or accessibility, can be readily incorporated and visualized. We provide examples of survey designs for point, line, areal-based features (e.g., lakes, streams, and vegetation) generated using our Spatial Sampling tool.