Geostatistical strategy for soil sampling: the survey and the census

Area of Science:

• Environmental Science
• Geostatistics
• Spatial Analysis

Background:

• Spatially correlated variables in environmental monitoring require efficient sampling strategies.
• Traditional methods may not optimally balance precision, accuracy, and cost.
• Geostatistical analysis offers advanced tools for spatial data interpretation.

Purpose of the Study:

• To develop a soil sampling strategy for spatially correlated variables using geostatistical analysis.
• To outline the logic of geostatistical analysis from semi-variogram modeling to pollution estimate mapping.
• To provide a method for balancing precision, accuracy, and costs in environmental monitoring.

Main Methods:

• Development of a two-stage sampling strategy based on geostatistical principles.
• First stage: Radial grid survey to define semi-variogram, ranges of influence, and correlation structure.
• Second stage: Census sampling with grid parameters determined by the semi-variogram, followed by kriging analysis.

Main Results:

• Generation of isomaps for pollution estimates and their standard deviations.
• Creation of isopleth maps of the pollution field and standard error isomaps.
• Demonstration of algorithms that balance precision, accuracy, and costs.

Conclusions:

• The developed two-stage sampling strategy effectively utilizes geostatistical analysis for environmental monitoring.
• The method provides understandable outputs (isomaps) for decision-makers.
• This approach enhances the efficiency and reliability of pollution assessment.