What is the ideal soil sampling grid density for geochemical mapping?

2 Sampling media

The second factor to consider is the sampling media, or the type of soil that you are sampling. Different types of soil have different properties that affect their geochemical composition and variability. For example, organic-rich soils tend to have higher concentrations of elements that are associated with organic matter, such as carbon, nitrogen, and phosphorus. Sandy soils tend to have lower concentrations of elements that are bound to clay minerals, such as potassium, calcium, and magnesium. The sampling media also influences the sample preparation and analytical methods that you will use, which may have different levels of accuracy and precision.

3 Sampling costs

The third factor to consider is the sampling cost, which includes the time, labor, equipment, transportation, and analysis expenses that are involved in collecting and processing the soil samples. The sampling cost is directly proportional to the number of samples that you collect, so the higher the grid density, the higher the cost. However, the sampling cost also depends on the accessibility and terrain of the sampling area, the availability and quality of the sampling equipment, and the choice and location of the analytical laboratory. You should balance the sampling cost with the expected benefits and returns of your geochemical mapping project.

4 Sampling statistics

The fourth factor to consider is the sampling statistics, which are the numerical measures that describe the distribution and variation of the geochemical data. Sampling statistics can help you estimate the minimum number of samples that you need to collect to achieve a certain level of confidence and accuracy in your geochemical map. Some common sampling statistics that you can use are the mean, standard deviation, coefficient of variation, and semivariogram. You can also use geostatistical methods, such as kriging, to interpolate and extrapolate the geochemical data between the sampling points.

5 Sampling optimization

The fifth factor to consider is the sampling optimization, which is the process of adjusting and improving your sampling grid density based on the results and feedback of your geochemical mapping. Sampling optimization can help you refine your sampling objective, identify and correct any errors or biases in your sampling design, and increase the efficiency and effectiveness of your geochemical mapping. Some common sampling optimization techniques that you can use are pilot studies, duplicate or replicate samples, quality control and assurance, and adaptive sampling.

6 Sampling examples

The sixth and final factor to consider is the sampling examples, which are the real-world cases and scenarios that illustrate how different soil sampling grid densities have been applied and evaluated for geochemical mapping. Sampling examples can help you learn from the experiences and best practices of other geochemical mappers, compare and contrast different sampling approaches and outcomes, and inspire and inform your own sampling decisions. Some sources of sampling examples that you can consult are scientific journals, technical reports, industry publications, and online databases.