Pedometric mapping

For example, data assimilation techniques, such as the space-time Kalman filter, can be used to integrate pedogenetic knowledge and field observations.

[4] In the information theory context, pedometric mapping is used to describe the spatial complexity of soils (information content of soil variables over a geographical area), and to represent this complexity using maps, summary measures, mathematical models and simulations.

[citation needed] Pedometrics is the application of mathematical and statistical methods to the study of the distribution and genesis of soils.

Pedometrics addresses soil-related problems when there is uncertainty due to deterministic or stochastic variation, vagueness and lack of knowledge of soil properties and processes.

Simulation models incorporate uncertainty by adopting chaos theory, statistical distribution, or fuzzy logic.

Such methods can be considered subjective, and it is hence difficult or impossible to statistically assess the accuracy of such maps without additional field sampling.

Traditional soil survey mapping also has limitations in a multithematic GIS, related to the fact that is often not consistently applied by different mappers, and is largely manual and difficult to automate.

This model was first introduced by French mathematician Georges Matheron, and has proven the Best Unbiased Linear Predictor for spatial data.

[2] A special group of pedometric mapping techniques focus on downscaling spatial information that can be area-based or continuous.

Prediction of soil classes is also another subfield of pedometric mapping, where specific geostatistical methods are used to interpolate the factor-types of variables.