Sentence examples for mapping units were from inspiring English sources

Fifteen mapping units were identified and grouped.

Soil mapping units were aggregated to generalize common properties and to minimize differences associated with variable spatial scales.

The moving windows consisting of several mapping units were shifted in space and meanwhile used as target areas for correlation analyses.

The non-genetic map based on spatial distributions of the different regolith mapping units were classified on genetic classes or regimes based on regolith-landform similarities to develop a genetic map.

The effects of aggregating soil data (DAE) by areal majority of soil mapping units was explored for regional simulations with the soil-vegetation model CoupModel for a region in Germany (North Rhine-Westphalia).

Raw material provisioning of the mapping units was calculated on the basis of the proportional shares of the STUs with raw material content in the area of each mapping unit.

Spatial and temporal variations in soil moisture and crop yield within different functional map units were statistically compared with those within different map units on the second-order and the high-intensity soil maps.

Soil physical and chemical properties generally varied with soil type and canonical discriminant analyses showed that soil drainage classes, series, and map units were delineated by a similar set of soil properties (total C, total N, moisture, pH, equivalent CEC (CECe), and available P). Ap texture classes were delineated by a different set of soil properties (available K, Mg, and Ca and CECe).

In a second study, the estimated spatial means of the Mean Highest Water table and Mean Lowest Water table of six map units were estimated by Stratified Simple Random Sampling in both phases in combination with the regression estimator that uses the starting depth of hydromorphic properties in the soil profile as an auxiliary variable.

The USDA surface soil texture classifications for the components in the studied soil map units were extracted from STATSGO; percentages of clay, silt and sand for each soil type encountered were approximated with the soil textural triangle.

Confidence limits of 95%, calculated using binomial distribution statistics applied to the map units, were used to determine the genetic map range.