In the past decade, substantial progress has been made in model-based optimization of
sampling designs for mapping. This paper is an update of the overview of sampling designs …

Mapping and monitoring soil spatial variability is particularly problematic for temporally and
spatially dynamic properties such as soil salinity. The tools necessary to address this classic …

For decades scientists have produced maps of biological, ecological and environmental
variables. These studies commonly evaluate the map accuracy through cross-validation with …

For baselining and to assess changes in soil organic carbon (C) we need efficient soil
sampling designs and methods for measuring C stocks. Conventional analytical methods …

Sampling design plays an important role in soil survey and soil mapping. Conditioned Latin
hypercube sampling (cLHS) has been proven as an efficient sampling strategy and used …

Estimating soil organic carbon (SOC) stocks in agricultural fields is essential for
environmental and agronomic research, management, and policy. Stratified sampling is a …

Several misconceptions about the design‐based approach for sampling and statistical
inference, based on classical sampling theory, seem to be quite persistent. These …

Efficient modelling methods to assess soil organic carbon (SOC) stocks have a pivotal
importance as inputs for global carbon cycle studies and decision-making processes …

Soils are notoriously spatially heterogeneous and many soil properties are temporally
variable. Spatial variability of soil properties has a profound influence on agricultural and …

Accurate digital mapping of soil organic carbon (SOC) over cultivated land is significant for
estimating potential soil carbon sequestration and mitigating future climate changes. Large …