Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algori...

We consider the problem of sequential estimation unknowns state-space and deep models that include functions latent processes models. The proposed approach relies on Gaussian are implemented via random feature-based processes. In these models, we have two sets unknowns, highly nonlinear (the values processes) conditionally linear constant parameters processes). present a method based particle f...

This paper proposes the use of Gaussian Mixture Models to estimate conditional probability density functions in an environmental risk mapping context. A conditional Gaussian Mixture Model has been compared to the geostatistical method of Sequential Gaussian Simulations and shows good performances in reconstructing local PDF. The data sets used for this comparison are parts of the digital elevat...

ÐGenerated realizations of random ®elds are used to quantify the natural variability of geological properties. When the realizations are used as inputs for simulations with a deterministic model, it may be desirable to minimize di€erences between statistics of sequential realizations and make the statistics close to ones speci®ed at generating the realizations. We describe the use of a genetic ...