Add to ORKGThe decision-oriented mapping of pollution using hybrid models based on statistical learning theory and geostatistics is considere
Geostatistical mapping of soil properties in 3D refers to the application of geostatistical methods ...
Gómez-Hernández, JJ.; Scheidt, C. (2013). Special Issue on Environmental Geostatistics. Mathematical...
Problems of model determination, prediction and statistical learning for space-time data arise in ma...
The paper presents decision-oriented mapping of pollution using hybrid models based on statistical l...
The paper presents some contemporary approaches to spatial environmental data analysis. The main top...
Spatial data analysis mapping and visualization is of great importance in various fields: environmen...
The algorithmic approach to data modelling has developed rapidly these last years, in particular met...
Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Tra...
[[abstract]]In many fields of science, predicting variables of interest over a study region based on...
Environmental attributes are usually highly variable both in space and time leading to substantial u...
Geostatistical techniques can be used to predict spatially correlated variables at unsampled locatio...
The INTAMAP FP6 project has developed an interoperable framework for real-time automatic mapping of ...
Conventional geostatistical methodology solves the problem of predicting the realized value of a lin...
The pollution of soils with heavy metals and radio-nuclides is a complex phenomenon. The interdiscip...
The automatic interpolation of environmental monitoring network data such as air quality or radiatio...
Geostatistical mapping of soil properties in 3D refers to the application of geostatistical methods ...
Gómez-Hernández, JJ.; Scheidt, C. (2013). Special Issue on Environmental Geostatistics. Mathematical...
Problems of model determination, prediction and statistical learning for space-time data arise in ma...
The paper presents decision-oriented mapping of pollution using hybrid models based on statistical l...
The paper presents some contemporary approaches to spatial environmental data analysis. The main top...
Spatial data analysis mapping and visualization is of great importance in various fields: environmen...
The algorithmic approach to data modelling has developed rapidly these last years, in particular met...
Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Tra...
[[abstract]]In many fields of science, predicting variables of interest over a study region based on...
Environmental attributes are usually highly variable both in space and time leading to substantial u...
Geostatistical techniques can be used to predict spatially correlated variables at unsampled locatio...
The INTAMAP FP6 project has developed an interoperable framework for real-time automatic mapping of ...
Conventional geostatistical methodology solves the problem of predicting the realized value of a lin...
The pollution of soils with heavy metals and radio-nuclides is a complex phenomenon. The interdiscip...
The automatic interpolation of environmental monitoring network data such as air quality or radiatio...
Geostatistical mapping of soil properties in 3D refers to the application of geostatistical methods ...
Gómez-Hernández, JJ.; Scheidt, C. (2013). Special Issue on Environmental Geostatistics. Mathematical...
Problems of model determination, prediction and statistical learning for space-time data arise in ma...