1. Abstract This paper presents a geostatistical approach to model uncertainty about the spatial distribution of soil properties and to propagate it through a crop model, allowing for incorporation of uncertainty in the choice of management scenarios (no lime, single-rate liming and site-specific lime applications to acidic field soil). The methodology involved modeling the uncertainty about wh...

In the context of the use of remote sensed data for monitoring land cover it is very important to develop methodologies to obtain reliable maps. In order to achieve this objective a possible approach is to combine both “spectral” and “spatial” features to characterizing each ground class. In this paper we propose the integration of a spectral classifier for remote sensed data at medium resoluti...

Kriging interpolation is largely used in geostatistics to characterise the spatial structure of data and it is established in general based upon the stationary or intrinsic assumptions; however, the consequence of this second-order approximation is that the local singularities (or extremes) could be smoothed off. This drawback could be magnified as a finerscale phenomenon is being investigated,...

Kriging (Gaussian process, spatial correlation) metamodels approximate the Input/Output (I/O) functions implied by the underlying simulation models; such metamodels serve sensitivity analysis and optimization, especially for computationally expensive simulations. In practice, simulation analysts often know that the I/O function is monotonic. To obtain a Kriging metamodel that preserves this kno...

We have developed a domain agnostic ordinary kriging algorithm accessible via a standardsbased service-oriented architecture for sensor networks. We exploit the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) standards. We need on-demand interpolation maps so runtime performance is a major priority. Our sensor data comes from wind in-situ observation stations in an area approximate...

Location fingerprinting suffers in dynamic environments and needs recalibration from time to time to maintain system performance. This paper proposes an adaptive approach for location fingerprinting. Based on real-time received signal strength indicator (RSSI) samples measured by a group of reference devices, the approach applies a modified Universal Kriging (UK) interpolant to estimate adaptiv...

For the six-wheel CRAB rover, this paper presents the torque control with Kriging estimation to improve the terrainability by minimizing wheel slip. In previous works, we presented a torque control approach, effectively improving terrainability by minimizing the variance of the required friction coefficient based on the static model. Using a Kalman filter to estimate the velocity information, a...

The research aim of this paper is to investigate the effectiveness of a new Kriging model which uses Taylor expansion to predict wireless network connectivity. Wireless network connectivity is measured by the strength of emitted signal power from the tower to the point in question. The prediction results are compared with those from the literature where an Ordinary Kriging model and a neural ne...

This paper focuses upon the efficient surrogate model algorithm for expensive simulation-based design optimization problems. Co-kriging method is used to develop a multi-fidelity surrogate model using two independent datasets. To achieve this objective, wing-body problem is taken as an example of application for highdimensional complex design problem. In addition, a simple sampling analysis is ...

When comparing the average citation impact of research groups, universities and countries, field normalisation reduces the influence of discipline and time. Confidence intervals for these indicators can help with attempts to infer whether differences between sets of publications are due to chance factors. Although both bootstrapping and formulae have been proposed for these, their accuracy is u...