We evaluate the implications of JPEG2000 lossy compression of remote sensing images for spatial analytical purposes. The main issue is to identify which cases and conditions in geostatistical studies are suitable for using lossy compressed images. For these purposes, an extensive test using Landsat, compact airborne spectrographic imager (CASI), and moderate resolution imaging spectroradiometer...

History matching forms an integral part of the reservoir modeling work-flow process. Despite the existence of many history matching tools, the integration of production data with seismic and geological continuity data remains a challenge. Geostatistical tools exists for integrating large scale seismic and fine scale well/core data. A general framework for integrating production data with divers...

[1] Reactive transport modeling is often used in support of bioremediation and chemical treatment planning and design. There remains a pressing need for practical and efficient models that do not require (or assume attainable) the high level of characterization needed by complex numerical models. We focus on a linear systems or transfer function approach to the problem of reactive tracer transp...

Interpretation of remote sensing images into terrestrial attributes is very dependent of their spatial and spectral resolution. Normally, these types of resolution are contradictory: high spatial resolution sensors have a low spectral resolution whereas multispectral sensors have a low spatial resolution. Digital image-merging procedures are techniques that aim at integrating the multispectral ...

The authors introduce two ways to produce locally calibrated grid-based probabilistic forecasts of temperature. Both start from the Global Bayesian model averaging (Global BMA) statistical postprocessing method, which has constant predictive bias and variance across the domain, and modify it to make it local. The first local method, geostatistical model averaging (GMA), computes the predictive ...

drought monitoring is a fundamental component of drought risk management. it is normally performed usingvarious drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolationof spatially referenced data and the prediction of values fo...

Stochastic seismic inversion is an important part of geostatistical method, and the combination sequence simulation. In process random inversion, firstly, histogram distribution variables counted, variation function calculated, range in different directions determined. Then, for each implementation, traces are synthesized at channel position according to calculated reflection coefficient, error...

nowadays, much attention has been paid on using geostatistical methods for estimation of spatial parameters, either using the variables of these parameters (kriging) or auxiliary variables (cokriging), in water and soil sciences. the quality of ground water for agriculture is very important; however, it is expensive and time consuming to measure parameters such as sar, na, ca, th, tds and ec. t...