Mining projects especially relating to limestone deposits require an accurate knowledge of tonnage and grade, for both short long-term planning. This is often difficult establish as detailed exploration operations, which are required get the description deposit, costly time consuming. Geologists mining engineers usually make use geometric geostatistical methods, estimating grade ore reserves. H...

Most studies on urban land values focus on the determinants, using hedonic land price models with the consideration of the physical and socio-economic factors. This article employs geostatistical methods to analyze urban land values. Through a case study of Milwaukee, we set up semivariogram models and 3-D TIN surface models for urban land values, and explore anisotropy characteristics and the ...

Propagation of radio occultation (RO) signals through the lower troposphere results in high phase acceleration and low signal to noise ratio signal. The excess Doppler estimation accuracy in lower troposphere is very important in receiving RO signals which can be estimated by sliding window spectral analysis. To do this, various frequency estimation methods such as MUSIC and ESPRIT can be adopt...

Classical geostatistical methods face serious computational challenges if they are confronted with large spatial datasets. The stochastic local interaction (SLI) approach does not require matrix inversion for parameter estimation, prediction, and uncertainty estimation. This leads to better scaling of complexity storage requirements data size than standard (i.e., without size-reducing modificat...

One of the effective steps in use of water resources is accurate estimation of plants water requirement. Lack of accurate estimation of this amount leads to water loss and failure to achieve optimum yield, reduced potential of production, soil resources degradation by too much irrigation or lack of enough leaching and salinization of soils by irrigation less than necessary level, which would ul...

In this paper we develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specically, our approach first allows for statistical noise, similar to Stochastic frontier analysis, and second, it allows modeling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to...

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been wid...