Ground-level tropospheric ozone is one of the air pollutants of most concern. It is mainly produced by photochemical processes involving nitrogen oxides and volatile organic compounds in the lower parts of the atmosphere. Ozone levels become particularly high in regions close to high ozone precursor emissions and during summer, when stagnant meteorological conditions with high insolation and hi...

Child malnutrition is often the most common factor that causes child mortality rate. In study of malnutrition, there limited evidence on spatial analysis to identify trends and hotspots indicators contextual factors contributing geographical inequalities in malnutrition. This aimes investigate distribution heterogeneity Malnutrition across districts states India examine influence determinants w...

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...

Coronavirus (Covid) is a severe acute respiratory syndrome infectious disease, spreads primarily between human beings during close contact, most often through the coughing, sneezing, and speaking small droplets. A retrospective surveillance research conducted in India 30th January–21st March 2020 to gain insight into Covid’s epidemiology spatial distribution. Voronoi statistics used draw attent...

Analyzing massive spatial datasets using a Gaussian process model poses computational challenges. This is problem prevailing heavily in applications such as environmental modeling, ecology, forestry and health. We present novel approximate inference methodology that uses profile likelihood Krylov subspace methods to estimate the covariance parameters makes predictions with uncertainty quantific...

This paper compares the results of two models, one hedonic and other geostatistical, when obtaining housing price estimates in Rumiñahui canton, Ecuador. In first model, different parameterizations variables that make up model are used to obtain best predictions. For geostatistical case, predictions composed a trend function depends on certain characteristics spatial error term, which is modele...