Geostatistical modeling of topography using auxiliary maps

Geostatistical modeling of topography using auxiliary maps

Modeling spatial distribution of Tehran air pollutants using geostatistical methods incorporate uncertainty maps

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

Modeling spatial distribution of Tehran air pollutants using geostatistical methods incorporate uncertainty maps

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

modeling spatial distribution of tehran air pollutants using geostatistical methods incorporate uncertainty maps

the estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. in this paper, we investigate the spatial distribution of three air pollutants in tehran’s atmosphere: carbon monoxide (co), nitrogen dioxide (no2), and atmospheric particulate matters less ...

Global monthly averaged CO2 fluxes recovered using a geostatistical inverse modeling approach: 2. Results including auxiliary environmental data

[1] Geostatistical inverse modeling has been shown to be a viable alternative to synthesis Bayesian methods for estimating global continental-scale CO2 fluxes. This study extends the geostatistical approach to take advantage of spatially and temporally varying auxiliary data sets related to CO2 flux processes, which allow the inversion to capture more grid-scale flux variability and better cons...