Due to the increasing availability of georeferenced microdata in several fields of research, surveys can benefit greatly from the use of the most recent spatial sampling methods. These methods allow to select spatially balanced samples, which lead to particularly efficient estimates, by incorporating the distances among the exact locations of statistical units into the design. Unfortunately, si...

Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation...

Spatial join is one of the fundamental operations in a Spatial Data Base Management System. Recently, the family of R-tree-based data structures has been adopted to support the execution of spatial joins. This paper introduces an analytical model that efficiently estimates the cost (in terms of disk accesses) of a spatial join query between two spatial datasets. The proposed model is based on a...

Proximity, or spatial closeness, can generate social closeness—the closer people are together, the more they interact, affiliate, and befriend one another. Mediated communication allows people to bridge spatial distance and can increase social closeness between conversational partners, even when they are separated by distance. However, mediated communication may not always make people feel clos...

Estimates of small-scale turbulence from numerical model output are produced from local estimates of the spatial structure functions of model variables such as velocity and temperature. The key assumptions used are the existence of a universal statistical description of small-scale turbulence and a locally universal spatial filter for the model variables. The shape of the model spatial filter i...

metric (mapping evapotranspiration at high resolution with internalized calibration) is known as an appropriate surface energy balance model for the estimation of the spatial distribution of evapotranspiration (et) in semi-arid regions. based on lysimeter measurements, metric has shown et estimates of 10% on a sub-field scale on a daily basis. there is a need to identify how the model is sensit...

Remote sensing has become a common and effective method for estimating the areal coverage of land cover classes. One class of particular interest is agriculture as area estimates of cultivated lands are important for purposes such as estimating yields or irrigation needs. The synoptic coverage of satellite imagery and the relative ease of automated analysis have led to widespread mapping of agr...

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting...

Defined as any substance in the air that may harm humans, animals, vegetation, and materials, air pollution poses a great danger to human health. It has turned into a worldwide problem as well as a huge environmental risk. Recent years have witnessed the increase of air pollution in many cities around the world. Similarly, it has become a big problem in Iran. Although ground-level monitoring ca...

Defined as any substance in the air that may harm humans, animals, vegetation, and materials, air pollution poses a great danger to human health. It has turned into a worldwide problem as well as a huge environmental risk. Recent years have witnessed the increase of air pollution in many cities around the world. Similarly, it has become a big problem in Iran. Although ground-level monitoring ca...