Areal interpolation is the process of transferring data collected over source zones to target zones. One of the applications of areal interpolation is to construct temporally consistent areal units for comparing socioeconomic data over time. Dasymetric modeling is the process of employing ancillary data to spatially refine the distribution of socioeconomic variables. In this paper, three areal ...

Iran is one of the world's arid regions and exposed to dust particles in the air. This is important in spatial and temporal terms as well as the affects human health. In this paper a day when due to the amount of dust particles visibility reduces to 5,000 m is considered the dusty day. In the spatial and temporal analysis of dusty days 38 synoptic stations were studied. In order to conduct data...

Iran is one of the world's arid regions and exposed to dust particles in the air. This is important in spatial and temporal terms as well as the affects human health. In this paper a day when due to the amount of dust particles visibility reduces to 5,000 m is considered the dusty day. In the spatial and temporal analysis of dusty days 38 synoptic stations were studied. In order to conduct data...

Spherekit is a spatial interpolation toolkit developed and distributed over the internet by the National Center for Geographic Information and Analysis (NCGIA). A unique feature of the software is its ability to work directly with the spherical geometry of the earth. Thus, distances, areas, and directions are spherically based, and interpolation can be carried out over large distances without d...

In studies of irrigation and drainage projects for drainage, it is necessary to extend the data from the sampling point to the network. Therefore, based on available data from observational wells, estimating the state of hydraulic conductivity (K) in the surrounding area. The estimation process values for locations where there is no information for them based on viewing areas called wells spati...

Rainfall is one of the most important climatic variables in the hydrology cycle. In flood estimation as well as environmental pollution studies in medium to large watersheds not only mus temporal pattern of rainfall t be known, but also the knowledge of its spatial distribution is required. Estimation of daily rainfall distribution without comparison and selection of &#10suitable methods may le...

Rainfall is one of the most important climatic variables in the hydrology cycle. In flood estimation as well as environmental pollution studies in medium to large watersheds not only mus temporal pattern of rainfall t be known, but also the knowledge of its spatial distribution is required. Estimation of daily rainfall distribution without comparison and selection of suitable methods may lead...

the performance of geostatistical and spatial interpolation techniques for estimation of spatial variability of heavy metals and water quality mapping of groundwater resources in ramiyan district (golestan province- iran) were investigated. 24 spring/well water samples were collected and the concentration of heavy metals (ni, co, pb, cd and cu) was determined using differential pulse polarograp...

Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolat...