This paper examines statistical approaches for interpolating climatic data over large regions, providing a brief introduction to interpolation techniques for climate variables of use in agricultural research, as well as general recommendations for future research to assess interpolation techniques. Three approaches—1) inverse distance weighted averaging (IDWA), 2) thin plate smoothing splines a...

Article history: Received 2 February 2006 Received in revised form 8 May 2006 Accepted 20 May 2006 The exact area calculation of irregularly distributed data is in the focus of all territorial geochemical balancingmethods or definition of protection zones. Especially in the deep-sea environment the interpolation ofmeasurements into surfaces represents an important gain of information, because o...

The relationship between exposure to environmental chemicals during pregnancy and early childhood development is an important issue that has a spatial risk component. In this context, we have examined mental retardation and developmental delay (MRDD) outcome measures for children in a Medicaid population in South Carolina and sampled measures of soil chemistry (e.g. As, Hg, etc.) on a network o...

There is increasing interest in the spatial aspects of many policy decisions. To be valid decision-malung tools it is important that maps not only convey what is known, but also where the uncertainties lie. This paper reports the results of tests conducted to assess the ability of various methods of error representation to accurately assist interpretation of maps. The work uses the predicted su...

The presented paper describes the geostatistical analysis of PSInSAR data. This analysis was preceded by short description of PSInSAR technique. The geostatistical computations showed in this article were performed with the R open-source software containing the gstat package. The analysis contains variograms computing (directional variograms) and ordinary kriging interpolation. The computationa...

A study was designed to compare the performance of six spatial interpolation methods to estimate soil properties at unvisited points. These methods were global mean, moving average, nearest neighbour, inverse squared distance, Laplacian smoothing splines and ordinary point kriging. These methods were also applied in combination with a choropleth map (soil map) by stratifying the area. The soil ...

Quantification of spatial and temporal patterns of rainfall is an important step toward developing regional water sewage models, the intensity and spatial distribution of rainfall can affect the magnitude and duration of water sewage. However, this input is subject to uncertainty, mainly as a result of the interpolation method and stochastic error due to the random nature of rainfall. In this s...

Kriging is a powerful spatial interpolation technique, especially for irregularly spaced data points, and is widely used throughout the earth and environmental sciences. The estimation at an unsampled location is given as the weighted sum of the circumjacent observed points. The weighting factors depend on a model of spatial correlation. Calculation of the weighting factors is done by minimizin...

A total of 21 gauges across the mountainous leeward portion of the island of Oʻahu, Hawaiʻi, were used to compare rainfall interpolation methods and assess rainfall spatial variability over a 34-month monitoring period from 2005 to 2008. Traditional and geostatistical interpolation methods, including Thiessen polygon, inverse distance weighting (IDW), linear regression, ordinary kriging (OK), a...

A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weightin...