Polynomial geometric interpolation by parametric curves became one of the standard techniques for interpolation of geometric data. An obvious generalization leads to rational geometric interpolation schemes, which are a much less investigated research topic. The aim of this paper is to present a general framework for Hermite geometric interpolation by rational Bézier spatial curves. In particul...

A key problem in environmental monitoring is the spatial interpolation. The main current approach in spatial interpolation is geostatistical. Geostatistics is neither the only nor the best spatial interpolation method. Actually there is no “best” method, universally valid. Choosing a particular method implies to make assumptions. The understanding of initial assumption, of the methods used, and...

For a property measured at several locations, interpolation algorithms provide a unique and smooth function yielding a locally realistic estimation at any point within the sampled region. Previous studies searching for optimal interpolation strategies by measuring cross-validation error have not found consistent rankings; this fact was traditionally explained by differences in the distribution,...

Visualization of scattered data over a volumetric spatial domain is often done by reconstructing a trivariate function on some grid using scattered data interpolation methods and visualizing the function using standard visualization techniques. Scattered data reconstruction algorithms are often computationally expensive and difficult to implement. In order to visualize streaming scattered data,...

Rainfall data is useful in many fields such as urban management, agriculture, and so on. Spatial interpolation is widely used to interpolation continue rainfall data from discrete rainfall gauges. The uncertainty in spatial interpolation is change in different region. Paper focus on urban small area of Beijing city, Xicheng District and analyses uncertainty of spatial interpolation from four as...

abstract precipitation as the most important factor plays the main role in many application researches which are based on climatic parameters. many researches in the field of hydrology, hydrometeorology and agriculture employs rain-gauges (such as synoptic and climatologic stations) data. precipitation characteristics, such as rainfall intensity and duration, usually exhibit significant spatial...

Spatial interpolation is an important feature of a Geographic Information System, which is the procedure used to estimate values at unknown locations within the area covered by existing observations. In this paper, we propose a conservative spatial interpolation technique that incorporates the advantages of local interpolation, Euclidean interpolation, and conservative fuzzy reasoning. The main...

Wireless communication networks offer subscribers the possibilities of free mobility and access to information anywhere at any time. Therefore, electromagnetic coverage calculations are important for wireless mobile communication systems, especially in Wireless Local Area Networks (WLANs). Before any propagation computation is performed, modeling of indoor radio wave propagation needs accurate ...

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...

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...