Drought monitoring is a fundamental component of drought risk management. It is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. In many instances, drought indices are used for monitoring purposes. Geostatistical methods allow the interpolation of spatially referenced data and the prediction of v...

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 ...

rainfall erosivity is the ability of rainfall to detach the soil particles. this study was conducted to evaluate spatial variability of rainfall erosivity indices in khouzestan province. the point data of indices (ei30, aim, ke>1 and onchev indices) in 74 stations were used to generate spatial erosivity maps through deterministic and geostatistical interpolation methods (radial basis functions,...

The concept of spatial interpolation is important in the soil sciences. However, the use of a single global interpolation model is often limited by certain conditions (e.g., terrain complexity), which leads to distorted interpolation results. Here we present a method of adaptive weighting combined environmental variables for soil properties interpolation (AW-SP) to improve accuracy. Using vario...

There has been much excitement and activity in recent years related to the relatively sudden availability of earth-related data and the computational capabilities to visualize and analyze these data. Despite the increased ability to collect and store large volumes of data, few individual data sets exist that provide both the requisite spatial and temporal observational frequency for many urban ...

Seismic data are often inadequately or irregularly sampled along spatial axes. Irregular sampling can produce artifacts in seismic imaging results. We present a new approach to interpolate aliased seismic data based on adaptive predictionerror filtering (PEF) and regularized nonstationary autoregression. Instead of cutting data into overlapping windows (patching), a popular method for handling ...

This extended abstract presents a new image data fusion method that aims to combine images with different spatial and spectral resolutions. It is based on a projection onto the subspace of the set of solutions of an underdetermined least squares problem. The data fusion problem may also involve an interpolation process, when images with different spatial resolutions are used. In our case, this ...

With the help of GPS and measuring instrument of soil moisture, soil moisture was measured and analyzed. As using Geo-statistics to the study of spatial variability of soil moisture and use ArcGIS 9.0, get the spatial distribution map of soil water property with Kriging interpolation. The research result showed that all soil spatial characters are normal distribution and the spatial distributio...

A low-complexity adaptive scaling algorithm is proposed for the implementation of 2-D image scaling applications. a less complexity, less memory requirement, and high performance algorithm is proposed for Very Large Scale Integration implementation of an image scaling processor. The anticipated image scaling algorithm consists of a clamp filter, spatial filter and a bilinear interpolation. The ...