This paper presents an algorithm for generating realizations of the spatial distribution of an environmental variable; these realizations must minimize the local error variance in addition to the traditional constraints of reproduction of histogram and semivariogram. The optimization technique is performed by simulated annealing and requires a prior determination of the conditional probability ...

Knowledge of spatial variation of soil properties is important in precision farming and environmental modelling. Spatial distribution of water content at field capacity (FC) and permanent wilting point (PWP) at different zones of a farm governs the available water for plant growth. These two soil hydraulic parameters play key roles in crop selection for different blocks of a farm, and in schedu...

Lecoustre, R., Fargette, D., Fauquet, C., and de Reffye, P. 1989. Analysis and mapping of the spatial spread of African cassava mosaic virus using geostatistics and the kriging technique. Phytopathology 79: 913-920. Theories of regionalized variables and kriging were used to assess the incidence along the wind-exposed southwest field borders, disease spatial pattern of African cassava mosaic vi...

Many geospatial science subdisciplines analyze variables that vary over both space and time. The space-time autoregressive (STAR) model is one specification formulated to describe such data. This paper summarizes STAR specifications that parallel geostatistical model specifications commonly used to describe space-time variation, with the goal of establishing synergies between these two modeling...

Semivariogram functions are compared to cooccurrence matrices for classification of digital image texture, and accuracy is assessed using test sites. Images acquired over the following six different spectral bands are used: 1) SPOT HRV, near infrared; 2) Landsat thematic mapper (TM), visible red; 3) India Remote Sensing (IRS) LISS-II, visible green; 4) Magellan, Venus, S-band microwave; 5) shut...

The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Co...

BACKGROUND A site near Tuskegee, Alabama was examined for vector-host activities of eastern equine encephalomyelitis virus (EEEV). Land cover maps of the study site were created in ArcInfo 9.2 from QuickBird data encompassing visible and near-infrared (NIR) band information (0.45 to 0.72 microm) acquired July 15, 2008. Georeferenced mosquito and bird sampling sites, and their associated land co...

Groundwater is one the major sources of natural water being exploited excessively for various uses in India.
 Thus, it very essential to monitor spatial and temporal variability groundwater quality. Geo-Statistical Interpolation using GIS has been considered as best most advanced method interpolation prediction studies pollution quality, adopted universally. In this paper, ordinary Kriging...