GS+ Quickly perform geostatistical analysis
Geostatistics provides a way to better understand the autocorrelation inherent in
spatial data – and to define and use this variation to make better estimates
of values for places not sampled and thereby create optimal, unbiased maps.
GS+ provides easy access to these computationally intense analyses. Whether you
are analyzing oil deposits, plankton distributions, sun spot patterns, infectious
disease outbreaks, or soil resources, GS+ allows you ready access to the power of
Create variograms on the fly
GS+ gives you complete control over variogram parameters such as
the active lag distance and the size of individual lag classes. Default values provide
reasonable starting places from which you can optimize an analysis to suit a particular
Model your variograms automatically – GS+ can automatically create a model
for kriging that honors your data to the maximum extent possible using iterative
techniques to optimize good model fits. A model window lets you override the values
that GS+ chooses and slider controls allow you to immediately see the results of
changes. GS+ provides models sufficient for almost all kriging applications.
Variograms are sometimes erratic due to data anomalies – outliers that become
apparent when they are the only values not autocorrelated with other values at a
particular scale. GS+ provides h-Scattergram and Variance Cloud analyses to allow
you to visualize and identify outliers fast, and a new masking command allows you
to surgically remove (either temporarily or permanently) the offending data record.
Directional (anisotropic) variograms are produced at the same time as isotropic
variograms so you can readily evaluate whether autocorrelation is dependent on compass
direction. This occurs, for example, when there is a slope effect or some other
environmental feature that causes autocorrelation in one direction to be different
from autocorrelation in another.
It’s easy to recognize anisotropy in GS+ by creating variogram maps –
graphs of semivariance in different compass directions. If present, you can then
easily define an angle of maximum variation to use for the anisotropic variogram
Calculate 11 different types of autocorrelation measures
Variograms are only one type of autocorrelation provided by GS+. Also included are correlograms, madograms, rodograms, covariograms, drift, Moran’s I, fractal
dimension, and standardized, general relative, and pairwise relative variograms.
All are evaluated in both isotropic and anisotropic directions.
Import data from a wide variety of sources
The GS+ worksheet can be directly edited and you can import data into the worksheet from a variety of sources – text files formatted in different
ways, Excel spreadsheets, Access and other database files, or cut and paste from
any other Windows program. There are also several ways to indicate missing values,
and any value in the spreadsheet can be removed from a particular analysis by setting
a temporary missing value attribute. The worksheet accepts over a billion records.
Summarize your data prior to geostatistical analysis
GS+ also provides basic parametric statistics to enable you to characterize your data prior to geostatistical analysis. When a data set is prepared
for analysis, GS+ reports stats such as the mean, range, standard deviation, and
kurtosis and skewness, and also creates frequency and probability distributions
so you can evaluate departures from normality. Quantile scattergrams provide a visual
map of your sample locations and identify the locations of data with particular
Interpolation methods to meet every need
Three different types of interpolation are provided by GS+. Ordinary kriging (both
block and punctual) provide optimal estimates for a property across the spatial
domain. Conditional simulation also provides optimal estimates but honors original
data at their locations so can be used to map sharp boundaries in a domain. Inverse distance
weighting is probably the best non-geostatistical interpolation technique, based
on simple nearest neighbor calculations.
GS+ also provides cokriging, which can be useful when your primary data are supported
by secondary data collected at many additional locations. Cokriging is available for
both block and punctual kriging and co-located cokriging is available for conditional
Polygon masks allow you to include or exclude complex shapes in the domain being
mapped. Interpolate across an island or avoid interpolating across a parking lot
– you can also nest polygons and overlap them.
Create interpolation output files that are usable by many other programs
GS+ creates interpolation output files (from kriging, cokriging, simulation, or
inverse distance techniques) that can be read into many other types of mapping programs.
GS+ will use these files to create it’s own maps or you can read the data
into any GIS or mapping program that supports ArcInfo® or Surfer® input
Cross-validation allows you to test your interpolation system against sampled data
In cross-validation analysis each measured point in a spatial domain is individually removed from the domain and its value estimated via kriging or inverse
distance weighting as though it were never there. In this way a graph of estimated
vs. actual values for each sample location in the domain can be constructed and
used to test the interpolation system.
Customize all details of your GS+ graphs and maps and publish to anywhere
A rich set of graph editing options allow you to change axes, fonts, perspective, titles, symbols and many other graph attributes. Maps and graphs can
be printed or sent to the Windows clipboard or to a file that can be read by web
browsers, word processors, or any other Windows program that accepts wmf, jpeg,
png, or bmp formats.