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MI-SDM (MapInfo Spatial Data Modeller)
is an extension to MapInfo Professional which provides advanced spatial
modelling with the goal of predicting the probability of occurrence of point
objects. MI-SDM
has been designed to integrate any number of large and diverse map layers in
both raster and vector format. Weights of Evidence, Fuzzy Logic and Neural
Networks techniques are then used to model the spatial patterns in the
combined data.
MI-SDM uses innovative data processing methods to work with input layers in
polygon, classified grid or a variety of continuous grid formats. MI-SDM is made up of a number of discrete modules for the preparation
and analysis of data and the subsequent visualization of results.
Want to know more ?
- Use an unlimited number of polygon or grid layers as input to the Spatial
Data Modeller
- Use any polygon or polygons as the analysis study area
- Project explorer keeps track of input data layers and output results tables
- Processing log keeps track of what processing has been done, and where the
results were stored
- Calculate weights of evidence for polygon or grid layers
- Calculate weights of evidence for unique conditions grid
- Check any number of input layers for conditional independence
- Generate unique conditions Prospectivity Map for any number of input
layers and classes
- Calculate logistic regression statistics for unique conditions grid
- Add fuzzy membership values to polygon or classified grid layers with manual
input or with fuzzification function
- Create output grid from single or multi-stage fuzzy logic model, using any
of the fuzzy arithmetic operators on any combination of polygon or grid layers
- Analysis using supervized (RBFLN, PNN) and unsupervized (Fuzzy Clustering)
processing methods
- Neural network processing is fully integrated into MI-SDM and available as
stand-alone exe
- Neural network analysis for a unique conditions grid creates a
prospectivity map
- Neural network analysis can also be performed for point layers
- Shade grids by linear, equalized, standard deviation, logarithmic or
natural breaks
- Generate correlation and covariance matrices for grids
- Principal components analysis for grids
- Filter grids and rasters with supplied or customized convolution filters
- Normalize and transform continuous grids
- Grid Calculator to create new grids by combining grids using mathematical
expressions
- Distance grid showing distance to nearest vector feature for each grid
cell
- Interpolate feature density
- Interpolate neighbourhood statistics
- Detect edges in grids and rasters
- Classify a continuous grid by histogram or value breaks
- Classify a raster to continuous and classified grid
- Convert classified grid to polygons
- Convert polygons to classified or continuous grid
- Classify, reclassify and generalize layers
- Extract contacts from polygon layers
- Extract intersection points from line layers
- Identify bends, jogs and splays between and within polylines
- Add line orientation to lines
- Clip polygon and grid layers to the study area
- Resample, reproject and stitch grids
- Import and export ascii and binary grids
- Clip grids to selected polygons
- Output grids can be created as classified grid or polygons
- Extract areas from prospectivity grids as fully attributed polygons
- Compare ranks of results in unique conditions grids
- Shade a unique conditions grid by weights of evidence results
- Shade a classified grid by any attribute
- Assign statistics to polygons from inlying points
- Assign statistics from grids and rasters to overlying vectors
- View univariate statistics for grids and rasters
- View univariate statistics for vector layers
- Normalize attributes for vector layers
- Centrographic statistics for point layers
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