Embedded Files
Manipulating raster data, ultimately in support of multicriteria evaluation.
Map algebra
Map algebra
Exercises exclusive to the raster data model and map algebra functions. These provide the foundation for preparing data in support of and performing multicriteria evaluation (MCE) analyzes including Boolean, WLC/AHP, and fuzzy logic.
Ex 1 - Conversion to raster - convert vector points, lines, and polygons into raster grid cells
Ex 2 - Image classification - approaches to landcover classification based on multispectral imagery
Ex 3 - Interpolation - generation of raster surfaces by way of predicting values between data samples
Ex 4 - Local functions - operations that work on single cell locations (math, Boolean, overlay, etc.)
Ex 5 - Focal functions - operations that consider cells within a neighborhood (edge detection, smoothing)
Ex 6 - Zonal functions - operations that consider cells within a cartographic zone (mean slope of landcovers)
Ex 7 - Global functions - operations where output cell values are dependent upon all cells (cost distance, corridor)
Topographic Position Index (TPI) - transforming digital elevation models into landforms (e.g. hills, ridges, valleys)
Multicriteria Evaluation (MCE)
Multicriteria Evaluation (MCE)
In GIS, multicriteria evaluation is concerned with the allocation of land to suit a specific objective on the basis of a variety of attributes that the area should possess. There are a number of approaches to MCE, each with their own advantages, workflows, and applications. Habitat suitability is a classic example.
Boolean - Binary, 0/1, True/False, locations must satisfy all specified conditions
WLC/AHP - criterion values placed on a discrete scale (1-5), weighted by importance, and cumulative scores calculated
AHP Explained - the math behind the weight and consistency ratios explained in the context of an erosion hazard model
Fuzzy logic - criteria values placed on continuous scale (0.0 to 1.0) indicating strength of membership and then combined
Report abuse