Spatial Analyst Toolbox Lecture 17

Spatial Analyst Tool Sets  Conditional  Density  Distance  Generalization  Ground Water  Interpolation  Conditional  Density  Distance  Generalization  Ground Water  Interpolation

 Local  Math  Reclass  Surface  Zonal  Local  Math  Reclass  Surface  Zonal

Spatial Analyst Tools work with Raster Data  Spatial Analyst Tools calculate an output value for your specific location (cell).  You need to know three things to calculate an output value:  The value of your specified location (cell)  The manipulation of the operator or function  Which other cell locations and their values to include in your calculations.  Spatial Analyst Tools calculate an output value for your specific location (cell).  You need to know three things to calculate an output value:  The value of your specified location (cell)  The manipulation of the operator or function  Which other cell locations and their values to include in your calculations.

Types of Functions  Local  Local functions rely on the value in a single cell of a raster database in order to produce an output raster value.  E.g. Sin  Focal  Focal functions rely on the value in a single cell and the cells surrounding it, defined as a neighborhood, in order to produce an output raster value.  E.g. Mean  Local  Local functions rely on the value in a single cell of a raster database in order to produce an output raster value.  E.g. Sin  Focal  Focal functions rely on the value in a single cell and the cells surrounding it, defined as a neighborhood, in order to produce an output raster value.  E.g. Mean

 Zonal  Zonal functions rely on the value in a single cell and cells in a zone that is defined in the calculation to produce an output raster value.  The zone is not necessarily contiguous with the first cell, and each zone may be unique.  E.g. Mean  Zonal  Zonal functions rely on the value in a single cell and cells in a zone that is defined in the calculation to produce an output raster value.  The zone is not necessarily contiguous with the first cell, and each zone may be unique.  E.g. Mean

 Global  Global functions calculate an output data set where a calculation is done at each cell location, taking input for the calculation from various input raster datasets.  There are two groups of global functions:  Euclidean distance global functions  Weighted distance global functions  Application  Application functions are functions that are designed to produce an output for a specific purpose.  E.g. Stream networks or watershed deliniation  Global  Global functions calculate an output data set where a calculation is done at each cell location, taking input for the calculation from various input raster datasets.  There are two groups of global functions:  Euclidean distance global functions  Weighted distance global functions  Application  Application functions are functions that are designed to produce an output for a specific purpose.  E.g. Stream networks or watershed deliniation

Interpolation Toolset  Estimates values that you don’t have by using values that you do have.  E.g. County temperatures are measured at a few specific locations, but you can predict the temperature at any point in the county.  Kriging  IDW (Inverse Distance Weighting)  Spline Interpolation  Estimates values that you don’t have by using values that you do have.  E.g. County temperatures are measured at a few specific locations, but you can predict the temperature at any point in the county.  Kriging  IDW (Inverse Distance Weighting)  Spline Interpolation

Kriging, IDW and Spline Interpolation  Each of these tools takes a set of points and produces a raster that estimates a value for each cell in the raster.  Each of these tools uses a different algorithm, and will return different results.  Try different methods and see which makes sense for the data that you have.  Each of these tools takes a set of points and produces a raster that estimates a value for each cell in the raster.  Each of these tools uses a different algorithm, and will return different results.  Try different methods and see which makes sense for the data that you have.

 Each cell has three important values for interpolation.  X and Y value location  Z value data  E.g. precipitation  The estimation is based on the value at the known points.  It’s best to have evenly distributed sample points.  The more points and more distributed the points, the more accurate the estimation.  Each cell has three important values for interpolation.  X and Y value location  Z value data  E.g. precipitation  The estimation is based on the value at the known points.  It’s best to have evenly distributed sample points.  The more points and more distributed the points, the more accurate the estimation.

Activating Spatial Analyst Extension License  If the Spatial Analyst Extension is not activated:  Tools  Extensions  Check Extensions to activate the License  If the Spatial Analyst Extension is not activated:  Tools  Extensions  Check Extensions to activate the License

Important Issues  To do spatial analysis:  Can’t use Join or Relate to link tables.  The Data must be added to the attribute table in the shapefile.  To do spatial analysis:  Can’t use Join or Relate to link tables.  The Data must be added to the attribute table in the shapefile.