You are currently viewing an archived version of Topic Directional Operations.
If updates or revisions have been published you can find them at Directional Operations.
Learning Objectives:
Describe several different measures of distance between two points (e.g., Euclidean, Manhattan, network distance, spherical)
Explain how different measures of distance can be used to calculate the spatial weights matrix
Explain why estimating the fractal dimension of a sinuous line has important implications for the measurement of its length
Explain how fractal dimension can be used in practical applications of GIS
Explain the differences in the calculated distance between the same two places when data used are in different projections
Outline the implications of differences in distance calculations on real world applications of GIS, such as routing and determining boundary lengths and service areas
Estimate the fractal dimension of a sinuous line
Describe operations that can be performed on qualitative representations of direction
Explain any differences in the measured direction between two places when the data are presented in a GIS in different projections
Compute the mean of directional data
Compare and contrast how direction is determined and stated in raster and vector data
Define “direction” and its measurement in different angular measures
You are currently viewing an archived version of Topic Directional Operations. If updates or revisions have been published you can find them at Directional Operations.
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