You are currently viewing an archived version of Topic Distance, Length, and Direction.
If updates or revisions have been published you can find them at Distance, Length, and Direction.

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You are currently viewing an archived version of Topic Distance, Length, and Direction. If updates or revisions have been published you can find them at Distance, Length, and Direction.

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