Avi Rana

ArcGis Tools + Methods

• Hot Spot Analysis tool was used to identify the densest cluster of young children in the Tacoma/Pierce County metro area and then Near tool was used to locate large (>50 acre) parks nearby to them.

• Aggregate Points’ tool was used to identify points that are clustered together within a specified distance. This cluster polygon was then converted to point feature class. ‘Generate Near Table’ tool in this step was used to determine 1) which parks are within five miles of the KidDensity cluster point, and 2) where, precisely, the closest point of entry to the park is relative to the KidDensity cluster point.

• Map Algebra was used to produce the slope and hillshade layers.

• Roads was rasterized so that they can be considered in the cost path analysis later on. Each road segment includes a classification attribute, which was used to assign values to the raster cells that are created during the rasterization procedure.

• Data was reclassified to overlay the various factors in the cost analysis.

• A Euclidean distance grid is used to identify the distance, from each cell in the grid, to any given location.

• Using Map Algebra, the road raster layer was reclassified so that residential roads (which are, hypothetically, more safe) receive a lower score (and, therefore, a lower cost) than arterials.

• Raster calculator was used to combine slope, street types and distance into a single grid.

• Finally, 'Cost Distance' tool was used to calculate the cost of traveling over each individual cell. 'Cost Path' tool was then used to calculate the least costly paths between the parks and the kid density cluster.