April 25, 2011
This portion of the model is a “quick” version of an exact area allocation model. Due to the time
constraints of this project, we decided that it was more important to get a very good approximation of
where the people and housing units were located, instead of looking for an exact model. The 25m grid
cells allows us to capture most of the land use polygons with at least one 25m grid cell centroid,
allowing for an approximate area allocation based solution. This version of the model is still missing
those blocks that contained people and housing units, but did not have any residential or institutional
land use fall inside them. This will be a part of the next model update.
Prior to running the final portion of the allocation a few things must be done
1) Create a file geodatabase in ArcCatalog to make a place for the fishnet to run
2) The outputs from the previous model and access need to use the “add attribute index tool” and
then the “add join” tool in order to greatly reduce the processing time required for the joins.
Steps and Logic taken by the Area allocation (based on Land Use typology) model
1. The fishnet is created at a 25 square meter level, with the extent of the vector grid template.
This fishnet (with labels) gives us 2 shapefiles, a grid and one of the grid centroids. This “label”
shape file is the centroids and will be used to intersect the land use file in a later step. It is so
fine grained because we had previously had difficulty where even with 50m grid cells, we were
missing some areas of habitable land.
2. A spatial index was given to the centroid layer in order to optimize calculations and
visualization.
3. The fishnet is spatially joined to the vector grid in order to associate each 25m centroid with the
250m grid cell that contains it. This is necessary for when we are aggregating up to the 250m
grid cell level later in this model.
4. Spatial join the centroids (join feature) to the land use (target feature) in order to get the count
of centroids that fall within the land use polygons. This will be used in calculating the number of
people/units allocated to each of the 25m grid cells. This process still missed a decent number
of small landuse polygons in Cambridge
5. Spatial join of the count of centroids (including itself) in the land use block it is located within.
6. Add the housing allocation field to the centroids
7. Add the Population allocation field to the centroids
8. Calculating the Population allocation field. This is allocating population to the 25m grid cells,
NOT the 250m grid cells. This is done by dividing the weighted population count for the land use
by the number of 25m centroids that fell within that polygon. Because we have no other
information aside from land use and block level census data, we must assume that the
population is distributed evenly over the polygon of that land use type.
9. Calculating the Housing allocation field. This is allocating population to the 25m grid cells, NOT
the 250m grid cells. This is done by dividing the weighted housing unit count for the land use by
the number of 25m centroids that fell within that polygon. Because we have no other
information aside from land use and block level census data, we must assume that the housing
units are distributed evenly over the polygon of that land use type.
10. Spatial join that uses summation for the aggregation tool in order to sum all the 25m centroids
within a 250m grid cell up to the original 250m grid cell level.