Input data
Attribute data
SimUrb application is designed to find similarities between municipalities based on multivariate attribute data. It requires map layer as JSON file and CSV file with attribute data about municipalities with specific structure.
In the CSV file, the most important are the names of three crucial columns (yellow).
ID containing the IDs of municipalities
NAME containing the name of the municipality
REGION containing the name of the region
All the other columns contain the attribute data. It is necessary to specify the weight (blue) and range (green) for each attribute
Note: Uploaded data are stored anonymously at out server and will not be used for any other purposes.
Source: urban_data.csv
Multifile method selection
Mean
Choose of method of multifile computation:
MEAN: SimUrb will compute the mean of modified matrices for all compressed files.
Map data
Map data should be in JSON file format and have WGS84 projection (EPSG:4326)
It is useful to simplify geometry for faster loading.
Map layer has to contain three columns:
ID containing the IDs of municipalities
NAME containing the name of the municipality
REGION_NAME containing the name of the region
Source: urban_map
Degree of occurrance <0,1>
Define degree of occurrance
Min. size of group
This number represents the minimal number of municipalities in each resulting group.
The lowest possible value is 2.
Use parameter p <0,1>
The parameter
p
takes value from the interval <0,1> and represents the degree of similarity between municipalities.
The higher value of
p
, the higher similarity of the municipalities.
Non-disjoint groups
Use this option when the desired groups are not disjoint - the calculation will find all maximal cliques.
Municipalities in these groups will be similar to each other according to given parameter
p
.
