Definition of levels

Each of the layers that we have obtained represents a conceptual level of the geographical dimension, in the package it is called geolevel. To define a geolevel, we need a layer and the set of attributes that make up the layer’s key (which uniquely identify each of its instances).

We can previously check if a set of attributes form a key of the layer using the check_key function.

library(tidyr)
library(sf)
library(geodimension)

names(layer_us_city)
#>  [1] "statefp"      "placefp"      "placens"      "geoid"        "name"        
#>  [6] "namelsad"     "lsad"         "classfp"      "pcicbsa"      "pcinecta"    
#> [11] "mtfcc"        "funcstat"     "aland"        "awater"       "shape_length"
#> [16] "shape_area"   "geoid_data"   "geometry"

check_key(layer_us_city, key = c("name", "statefp"))
#> [1] FALSE

check_key(layer_us_city, key = c("geoid"))
#> [1] TRUE

We might expect the city name (name) and state code (statefp) to be sufficient to identify a city, however, they are not³. We check that the geoid field is a valid key, therefore, it will be the one we use to define the geolevel.

We can check the geometry that is considered for the definition of the level by means of the get_geometry function (it simplifies the types into three: point, line, and polygon). In addition, we give each level a name to be able to refer to it, as shown below.

get_geometry(layer_us_city)
#> [1] "point"

city <-
  geolevel(name = "city",
           layer = layer_us_city,
           key = c("geoid"))

For county it is the same as for city, the name and the code of the state do not compose a valid key. In this case, the geometry is polygon. Additionally, a layer with another geometry can be associated using the add_geometry function or, in the case of point-type geometry, it can be generated from the polygon layer using the complete_point_geometry function, as is done below.

get_geometry(layer_us_county)
#> [1] "polygon"

county <-
  geolevel(name = "county",
           layer = layer_us_county,
           key = c("geoid")) %>%
  complete_point_geometry()

In the same way, the checks are made and the rest of the levels are defined. Although all the layers are of the polygon type, we generate the point layers only for those that we think may be needed.

In some cases, latitude and longitude are stored as fields in the attribute table, from which we can generate a layer of points using the coordinates_to_geometry function. We can later associate that layer to the corresponding level using the add_geometry function mentioned above.

Below is only the definition of the levels.

us_state_point <-
  coordinates_to_geometry(layer_us_state,
                          lon_lat = c("intptlon", "intptlat"))

state <-
  geolevel(name = "state",
           layer = layer_us_state,
           key = c("statefp")) %>%
  add_geometry(layer = us_state_point)

region <-
  geolevel(name = "region",
           layer = layer_us_region,
           key = c("regionce"))

division <-
  geolevel(name = "division",
           layer = layer_us_division,
           key = c("divisionce"))

nation <-
  geolevel(name = "nation",
           layer = layer_us_nation,
           key = c("name"))

Once the levels are defined, then we will define the dimension and the relationships between the levels.

Definition of relationships

To define a geodimension, we give it a name and start from any geolevel. Next, we add the rest of the geolevels in any order.

gd <-
  geodimension(name = "gd_us",
               level = region) %>%
  add_level(division) %>%
  add_level(state) %>%
  add_level(nation) %>%
  add_level(city) %>%
  add_level(county)

Next, we can define the relationships that we want to consider between the levels. In a relationship there are two parts, the lower level and the upper level. To define the relationships, the following points must be taken into account:

• There are no restrictions on the relationships you define, as long as the relationship can be established.

• It is only necessary to define direct relationships (from them, indirect ones are derived).

• Relationships can be defined using attributes with common values between the levels or through geographic relationships between their instances.

• If we want to reference the upper level through attributes, these must form a valid key for the level (it does not necessarily have to be the key that was indicated when defining it, this is used by default).

• Currently, to define a relationship using geographic properties, the upper level must be of type polygon.

The relationships between state, region, division and nation are defined below.

gd <- gd %>%
  relate_levels(lower_level_name = "state",
                lower_level_attributes = c("division"),
                upper_level_name = "division") %>%
  relate_levels(lower_level_name = "division",
                upper_level_name = "region",
                by_geography = TRUE) %>%
  relate_levels(lower_level_name = "region",
                upper_level_name = "nation")

The relationship between state and division is defined by a state attribute that matches the division key.

The relationship between division and region is defined by geographic relationship because they do not have any attributes in common.

Finally, as nation has only one instance, it relates directly to all instances of the indicated level (in this case, region), no additional relationship is required.

In addition to these relationships there is a clear relationship between city and state and also between county and state. In both cases it can be defined by attributes.

gd <- gd %>%
  relate_levels(lower_level_name = "city",
                lower_level_attributes = c("statefp"),
                upper_level_name = "state") %>%
  relate_levels(lower_level_name = "county",
                lower_level_attributes = c("statefp"),
                upper_level_name = "state")

The relationship between city and county is a bit fuzzy (at least for me), it depends on the state, the city and also the county. In any case, if we are interested in establishing a relationship, we could define it between city and state using the geographical properties of the levels, since county includes polygon-type geometry.

gd <- gd %>%
  relate_levels(lower_level_name = "city",
                upper_level_name = "county",
                by_geography = TRUE)

We can check if all the instances have been related using the following function:

nrow(
  gd %>% get_unrelated_instances(lower_level_name = "city",
                                 upper_level_name = "county")
)
#> [1] 0

Since there are no unrelated instances, each city has been linked to the county whose boundaries contain it.

If we did a similar check for each defined relation, we would observe that all the instances of the lower levels have been related to those of the higher levels, except for the following:

nrow(
  gd %>% get_unrelated_instances(lower_level_name = "state",
                                 upper_level_name = "division")
)
#> [1] 1

If we look at the content:

The region or division code does not correspond to any of the existing ones. If we want to relate all the instances of state to the nation level, we must define the relationship explicitly (there are other solutions but we will not consider them here, in any case they can be generated from this one).

gd <- gd %>%
  relate_levels(lower_level_name = "state",
                upper_level_name = "nation")

With these operations we have defined a geodimension.

Obtaining information

From a geodimension we can obtain information in table or layer format, to define a geographic dimension in a star schema. We can also define new versions of the dimension.

We can consult the levels of the geodimension using the following function:

gd %>%
  get_level_names()
#> [1] "city"     "county"   "division" "nation"   "region"   "state"

A new geodimension is defined by selecting a subset of levels, which we want to take into account when obtaining information, or to define new dimensions.

gds <- gd %>%
  select_levels(level_names = c("state", "division", "region", "nation"))

gds %>%
  get_level_names()
#> [1] "division" "nation"   "region"   "state"

From any level of the geodimension, a data table can be obtained that includes only the data of the level or all the data inherited from higher levels. For each level you can indicate whether or not a prefix is added to identify the origin of the fields. By default it is added, as you can see below.

ld <- gd %>%
  get_level_data(level_name = "division")
names(ld)
#> [1] "division_key" "divisionce"   "affgeoid"     "geoid"        "name"        
#> [6] "lsad"         "aland"        "awater"

ld <- gd %>%
  get_level_data(level_name = "division",
                 inherited = TRUE)
names(ld)
#>  [1] "division_key"      "divisionce"        "affgeoid"         
#>  [4] "geoid"             "name"              "lsad"             
#>  [7] "aland"             "awater"            "NATION_nation_key"
#> [10] "NATION_name"       "NATION_affgeoid"   "NATION_geoid"     
#> [13] "REGION_region_key" "REGION_regionce"   "REGION_affgeoid"  
#> [16] "REGION_geoid"      "REGION_name"       "REGION_lsad"      
#> [19] "REGION_aland"      "REGION_awater"

Previously, if we need it, we can obtain the name of the levels from which a level will inherit attributes.

gd %>%
  get_higher_level_names(level_name = "state",
                         indirect_levels = TRUE)
#> [1] "division" "nation"   "region"

ld <- gd %>%
  get_level_data(level_name = "state",
                 inherited = TRUE)
names(ld)
#>  [1] "state_key"             "statefp"               "region"               
#>  [4] "division"              "statens"               "geoid"                
#>  [7] "stusps"                "name"                  "lsad"                 
#> [10] "mtfcc"                 "funcstat"              "aland"                
#> [13] "awater"                "intptlat"              "intptlon"             
#> [16] "shape_length"          "shape_area"            "geoid_data"           
#> [19] "DIVISION_division_key" "DIVISION_divisionce"   "DIVISION_affgeoid"    
#> [22] "DIVISION_geoid"        "DIVISION_name"         "DIVISION_lsad"        
#> [25] "DIVISION_aland"        "DIVISION_awater"       "NATION_nation_key"    
#> [28] "NATION_name"           "NATION_affgeoid"       "NATION_geoid"         
#> [31] "REGION_region_key"     "REGION_regionce"       "REGION_affgeoid"      
#> [34] "REGION_geoid"          "REGION_name"           "REGION_lsad"          
#> [37] "REGION_aland"          "REGION_awater"

For a level we can obtain the available geometries and a layer with the attribute configuration we want and the selected geometry.

gd %>%
  get_level_geometries(level_name = "state")
#> [1] "point"   "polygon"

ll <- gd %>%
  get_level_layer(level_name = "state",
                  geometry = "polygon",
                  only_key = TRUE)

plot(ll)

In addition to these functions, the package offers the possibility to change the CRS of all the layers of a geodimension using the transform_crs function.