Example Tilesets
Some of the spatial datasets offered in the Data Observatory are very large (a few TB), either due to their global coverage, such as WorldPop or NASADEM, or their fine granularity, such as ACS Sociodemographics at census block group level and their visualization requires the creation of tilesets. Tilesets creation is currently only available for BigQuery users through the CARTO Analytics Toolbox.
We have created a collection of ready-to-use Data Observatory tilesets from public datasets that are publicly available in the BigQuery project
carto-do-public-tilesets.Use the gallery below to browse examples of the types of visualizations that can achieved along with a table that details how to find the location and characteristics of all available tilesets.
DO dataset | Variables | Type | Example viz | Location in BigQuery |
|---|---|---|---|---|
d.c0001_t as population_2016, d.c0004_t as total_dwellings, d.c0006_t as population_sq_km | Simple | carto-do-public-tilesets.can_statistics.demographics_sociodemographics_can_censusdivision_2016_5yrs_2016_tileset_000 | ||
SUM(population) as population, SUM(retail) as retail, SUM(food_drink) as food_drink | Aggregation | carto-do-public-tilesets.carto.derived_spatialfeatures_usa_quadgrid15_v1_yearly_2020_tileset_002 | ||
SUM(population) as population, SUM(retail) as retail, SUM(food_drink) as food_drink | Aggregation | carto-do-public-tilesets.carto.derived_spatialfeatures_esp_quadgrid15_v1_yearly_2020_tileset_000 | ||
d.t1_1 as population_per_sqkm, d.t21_1 as households_per_sqkm, d.t6_2 as foreigners_per_sqkm, all normalized by squared kilometer | Simple | carto-do-public-tilesets.esp_ine.demographics_sociodemographics_esp_censussection_2011_yearly_2011_tileset_003 | ||
Spielman_Singleton_Group | Simple | carto-do-public-tilesets.gbr_cdrc.demographics_newamericanatlas_usa_censustract_2019_5yrs_2020_tileset_002 | ||
total_pop normalized per squared kilometer as population_per_sqm, economically_active, long_term_unemployed | Simple | carto-do-public-tilesets.gbr_ons.demographics_sociodemographics_gbr_outputarea_2011_10yrs_2011_tileset_000 | ||
total_pop, households, median_income, income_per_capita | Simple | carto-do-public-tilesets.usa_acs.demographics_sociodemographics_usa_blockgroup_2015_5yrs_20142018_tileset_001 | ||
SUM(population) as population_t | Aggregation | carto-do-public-tilesets.worldpop.demographics_population_glo_grid1km_v1_yearly_2020_tileset_000 | ||
SUM(population) as population_t | Aggregation | carto-do-public-tilesets.worldpop.demographics_population_jpn_grid100m_v1_yearly_2020_tileset_000 | ||
amenity | Simple | carto-do-public-tilesets.openstreetmap.pointsofinterest_nodes_esp_latlon_v1_quarterly_v1_tileset001 | ||
amenity | Simple | carto-do-public-tilesets.openstreetmap.pointsofinterest_nodes_fra_latlon_v1_quarterly_v1_tileset002 | ||
MAX(value) as value | Aggregation | carto-do-public-tilesets.coschoolofmines.demographics_nighttimelights_glo_grid500x500m_v1_yearly_2020_tileset_000 | ||
AVG(elevation) as elevation | Aggregation | carto-do-public-tilesets.nasa.environmental_nasadem_glo_quadgrid15_v1_static_v1_tileset_000 |
Last modified 4mo ago