Commit 0e0deec7 authored by Cecilia Nievas's avatar Cecilia Nievas
Browse files

Added chapter on Storage

parent 2a930442
Pipeline #40761 passed with stage
in 2 minutes and 37 seconds
......@@ -29,12 +29,13 @@ et al., 2020).
The [`ExposureModelESRM20`](../gdeimporter/aggregatedexposuremodel.py#L341) sub-class
represents the structure and contents of the exposure model of the European Seismic Risk Model
2020 (ESRM20, Crowley et al., 2020). The ESRM20 exposure model covers three occupancy cases
(residential, commercial and industrial) for 44 European countries: Albania, Andorra, Austria,
Belgium, Bosnia_and_Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland,
France, Germany, Gibraltar, Greece, Hungary, Ireland, Iceland, Isle_of_Man, Italy, Kosovo,
Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro,
the Netherlands, Norway, North Macedonia, Poland, Portugal, Romania, Serbia, Slovakia,
Slovenia, Spain, Sweden, Switzerland, Turkey, and the United Kingdom.
(residential, commercial and industrial) for 44 European countries (names include underscores
used internally by ESRM20 and `gde-importer`): Albania, Andorra, Austria, Belgium,
Bosnia_and_Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France,
Germany, Gibraltar, Greece, Hungary, Ireland, Iceland, Isle_of_Man, Italy, Kosovo, Latvia,
Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, Norway,
North_Macedonia, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden,
Switzerland, Turkey, and the United_Kingdom.
<img src="images/aem_ESRM20.png" width=75%>
......
# Storage
The `gde-importer` writes its output to six tables of the
[GDE Tiles](https://git.gfz-potsdam.de/dynamicexposure/globaldynamicexposure/database-gdetiles)
database. These are:
- [aggregated_sources](https://git.gfz-potsdam.de/dynamicexposure/globaldynamicexposure/database-gdetiles#aggregated_sources-information-about-sources-of-aggregated-exposure-models)
- [data_units](https://git.gfz-potsdam.de/dynamicexposure/globaldynamicexposure/database-gdetiles#data_units-information-about-data-units)
- [data_unit_tiles](https://git.gfz-potsdam.de/dynamicexposure/globaldynamicexposure/database-gdetiles#data_unit_tiles-information-about-data-unit-tiles)
- [data_units_buildings](https://git.gfz-potsdam.de/dynamicexposure/globaldynamicexposure/database-gdetiles#data_units_buildings-information-about-buildings-in-a-data-unit)
- [exposure_entities_costs_assumptions](https://git.gfz-potsdam.de/dynamicexposure/globaldynamicexposure/database-gdetiles#exposure_entities_costs_assumptions-information-about-assumptions-associated-with-building-replacement-costs)
- [exposure_entities_population_time_distribution](https://git.gfz-potsdam.de/dynamicexposure/globaldynamicexposure/database-gdetiles#exposure_entities_population_time_distribution-information-about-the-distribution-of-people-in-buildings-at-different-times-of-the-day)
Please see the description of their contents and fields in the corresponding links.
## Number of Buildings of Different Classes in a Data-Unit Tile
For a specific data-unit tile, which is defined by a unique combination of `quadkey`,
`aggregated_source_id`, `occupancy_case` and `data_unit_id` in the `data_unit_tiles` table, its
total number of buildings (`aggregated_buildings` in the `data_unit_tiles` table) can be
multiplied by the `proportions` in the `data_units_buildings` table for the corresponding
`aggregated_source_id`, `occupancy_case` and `data_unit_id` to obtain the number of buildings
per building class. As explained
[here](03_Organisation_Building_Information.md#building-classes-proportions-and-properties),
building classes are defined by the combination of the fields `building_class_name`,
`settlement_type` and `occupancy_subtype` from the `data_units_buildings` table.
## Number of People in a Building at Different Times of the Day
For any particular building class in the `data_units_buildings` table, the number of people
expected to be in the building during the day, night and transit times can be calculated as the
product between `census_people_per_building` from the `data_units_buildings` table and the
fields `day`, `night` and `transit` from the `exposure_entities_population_time_distribution`
table, corresponding to the relevant `exposure_entity`, `occupancy_case` and
`aggregated_source_id`.
## Structural, Non-Structural and Content Replacement Costs of a Building
For any particular building class in the `data_units_buildings` table, its total replacement
cost `total_cost_per_building` can be disaggregated into the costs of structural and
non-structural components, as well as contents, by multiplying the `total_cost_per_building` by
the fields `structural`, `non-structural` and `contents` of the
`exposure_entities_population_time_distribution` table, corresponding to the relevant
`exposure_entity`, `occupancy_case` and `aggregated_source_id`.
......@@ -15,7 +15,7 @@ models onto the zoom level 18 tiles, both in terms of numbers and classes of bui
5. [Processing logic](05_Processing_Logic.md)
6. [Ensuring full geographic coverage](06_Ensuring_Full_Geographic_Coverage.md)
7. [Creation of data-unit tiles](07_Creation_Data_Unit_Tiles.md)
8. Storage
8. [Storage](08_Storage.md)
# Installation and running
......
......@@ -45,7 +45,7 @@ class Configuration:
List of keys of occupancy_cases of the input aggregated exposure model for which
data will be retrieved.
self.exposure_entities_to_run (list of str):
List of names of the exposure entities for which the data units will be retrieved.
List of names of the exposure entities for which the code will be run.
self.exposure_entities_code (str or dict):
If "ISO3" (str), the country ISO3 codes associated with the names of the exposure
entities will be automatically retrieved and used as their codes. Otherwise it needs
......
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment