Housing unit allocation

Housing unit allocation#

Description

This analysis sets up a detailed critical infrastructure inventory with housing unit level characteristics. The process aligns the housing unit inventory with physical systems, such as the inventory of buildings and the demand nodes of a potable water network. The allocation of housing units to the address points (buildings) provides a framework to account for uncertainty in community structure that allows for the hazard impacts to be analyzed statistically.

The output of this analysis is a CSV file with detailed household and housing unit characteristics (number of persons, race, tenure, vacancy) allocated to individual house units assigned to individual buildings.

Contributors

  • Science: Nathanael Rosenheim

  • Implementation: Nathanael Rosenheim, Michal Ondrejcek, and NCSA IN-CORE Dev Team

Related publications

  • Rosenheim, N., Guidotti, R., Gardoni, P. and Peacock, W.G. (2019). Integration of detailed household and housing unit characteristic data with critical infrastructure for post-hazard resilience modeling. Sustainable and Resilient Infrastructure DOI: 10.1080/23789689.2019.1681821

  • Rosenheim, Nathanael (2021). Detailed Household and Housing Unit Characteristics: Alpha Release of Housing Unit Inventories. DesignSafe-CI DOI: 10.17603/ds2-jwf6-s535

Input parameters

key name

type

name

description

result_name *

str

Result name

Name of the result dataset.

seed *

int

Seed

Initial value to seed the random number generator.

iterations *

int

Iterations

Number of iterations of running the probabilistic model.

Input datasets

key name

type

name

description

building_inventory *

ergo:buildingInventoryVer4
ergo:buildingInventoryVer5
ergo:buildingInventoryVer6
ergo:buildingInventoryVer7

Building inventory

A building inventory dataset.

housing_unit_inventory *

incore:housingUnitInventory

Housing inventory

A housing unit inventory dataset.

address_point_inventory *

incore:addressPoints

Address inventory

An address locations dataset.

Output datasets

key name

type

name

description

result *

incore:housingUnitAllocation

Results

A dataset containing results
(format: CSV).

(* required)

Execution

code snippet:

    # Create housing allocation
    hua = HousingUnitAllocation(client)

    # Load input dataset
    hua.load_remote_input_dataset("housing_unit_inventory", housing_unit_inv)
    hua.load_remote_input_dataset("address_point_inventory", address_point_inv)
    hua.load_remote_input_dataset("building_inventory", building_inv)

    # Specify the result name
    result_name = "IN-CORE_1bv6_housingunitallocation"

    seed = 1238
    iterations = 1

    # Set analysis parameters
    hua.set_parameter("result_name", result_name)
    hua.set_parameter("seed", seed)
    hua.set_parameter("iterations", iterations)

    # Run Housing unit allocation analysis
    hua.run_analysis()

full analysis: housingunitallocation.ipynb
Galveston, TX housing unit allocation: HUA_Galveston_2020-12-04.ipynb
Visualization of Total Population by various categories: pyincore-viz-analysis-example.ipynb