HCD created an interactive statewide AFFH Data Viewer to assist in the assessment of fair housing. HCD solicited feedback from advocates, councils of government, partner public agencies, and academic research groups to ensure the first iteration of the tool consolidates relevant data and provides options for addressing each component within the Assessment of Fair Housing (within the Housing Element). It consists of mapped data layers in six categories:
- Fair Housing Enforcement and Outreach Capacity
- Segregation and Integration
- Disparities in Access to Opportunity
- Disproportionate Housing Needs/Displacement Risk
- Racially Concentrated Areas of Poverty and Affluence
- Supplemental Data
The interactive maps can be explored in any internet browser and exported as a PDF, jpeg, and other image files. In addition, the underlying data layers can be downloaded for offline data analysis. HCD plans to continuously update these map layers and add additional data, as well as incorporate user feedback. Comments can be submitted to AFFHGuidance@hcd.ca.gov.
Recent Additions to the AFFH Data Viewer:
- Subsidized Housing – CHPC, 2021 (Fair Housing Enforcement and Outreach Tab) Added December 2021
- Point in Time Count – Emergency Shelter Housing Location – HUD, 2020 (Disproportionate Housing Needs Tab) Added December 2021
- Racially Concentrated Areas of Affluence (RCAA) – HCD, 2021 (Racially and Ethnically Concentrated Areas of Poverty and Affluence Tab) Added July 2022
- Estimated Displacement Risk Model – UDP, 2022 (Disproportionate Housing Needs / Displacement Risks Tab) Added September 2022
HCD’s RCAA layer is now available for public use on the AFFH Data Viewer. As stated in HCD’s AFFH Guidance Memo, when analyzing patterns and trends of segregation and proposing policy approaches, localities should not only focus on communities of color. Segregation is a continuum, with polarity between race, poverty, and affluence, which can be a direct product of the same policies and practices. To better evaluate these conditions, both sides of the continuum should be considered and compare patterns within the community and across the region. This more holistic approach will better unveil deeply rooted policies and practices and improve identification and prioritization of contributing factors to inform more meaningful actions. The RCAA metric will aid local jurisdictions in their analysis of racially concentrated areas of poverty and affluence pursuant to AB 686 and AB 1304. HCD’s RCAA metric is provided as a resource to be paired with local data and knowledge – jurisdictions are encouraged but not required to use the RCAA layer provided by HCD in their housing element analyses. HCD will continue to revisit and refine the layer over the coming year. If you identify areas where the RCAA methodology does not reflect local dynamics in your community, please reach out to us at email@example.com.
HCD has now added a map recently released by the Urban Displacement Project (UDP) to the AFFH Data Viewer that identifies varying levels of displacement risk for low-income renter households. Displacement risk means that in 2019—the most recent year with reliable census data—a census tract had characteristics which, according to the model, are strongly correlated with more low-income renter population loss than gain. In other words, the model estimates that more low-income households are leaving these neighborhoods than moving in. This map will aid local jurisdictions in their analysis of disproportionate housing needs, including displacement risk, pursuant to the duty to AFFH. This map is provided as a resource and should be paired with other variables (such as overcrowding, cost burden, and income diversity) to fully capture displacement risk. Any analysis of displacement risk should also consider local data and knowledge (including public comment) of on-the-ground displacement trends, given that some areas could be impacted by recent changes not captured in the model, such as changes to market conditions, the COVID-19 pandemic, or pending planning decisions.