- Measuring Blight
- Volume 24 Number 2
- Managing Editor: Mark D. Shroder
- Associate Editor: Michelle P. Matuga
U.S. Department of Housing and Urban Development
The views expressed in this article are those of the author and do not represent the official positions or policies of the Office of Policy Development and Research, the U.S. Department of Housing and Urban Development, or the U.S. government.
Communities across the United States struggle with blighted urban environments. Negative associations with blight include crime (Branas, Rubin, and Guo, 2012), falling property values (Han, 2014), poor social determinants of health (Garvin et al., 2013), sprawl (Brueckner and Helsley, 2011), and dwindling tax bases but increased burdens (Tri-COG Collaborative, 2013). Despite substantial research into the negative effects of blight, no single definition of blight emerges (Morckel, 2014). The context of defining blight matters for identifying the proper measurement and data source for evaluating blight. Discussing the ever-evolving definition of blight, Gordon (2004) quotes a California state legislator who said, “defining blight became an art form” which also applies to the measurement of blight.
Measuring blight continues to remain important because during the 2010s, approximately one-fifth of metropolitan areas and one-half of micropolitan areas lost population (Mackun, Comenetz, and Spell, 2021). As communities shrink, structures will be abandoned. Because the definition of blight is ambiguous, measuring this phenomenon is difficult. Measuring blight requires substantial work, which can be labor-intensive and can quickly become outdated (Pagano and Bowman, 2000). Windshield and parcel surveys have been sources of good-quality data but are expensive to produce and maintain. Administrative records are increasingly popular measurements of blight because the information already exists, although this data frequently uses other indicators as a proxy for blight. Efforts to measure blight using administrative records have included housing code violations (Hillier et al., 2003), tax delinquency (Whitaker and Fitzpatrick, 2013), 311 calls-forservice (Athens et al., 2020), and postal delivery status records (Molloy, 2016).
This issue of Cityscape explores recent developments in the measurement of blight. Administrative data, particularly housing vacancy data, continue to be a leading proxy for blight. Novel techniques using image classification ameliorate early warnings of housing abandonment, which may enable blight intervention programs to become more proactive rather than reactive. This symposium also describes how the measurement of blight is also correlated to the measurement of other phenomena, such as sprawl.