LAUSR

You cannot improve what cannot be measured (Drucker 1959). In urban planning, this line of thought has guided the way we track progress and analyze the effects of implemented policies. While cities are generators of innovation and wealth, they also represent a visible relic of social and cultural norms through their reflection of the spatial organization of human society. Urban planners help guide this organization through policy and relevant environmental design interventions. To compare levels of policy efficiency across locations, there is an intensifying need not only to develop common indicators that measure the performance of urban policy that are both representative and comparable between countries, states, cities, and neighborhoods but also to make these indicators easily measurable and their results digestible to diverse audiences (Bobek 2015). Presently, there are a myriad of urban indicators which can be evaluated for a given agenda. There are also an abundance of institutions, researchers, organizations, tools, and methods used to compile and analyze these indicators. However, the fundamental problem with this variety of measurement options and approaches is the lack of consistency and comparability (both over time and between locations), thereby decreasing generalizability to broader contexts. This issue is reflected in many published and submitted manuscripts. The ability to measure the impacts of planning policy has often been alluded to in multiple articles as “urban policy performance,” yet no clear consensus definition of this term fully exists (Boschken 2000; Kaplan et al., 2022). As community interests have been embraced as both formulators and targets of new policy, performance monitoring and evaluation have become both more complex and more necessary (Murtagh 1998). Some common urban policy performance indicators include land use, demographics, points of interests, population and building density, floor-to-area ratio, mobility, safety, design features, economic vitality, quality of life, and street activity, but these measures expand exponentially when examining specific topics such as resilience, regeneration, transportation, or other related urban planning sub-fields (Sisto et al., 2021). Due to such a broad and growing set of data linked to urban settings, urban data analytics and methods have become important as ways to analyze cities and neighborhoods as well as to decipher long-term, sustainable plausible outcomes of possible planning policy options and scenarios. As a result, numerous new tools have rapidly emerged, which seek to automate the process of analyzing urban conditions and policy impacts through intrinsically linked algorithms and commands. Broader, more interpretive frameworks such as Plan Evaluation methods for assessing plan quality or even the United Nations Sustainable Development Goals for guiding an overarching framework have been commonly used in the literature. New innovative resources, however, which link urban data into easy-to-use tools such as the Environmental Protection Agency’s National Stormwater Calculator, the Long-Term Hydrologic Impact Analysis (L-THIA) model, Sasaki’s Carbon Conscience tool, the California Academy of Sciences and National Geographic Society’s iNaturalist Tool, or the Gehl Institute’s Public Life tool now exist. These examples are only a subset of the example of urban policy performance resources available to examine measures such as stormwater runoff, pollutant load, carbon sequestration, biodiversity, or urban pedestrian activity. Yet, such tools are not as often applied in the planning literature, in Journal of Planning Education and Research (JPER), or otherwise. Perhaps this is due to both the newness of these tools, the limitations in their application, and because there is no agreed upon definition of urban policy performance. Because no such consensus definition exists, ethos and approaches for measuring urban policy performance remain variable, broad, and disconnected. Meanwhile, other programs such as ArcUrban and ArcGIS Pro are continually building in automated analytical tools, while online dashboards and multiple other new online and desktop platforms for combining and assessing urban spatial data and capabilities to assess urban policy performance are appearing almost daily. The aforementioned tools (and many others which are not mentioned here for brevity) afford the capabilities to help quantitatively compare results and impacts of urban policy across time and location. Now is the time for both the creation of new urban performance tools, models, and calculators, and the mixing and linking of existing ones to help develop common methodologies based on the proven indicators that can be applied and scaled to multiple cities and neighborhoods to generate a common framework for measuring the impact of public policies. In this issue of JPER alone, performance measures for measuring (1) the child-friendliness of local spaces (Loebach and Gilland), (2) neighborhood walkability (Frank et al.), (3) 1120414 JPEXXX10.1177/0739456X221120414Journal of Planning Education and ResearchEditorial editorial2022