Global datasets derived from remote sensing, urban sensors, crowdsourcing, or surveys can provide valuable insights on the current state of cities, how cities are changing, and opportunities to improve the urban environment. This technical note discusses methods for using these data in combination with locally meaningful jurisdictional boundaries to calculate local measurements of indicators on several themes—including access to urban amenities, air quality, biodiversity, flooding, climate change mitigation, heat, and land protection and restoration—relevant to urban decision-makers, researchers, and other stakeholders. 

The authors identified and prioritized these indicators in consultation with program staff and stakeholders from several global sustainable urban development initiatives: Cities4Forests; UrbanShift; Transformative Urban Coalitions; and Deep Dive Cities from World Resources Institute’s Ross Center for Sustainable Cities. We also generated indicator calculations for cities of interest for these initiatives. These indicators can help urban policymakers and civil society assess differences within their cities; make comparisons with other cities; and measure themselves against national or global benchmarks, such as the Sustainable Development Goals, or against self-defined metrics. We applied geospatial analysis and zonal statistics methods to existing published geospatial datasets and relevant administrative, statistical, or physical city boundaries to calculate comparable indicators for any city or urban area. This methodology can be applied to any area of interest on Earth. Most indicators are based on open-source data, increasing the feasibility of repeating, replicating, and scaling the analyses at low marginal cost. Although the transferability and comparability of these methods are notable strengths of this approach, this note also discusses the limitations of this approach for decision-making..