Global data sets 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.

These indicators were identified and prioritized in consultation with program staff and stakeholders from two global sustainable urban development initiatives: Cities4Forests and UrbanShift. Indicator calculations were also generated for cities of interest to 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. Geospatial analysis and zonal statistics methods are applied to existing published geospatial data sets 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 limitations of this approach for decision-making.