Google’s Environmental Insights Explorer (EIE) represents one of the most ambitious attempts to democratize climate data for cities worldwide, providing free emissions analysis to municipalities that previously couldn’t afford costly greenhouse gas inventories. Launched in September 2018 at the Global Climate Action Summit in San Francisco, this platform now offers environmental data for over 40,000 cities and regions across 120+ countries, transforming how urban areas understand and address their carbon footprints. The platform emerged from a stark reality: while 9,000+ cities committed to the Paris Agreement, fewer than 20% had completed baseline emissions inventories due to costs often exceeding hundreds of thousands of dollars and timelines stretching years.
From five pilot cities to global climate infrastructure
The Environmental Insights Explorer began as a beta project with just five pilot cities: Melbourne, Buenos Aires, Victoria (Canada), Pittsburgh, and Mountain View—Google’s own headquarters. Rebecca Moore, Director of Google Earth Outreach, led a cross-functional team of carbon accounting experts, software engineers, and data visualization specialists to build what would become a cornerstone of urban climate planning. The project grew from Google’s earlier sustainability initiatives, particularly Project Sunroof (launched 2015 for rooftop solar analysis) and Project Air View (mobile air quality monitoring via Street View vehicles).
The platform’s expansion accelerated rapidly. By October 2019, Kyoto became the first Japanese city added, with European cities like Dublin following closely. At COP26 in 2021, Google announced transportation emissions data would cover 20,000+ cities worldwide. The Global Covenant of Mayors for Climate & Energy (GCoM), co-founded with Bloomberg Philanthropies and the European Commission, became EIE’s primary implementation partner, representing approximately 10,000 cities committed to fighting climate change. Additional partnerships with C40 Cities, ICLEI (Local Governments for Sustainability), and CDP further extended the platform’s reach and credibility among municipal planners.
Five data layers power urban climate analysis
EIE provides cities with five primary categories of environmental data, each derived from Google’s proprietary sources and validated methodologies. Building emissions estimates calculate heating, cooling, and electricity consumption for residential and non-residential structures using Google Maps building footprints and floor space analysis. This data covers everything from single-family homes to hospitals, warehouses, and retail establishments.
Transportation emissions represent perhaps EIE’s most innovative contribution, utilizing aggregated, anonymized Location History data from Google Maps to understand how people move within and through cities. Unlike traditional traffic counts conducted periodically at specific locations, this approach provides continuous observation of trips by mode—cars, buses, bicycles, walking, and transit—with breakdowns for inbound, outbound, and in-boundary travel. ICLEI USA’s technical review found this transportation data “more accurate than other data sources” and “higher-quality than traditional sources.”
The rooftop solar potential layer, derived from Project Sunroof technology, analyzes total sunshine exposure, weather patterns, and roof dimensions to estimate energy generation capacity across entire cities. Tree canopy coverage uses aerial imagery and machine learning algorithms to map urban forest distribution, correlating with heat risk vulnerability and population density. Finally, air quality data—available only in Hamburg, Dublin, Copenhagen, Amsterdam, London, and Bengaluru—provides street-by-street measurements of black carbon, ultrafine particles, nitrogen dioxide, and PM2.5 collected by Google Street View vehicles equipped with environmental sensors.
How machine learning transforms location data into carbon estimates
The technical methodology behind EIE combines Google’s vast data resources with standardized emission factors to produce city-scale estimates. The process begins with activity measurement—using aggregated location data to infer traffic patterns, travel modes, distances, and building occupancy. This data is then scaled to account for total population (not just Google users) before applying regional-specific fuel type, fuel efficiency, and emissions factors following the CURB methodology developed for city-scale greenhouse gas accounting.
Machine learning plays a critical role throughout the platform. AI models extract three-dimensional roof geometry from aerial imagery, including angles and slopes that affect solar potential. Tree detection algorithms identify and measure urban canopy coverage. Transportation mode classification systems distinguish between driving, cycling, transit use, and walking based on movement patterns. The resulting emissions estimates align with the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC), the international standard for urban carbon accounting, and are compatible with the U.S. Community Protocol used by American cities.
The methodology documentation is publicly available, and ICLEI conducted extensive technical validation comparing EIE data to existing community-scale GHG sources. Their assessment found EIE methods “useful to ‘upscale’ locally sourced building performance data” and providing “greater completeness using uniquely powerful ways of measuring transportation and building activity parameters.”
Cities worldwide leverage EIE for tangible climate action
The real impact of EIE becomes visible through implementation stories spanning every continent. Los Angeles pioneered the Tree Canopy Lab in November 2020, discovering that more than 50% of Angelenos live in areas with less than 10% tree canopy coverage and 44% face extreme heat risk. This data drove the city’s commitment to increase canopy coverage by 50% in highest-need areas by 2028, with immediate plans to plant and maintain 90,000 trees. City Forest Officer Rachel Malarich now uses EIE alongside traditional inventory systems to project canopy acreage gains.
Copenhagen provides perhaps the most sophisticated example of air quality data application. After Google Street View vehicles collected street-level pollution measurements, researchers from Utrecht University and Aarhus University discovered major access roads contained nearly three times more ultrafine particles and nitrogen dioxide, with black carbon levels five times higher than residential areas. These findings directly shaped Copenhagen’s “Thrive Zones” initiative—designing schools and playgrounds away from high-pollution corridors and creating healthier bicycle routes that avoid car traffic.
Dublin’s Project Air View deployment generated over 50 million air quality measurements at 5 million locations across more than 30,000 kilometers between May 2021 and August 2022—the largest such urban dataset in Europe. The city hosted a February 2023 data hackathon to develop solutions and published all measurements openly on Smart Dublin’s data platform. Key findings revealed elevated NO2 levels along the River Liffey quays due to traffic congestion.
In Yokohama, Japan, where households generate approximately 25% of city CO2 emissions, EIE transformed environmental education. The platform is now incorporated into curricula from junior high through university, with students visualizing emissions impacts and developing behavior change strategies. University students created EV promotion reports later presented at Ministry of Foreign Affairs conferences, and Yokohama shares its educational approach with emerging Southeast Asian cities.
Málaga, Spain demonstrates direct infrastructure impact, with city officials crediting EIE for identifying critical daily commuter corridors, stating: “This data was the foundation for designing new, protected bike lanes that directly address traffic flow, making our active mobility strategy far more effective.” Meanwhile, 100+ Australian councils access EIE transportation data through Ironbark Sustainability’s Snapshot Climate tool, which calculates emissions from transport, waste, agriculture, and land-use change for local governments nationally.
Free access removes barriers, but full features require registration
EIE operates entirely without cost—Google provides it as part of sustainability commitments in partnership with GCoM. Access comes in two tiers: Preview Insights allows anyone to view sample environmental data for 40,000+ cities through the public portal at insights.sustainability.google, while the Insights Workspace provides full data access, download capabilities, and team collaboration features for registered users.
Full workspace access is available to city government employees, consultants working with municipalities, NGOs partnering with city governments, and other government-affiliated personnel. Users can sign up via Google’s website, requesting access for specific cities or regions. If a city isn’t yet in the database, users can request Google add it—though expansion depends on data availability and Google’s priorities.
The platform allows users to download and share transportation, building, and solar potential data, though export formats appear designed for climate planning rather than programmatic integration. Cities can make their EIE data publicly available from the Insights Workspace, with 320+ cities currently sharing data openly.
Integration possibilities remain limited despite Google’s ecosystem
Despite Google’s extensive cloud and data platforms, EIE operates primarily as a standalone web application without public API access for automated integration. This represents a significant limitation for organizations hoping to build programmatic workflows around EIE data. Users can download datasets manually, but there is no documented pathway for direct integration with BigQuery, Earth Engine, or external systems through automated pipelines.
That said, EIE data does flow into several third-party tools through partnership arrangements. ICLEI ClearPath, the greenhouse gas inventory tool used by hundreds of American cities, can incorporate EIE data into its calculations. Australia’s Snapshot Climate tool represents the most extensive third-party integration, pulling EIE transportation data for over 100 councils. Los Angeles combines EIE Tree Canopy data with their existing inventory management systems for urban forestry planning.
The platform connects conceptually to other Google sustainability tools—Project Sunroof provides individual rooftop solar analysis complementing EIE’s city-scale estimates, while Google Earth Engine offers agricultural and land-use analysis capabilities absent from EIE. However, these remain separate products requiring distinct access and workflows rather than integrated components of a unified platform.
Transparency concerns and methodological critiques emerge
A significant peer-reviewed critique appeared in Urban Studies in 2025, authored by Florian Koch and Sarah Beyer under the title “A gift from heaven: Google’s Environmental Insights Explorer and its tech-down approach to monitor urban sustainability beyond local contexts.” The researchers raised several concerns about EIE’s approach to urban sustainability measurement.
The primary criticism centers on transparency and opacity. EIE relies on proprietary data generation processes—the “black box” nature of Google’s location history data and modeling algorithms makes independent verification challenging. Koch and Beyer argue this creates power imbalances between Google and cities, with municipalities depending on data whose validity they cannot fully assess.
The paper introduces the concept of a “tech-down” approach to sustainability indicators, distinct from both bottom-up community-driven methods and top-down governmental frameworks. By defining sustainability metrics through a process dominated by one private company, local knowledge, context, and narratives risk marginalization. The researchers conclude that cities must consciously “reconcile [EIE’s] global standardisation with specific local needs” rather than accepting Google’s framework uncritically.
ICLEI’s technical assessments, while generally positive, identified methodological considerations. Transport emissions data may differ from local calculations due to different accounting approaches—EIE shows all inbound and outbound trips without allocation adjustments, potentially causing double-counting if used directly without GPC protocol modifications. The platform’s sampling from Google Location History users may also introduce biases not present in traditional traffic counting methods.
Geographic and feature coverage limitations persist. Air quality data remains confined to just six cities globally. Tree canopy analysis isn’t universally available. Some data is marked as “incomplete or a work in progress.” And critically, EIE excludes industrial emissions, agricultural operations, and other significant emissions sectors—it’s fundamentally an urban building and transportation tool.
2024 brought expanded partnerships and educational resources
The most notable 2024 development was EIE’s partnership with EIT Urban Mobility, a European innovation consortium focused on sustainable transportation. This collaboration reached over 60 cities, with 30+ actively participating in educational webinars. A joint session at Tomorrow.Mobility World Congress 2024 titled “The Power of Mobility Data for Cities” drew 50+ participants from 15 cities, demonstrating growing municipal interest in EIE’s capabilities.
Google launched a comprehensive Resource Center with tutorials, case studies, and implementation guides. New documentation includes an introduction guide for city sustainability professionals, deep-dive methodology videos explaining data generation processes, and a specialized guide for German municipalities navigating EIE implementation. Published case studies highlighted implementations in Athens (transitioning from top-down to bottom-up transport calculations), Greater Manchester (informing the 2040 Right Mix Local Transport Plan), Aarhus (supporting green transition), and New Taipei City (tracking net-zero progress).
The Insights Workspace received enhancements providing “first look at new insights and functionality” designed for comprehensive climate policy development, including improved year-over-year mobility trend analysis. These updates suggest Google continues investing in EIE despite the platform receiving less public attention than it did during its initial launch years.
Applications for regenerative agriculture remain severely limited
For regenerative agriculture operations, EIE provides minimal direct utility. The platform focuses exclusively on urban emissions—buildings and transportation—without including farmland-specific data, agricultural emissions tracking, soil carbon monitoring, or crop-related analysis. Rural areas generally fall outside EIE’s coverage scope.
Indirect applications exist for agricultural operations near urban centers. Farms could potentially use EIE’s transportation emissions data to understand regional logistics patterns for delivery route optimization, or leverage solar potential estimates for farm buildings with suitable rooftops. However, these represent marginal use cases far from the platform’s intended purpose.
Google Earth Engine provides the robust capabilities regenerative agriculture actually requires. Perennial, an agro-informatics company, uses Earth Engine with over 350,000 soil samples to map soil health, carbon content, and ecosystem metrics. Regrow monitors 1.2 billion acres globally through Earth Engine, tracking agricultural practices and verifying climate impacts of regenerative approaches. FAO datasets available through Earth Engine include drained organic soils emissions estimates, cropland carbon data, and methane/nitrous oxide monitoring for livestock operations. For any serious agricultural application, Earth Engine—free for research and nonprofit use—represents the appropriate Google tool rather than EIE.
Community sustainability initiatives find strong platform support
EIE’s design explicitly targets community-scale sustainability planning, making it highly valuable for local governments, NGOs, and neighborhood organizations focused on climate action. The platform helps communities lacking resources leapfrog costly primary data collection, establishing emissions baselines that would otherwise require months of fieldwork and hundreds of thousands of dollars.
Visual data helps communicate emissions sources to residents who may struggle with abstract carbon accounting concepts. Austin’s Environmental Program Manager Marc Coudert used EIE’s tree canopy data to identify higher ambient temperatures in the city’s Eastern Crescent, developing the Community Tree Priority Map that doubled tree planting investments in underserved neighborhoods. Chicago’s Department of Public Health applies Tree Canopy Insights to promote health and racial equity, discovering that the city’s hottest neighborhoods are often the most disadvantaged and focusing planting efforts accordingly.
Brazilian cities demonstrate community-scale adoption at national scale. After ICLEI South America showcased EIE to 1,500+ viewers, 23 municipalities adopted the platform. Google.org’s $4 million Action Fund Brazil provides $150,000 subgrants to nonprofits in Porto Alegre and Curitiba for data-driven climate projects. Campo Grande now uses EIE data for monitoring its Urban Transport and Mobility Master Plan. Burlington, Canada uses EIE for Climate Action Plan community engagement, while the Tri-Cities Mayors Group in New Brunswick employs the platform for collaborative cross-municipal climate action.
Local energy production planning benefits from solar potential data
EIE’s rooftop solar potential layer provides meaningful value for local energy planning, though building-level analysis requires complementary tools. At city scale, EIE identified over 4 gigawatts of solar potential across 40 Canadian cities alone. Houston used EIE solar data to design a proposed 5 million MWh target plan as part of its climate action strategy. Mexico City analyzed potential to generate 4MW of renewable energy from rooftop installations using the platform.
Madrid partnered with ICLEI Europe to explore solar development through EIE, supporting the Madrid 360 Solar strategy targeting 30% of municipal building electricity demand from rooftop solar by 2030. These city-wide assessments help municipalities understand aggregate potential and set appropriate targets before detailed site-specific analysis.
For individual building and community solar project planning, Project Sunroof provides essential complementary capabilities. It analyzes 3D roof geometry including shadows, tilt, and orientation for specific addresses; calculates expected yearly savings; and offers data coverage for 43+ million rooftops in the U.S. The Solar API extends this to 320+ million buildings across 40 countries for business applications.
The optimal workflow combines EIE for city-wide context and emissions baseline, Project Sunroof for neighborhood and building-level solar assessment, and NREL tools like REopt and the Community Solar Scenario Tool for economic modeling and project design. This layered approach lets communities move from aggregate potential understanding through site identification to implementation planning.
Conclusion: A powerful but imperfect democratization of climate data
Google’s Environmental Insights Explorer has genuinely transformed climate planning for thousands of municipalities worldwide, providing free access to emissions data that would otherwise remain out of reach for small and medium cities—particularly in the developing world where climate action must scale most rapidly. The platform’s validated methodology, expanding feature set, and growing implementation base establish it as significant infrastructure for urban sustainability.
Yet the platform’s limitations deserve honest acknowledgment. The “tech-down” approach concentrating sustainability measurement power in a single corporation raises legitimate governance questions. Transparency about proprietary algorithms remains incomplete. Feature coverage varies dramatically by location, with air quality data confined to just six cities. And the absence of public API access limits integration possibilities for organizations building climate data workflows.
For regenerative agriculture, EIE provides virtually no direct value—Google Earth Engine is the appropriate tool for land-based carbon analysis. For community sustainability, the platform offers substantial utility when combined with local knowledge and complementary data sources. For local energy planning, EIE’s solar potential estimates provide useful city-scale context that should be combined with Project Sunroof’s building-level analysis and NREL’s economic modeling tools.
The most productive approach treats EIE as what it is: a powerful starting point for urban climate analysis that should inform but not replace locally-grounded emissions inventories, community expertise, and specialized tools for specific applications. Cities embracing this nuanced relationship—like Copenhagen combining air quality data with local urban planning knowledge, or Australian councils integrating EIE into Snapshot’s broader emissions framework—demonstrate how the platform delivers maximum value when positioned as one component of comprehensive climate action strategy rather than a complete solution unto itself.
econology 