Alejandra Macarena Tomietto is an urban planner, infrastructure strategist, and architect based in Washington DC who has spent more than 15 years helping governments plan the future of cities. Her work brings together urban planning, infrastructure strategy, GIS, and human-centered design to help cities make smarter, more sustainable decisions about growth. When she joined a team tasked with analyzing how the Buenos Aires metropolitan area would evolve and to plan essential infrastructure like water and sanitation, she hit a wall: the official zoning maps she was given were outdated, and lacked the context only imagery can provide. By turning to Google Earth, Alejandra combined rich imagery with professional-grade data, bypassing bureaucratic delays to ground her decisions in reality. This remote analysis enabled her to predict urban growth patterns, identify areas for investment, and make better planning decisions, faster.
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Deeper local understanding |
Speed to impact |
2,567 km² mapped and analyzed |
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Combining historical imagery & GIS information on a single map to make better planning decisions |
“Something that could have taken weeks or even months can now be done in less than an hour” |
Large, complex geospatial information turned into a shared story for stakeholders |
We were tackling something deeply complex, and Google Earth made it feel easy.Urban Planning Expert
The Challenge: An incomplete planning picture
Buenos Aires is a complex, highly regulated metropolis with a massive variety of land uses, from informal settlements to gated communities to mixed-use zones. Alejandra needed to analyze 2,567 km² of metropolitan territory and predict how it would evolve so she could plan the best strategy for infrastructure, safety, and services.
To make these high-stakes decisions, she needed to ground her planning in reality. But the official tools available to her weren't keeping up. Official zoning maps were outdated, describing a version of the city that no longer existed on the ground. "Traditionally, urban planning relies on official, bureaucratic land-use maps," Alejandra says. "But as anyone working in the field knows, what's written in a zoning law rarely matches what is happening on the ground." With land uses changing rapidly, she needed a way to "cut through the complexity, stop guessing, and see the territory as it actually existed."
The Solution: Combining geospatial information to tell a complete story
To validate reality remotely, Alejandra turned to Google Earth, combining rich imagery with professional-grade data to assess the metropolitan area. By bringing these elements together on a single canvas, she could evaluate the city without relying solely on gathering new data and expensive, slow on-site exploration.
She began by importing information and creating new analysis directly on the map. She then organized her findings using layered folders to neatly structure the information and tell a clear story. This allowed Google Earth to serve as a shared canvas for the analysis.
After her data was incorporated, Google Earth's high-resolution imagery enabled her to analyze the metropolitan footprint at multiple scales. She could visualize the entire region as an interconnected network, while also identifying the unique shapes, scales, and boundaries of individual neighborhoods. To understand the pace of development, she combined her data with historical imagery, visualizing how these neighborhoods had changed over years.
By pinpointing the areas of the city that were growing the fastest and examining them remotely, she came to a powerful realization: nearly 400,000 residents were living in high environmental risk zones. By adding satellite imagery to data, she was able to reveal settlement logics — preexistence, connectivity, risk exposure — all crucial details that official land-use maps simply didn’t capture, exposing a real vs. legal territory gap that had been invisible to traditional planning. That combination of ground-truthed data and pattern-level insight is what made the approach credible enough for other organizations to independently adopt it for its own national urban-expansion analysis and for her findings to feed directly into risk mapping and relocation protocols.
Combining zoning data layers with historical imagery illuminated new insights for Alejandra.
Google Earth helped us anticipate the future by showing real-world development patterns. By observing how the city was evolving, we could predict where it was expanding and identify open spaces available for services. It turned a mountain of abstract geographic data into a clear, visual language that we could actually use to plan effectively.
Alejandra added that previously her team had to design everything from scratch based on laborious searching because they didn’t have really trustworthy databases with layers and critical information available. Now, with Ask Google Earth and data layers, they can choose data layers for themselves directly in the product or even just ask for what they’re looking for. This has reduced the working time considerably. “Something that could have taken weeks or even months can now be done in less than an hour—with prompting and, of course, checking that everything is accurate. Google Earth has now evolved with AI and the ability to visualize data layers that are ready to put to work. Some of them are free, and some require payment, but they are definitely worth it”, shared Alejadra.
The Impact: Time savings and better outcomes for citizens
Grounding her work in the reality of Google Earth’s imagery reshaped Alejandra's planning process and saved time. She ensured that critical infrastructure investments like water and sanitation were directed to the right locations. As metropolitan infrastructure projects can take decades to plan, finance, and execute, the ability to improve decision-making through smart planning methodologies represents a critical opportunity. By combining territorial data, predictive analysis, infrastructure mapping, and integrated urban management approaches, metropolitan regions can identify priorities earlier, reduce inefficiencies, and optimize the use of public resources before major investments are committed.
For example, in the case of Alejandra’s work in Buenos Aires, smart planning methodologies could support more coordinated territorial management, benefiting a population of several million inhabitants across thousands of square kilometers.
By improving project prioritization, reducing overlaps, accelerating administrative processes, and enabling evidence-based allocation of resources, our approach helped avoid significant unnecessary bureaucratic and operational costs while increasing the effectiveness, resilience, and long-term impact of metropolitan infrastructure investments.
Looking ahead, Alejandra is excited about how Google Earth’s new data layers, analysis tools, and image generation will fundamentally change planning workflows. By solving the persistent bottleneck of finding and organizing data, and grounding that data in iconic imagery, planners can make better-informed decisions on a shared canvas. Whether she's leading infrastructure strategy, developing AI-enabled planning tools, or applying human-centered design to complex public-sector problems, her focus remains the same: helping governments and organizations make better decisions by turning complex data into practical, actionable insights that improve how cities grow and serve their communities.
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