Andrii Bidochko

• Updated: February 26, 2026
• 2 min read

How to Download and Analyze Google Street View Coverage Data – A Step‑by‑Step Guide

Unlocking the Full Potential of Google Street View Coverage

Google Street View has become an indispensable tool for mapping, navigation, and visual storytelling. In a recent deep‑dive article by Mark Litwintschik, the author walks readers through the entire workflow for extracting raw coverage data, transforming it into a spatially‑sorted Parquet file, and deriving insightful statistics by year and region.

What the Original Blog Covers

• Downloading the JSON files that list every Street View panorama captured by Google.
• Converting JSON to Parquet using DuckDB with extensions for JSON handling and spatial indexing.
• Sorting the data spatially so that each record is linked to its geographic location.
• Aggregating results to show coverage trends over time and across continents.

Why This Matters for Data Professionals

By turning a massive, unstructured JSON dump into an optimized Parquet dataset, analysts can query Street View coverage in seconds rather than minutes. This opens up new possibilities for:

• Urban planning and infrastructure monitoring.
• Historical analysis of how Google’s mapping footprint has expanded.
• Integrating Street View metadata with other geospatial datasets.

Key Steps Summarized

1. Visit the original article and download the coverage.json file.
2. Use DuckDB’s json_each function to explode the JSON array into rows.
3. Apply the spatialite extension to convert latitude/longitude pairs into geometry objects.
4. Write the result to a Parquet file with COPY (SELECT …) TO 'coverage.parquet' (FORMAT PARQUET);
5. Run simple SQL aggregations to count panoramas per year and per region.

Internal Resources to Help You Get Started

For a deeper dive into DuckDB and Parquet, check out our own guides:

• DuckDB – The Fast In‑Memory Analytics Engine
• Parquet Best Practices for Geospatial Data
• Geospatial Data Workflows on UBOS

By following Mark’s workflow, you can turn a raw Street View dump into a powerful analytical asset in just a few commands.

Ready to explore the world from a new data perspective? Grab the coverage file, run the DuckDB script, and start visualizing the growth of Google’s street‑level imagery today.

Andrii Bidochko

CTO UBOS

Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.