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GeoJSONL to CSV Converter

Convert GeoJSONL (.geojsonl) files to CSV (.csv) right in your browser — free, instant and private. Drop a file below and download the result in seconds. Nothing is uploaded to a server, so your data never leaves your device.

GeoJSONLCSV

Drag & drop your .geojsonl file

or click to browse

100% private — converted in your browser. Files are never uploaded.

How to convert GeoJSONL to CSV

  1. 1

    Add your GeoJSONL file

    Drag and drop your .geojsonl file onto the box above, or click to browse — you can also paste the raw text directly.

  2. 2

    Convert in your browser

    GeoMaps reads the GeoJSONL and rewrites it as CSV locally, on your device. The conversion is instant and your file is never sent anywhere.

  3. 3

    Download your CSV

    Click download to save the converted .csv file, or copy the output text. That's it — no account, no watermark, no limits.

GeoJSONL — also called newline-delimited GeoJSON, NDJSON or GeoJSON Text Sequence (RFC 8142) — writes one GeoJSON feature per line instead of wrapping everything in a single FeatureCollection. That streaming-friendly layout lets tools like Tippecanoe, BigQuery and DuckDB read enormous datasets line by line without loading the whole file into memory. It's the format of choice for large-scale geospatial pipelines.

Need the other direction instead? CSV is spreadsheet rows with latitude / longitude columns. CSV (comma-separated values) is the universal spreadsheet and database interchange format, opened by Excel, Google Sheets, and every data tool. For mapping it carries one record per row with latitude and longitude columns (plus any attributes). It's the simplest way to get tabular location data onto a map, or to pull mapped data back into a spreadsheet for analysis.

CSV is row-based and point-centric: each row needs latitude/longitude columns. Lines and polygons are written to a geometry column as WKT rather than as drawn shapes.

What is GeoJSONL?

.geojsonl

GeoJSONL — also called newline-delimited GeoJSON, NDJSON or GeoJSON Text Sequence (RFC 8142) — writes one GeoJSON feature per line instead of wrapping everything in a single FeatureCollection. That streaming-friendly layout lets tools like Tippecanoe, BigQuery and DuckDB read enormous datasets line by line without loading the whole file into memory. It's the format of choice for large-scale geospatial pipelines.

What is CSV?

.csv

CSV (comma-separated values) is the universal spreadsheet and database interchange format, opened by Excel, Google Sheets, and every data tool. For mapping it carries one record per row with latitude and longitude columns (plus any attributes). It's the simplest way to get tabular location data onto a map, or to pull mapped data back into a spreadsheet for analysis.

GeoJSONL to CSV — FAQ

How do I convert GeoJSONL to CSV?
Upload your .geojsonl file using the converter above (drag & drop or click to browse). GeoMaps converts it to CSV instantly in your browser and gives you a .csv file to download. No software to install and no signup required.
Is the GeoJSONL to CSV converter free?
Yes — it's completely free with no usage limits, watermarks or account needed. We offer it as a free tool from GeoMaps, the platform for turning your data into interactive maps.
Is my data private? Are my files uploaded to a server?
No. The conversion runs entirely in your web browser using JavaScript — your file is never uploaded to any server. Because nothing leaves your device, it's safe for sensitive or confidential data and works even offline once the page has loaded.
Can I convert CSV back to GeoJSONL?
Yes. Use our CSV to GeoJSONL converter for the reverse conversion — every format on GeoMaps converts both ways.
Anything to know about CSV output?
CSV is row-based and point-centric: each row needs latitude/longitude columns. Lines and polygons are written to a geometry column as WKT rather than as drawn shapes.
How large a file can I convert?
Because conversion happens in your browser, the limit is your device's memory rather than a server quota — files up to tens of megabytes convert comfortably on a typical laptop. Very large datasets may be slower depending on your machine.

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