Geospatial Data Mapping

Convert JSON, GeoJSON & KML Data

MapForce makes it easy to convert data with visual, drag-and-drop data mapping.

Convert between JSON, KML, and GeoJSON
Map coordinates, placemarks, & geometry data
Schema-based mapping for KML and GeoJSON
Inferring schemas from instances
Turn JSON output from REST APIs into KML

Chained mappings for multi-step conversions
Interactive data mapping debugger
Altova AI automatically generates data mappings
Automate conversions with MapForce Server

Transforming Geospatial Data

MapForce converts geospatial data between JSON, GeoJSON, KML, CSV, Excel, XML, databases, and other formats using visual drag-and-drop mapping. Because KML is XML and GeoJSON is JSON, MapForce works with both natively — mapping coordinates, placemarks, geometry and attribute data field by field. Every conversion is saved as a reusable mapping you can re-run or schedule.

You can even use the optional Altova AI Assistant to generate connections from your source and target structures. Altova AI analyzes the data structures, generates the field connections, suggests transformation functions, and produces an executable project with defined data flows and processing steps, all in the standard MapForce graphical environment. The process is interactive: review each suggested connection and accept or decline it individually, or apply all the changes at once.

MapForce supports converting geospacial data to numerous formats, and not every conversion is lossless. A tool telling you a conversion succeeded isn't the same as a file that still holds everything you started with. Geospatial formats are used for various purposes: KML was built to display things, GeoJSON to exchange them, CSV to tabulate them. Converting between them means deciding what happens to the parts one format carries and another has nowhere to put. Here's what survives each conversion, and what doesn't.

What each geospatial conversion preserves and what it loses
Conversion	Geometry	Attributes	Notes
GeoJSON → KML	Preserved	Preserved as ExtendedData	Styling has no GeoJSON equivalent and must be added in the mapping
KML → GeoJSON	Preserved	ExtendedData → properties	KML styling, icons and folder structure have no GeoJSON equivalent
GeoJSON → CSV	Flattened	Preserved as columns	One row per feature; multi-part geometry must be flattened or serialised
KML → CSV / Excel	Flattened	Preserved as columns	Nested folders collapse; decide row granularity up front
CSV → GeoJSON	Rebuilt from lat/long	Preserved as properties	Column-to-property mapping is explicit; requires valid coordinate columns
CSV → KML	Rebuilt from lat/long	Preserved as ExtendedData	Point geometry is straightforward; lines and polygons need construction
JSON (REST API) → KML	Constructed	Mapped by field	The common “plot my API data on a map” job
GeoJSON / KML → DB	Flattened	Preserved as columns	The repeatable-reporting use case

Converting between GeoJSON and KML preserves geometry and attributes but not presentation. Converting to a tabular format — CSV, Excel, a database table — flattens geometry, and you decide what "one row" means. Converting from tabular back to a geo format rebuilds geometry from coordinate columns.

Common Conversion Jobs

Plot REST API output on a map (JSON → KML)

A fleet-tracking, sensor or asset API returns JSON. Google Earth and most mapping viewers want KML. Load the JSON response as a source, load or infer a KML structure as the target, connect the coordinate fields to <coordinates> and the descriptive fields to <name>, <description> and ExtendedData, and run it.

Get geo data into a spreadsheet people will actually open (GeoJSON / KML → Excel or CSV)

The recipient does not have GIS software and does not want it. Flatten features into rows, choose which properties become columns, and hand over an .xlsx.

Turn a spreadsheet of addresses or coordinates into map data (CSV → GeoJSON / KML)

Latitude and longitude columns become point geometry; the remaining columns become properties or ExtendedData.

Load geo attributes into a database on a schedule

Map GeoJSON or KML features into database tables, then run the mapping weekly against a folder of new files.

Automating GeoJSON and KML Conversion

Unlike free web based tools that ohly support one-off conversions, MapForce lerts you save your data mapping to automate the same conversions on a recurrent basis:

Save the mapping once and re-run it against new files
Process an entire folder of GeoJSON or KML files in one pass
Compile the mapping for MapForce Server and schedule it with FlowForce Server
Chain mappings when the conversion takes more than one step

What MapForce is Not

MapForce is a data mapping tool, not a GIS. It moves geospatial data between formats and systems and does it repeatably. It does not do spatial analysis, rendering, or cartography, and it does not reproject between coordinate reference systems. For buffering, intersections, spatial joins or map production, use QGIS or ArcGIS — and use MapForce for the format conversion and database loading around them. Download a free trial to get started.

FAQ about Converting Geospatial Data in MapForce

Below is a list of commonly asked questions by customers evaluating data conversion tools.

Can MapForce convert JSON to KML?
Yes. Load your JSON file as the source and a KML structure as the target, then connect the fields visually — coordinates to the <coordinates> element, descriptive fields to <name>, <description> and ExtendedData. MapForce infers a schema from your JSON if you do not have one. The mapping is saved as a file, so the same conversion can be re-run on new data.
What is the difference between GeoJSON and KML?
GeoJSON is a JSON format defined by RFC 7946 and built for data interchange between applications and APIs. KML is an XML format originally from Google Earth and built for display. That difference shows up in what each one carries: KML has styling, icons and folder organization that GeoJSON has no equivalent for. Both describe the same geometry types.
Can I open a KML file in Excel?
Not directly. Excel cannot interpret KML’s nested placemark structure, so the data has to be flattened into rows and columns first. That means deciding which placemark attributes become columns. MapForce performs the conversion and saves it as a reusable mapping, so additiona KML files convert the same way every time.
Do I need a GIS licence to convert geospatial files?
No. Format conversion, attribute mapping and loading geo data into a database do not require GIS software.
You need a GIS for spatial analysis and map production — buffering, intersections, cartography. For moving data between formats and systems, a data mapping tool is the lighter and more automatable option.
Is my data uploaded anywhere?
No. MapForce is desktop software installed on your own machine. Files are read from and written to your local disk or network, and nothing is transmitted to Altova or any third party as part of a conversion.
Can I convert a whole folder of files at once?
Yes. MapForce processes batches of files through the same mapping in a single run.
To make it recurring, compile the mapping for MapForce Server and schedule it with FlowForce Server — hourly, nightly, or whenever new files arrive.
What happens to geometry when I convert to CSV?
It gets flattened. CSV has no nested structure, so each feature becomes a row and you decide what a row represents. Point data maps cleanly to latitude and longitude columns. Lines and polygons have multiple coordinate pairs, so you either serialise the coordinate string into one column or expand to one row per vertex.
Can MapForce reproject coordinates between coordinate reference systems?
No. MapForce maps and transforms the values in your data but does not perform geodetic reprojection. If your source and target need different coordinate reference systems, reproject in a GIS tool first, then use MapForce for the format conversion and everything downstream of it.

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