Question 1

Spatial4j vs JTS: which one should I use?

Accepted Answer

Use Spatial4j if you need geodesic circles or dateline-wrap support for shapes, as it fills gaps JTS lacks. However, for complex Euclidean geometry without geodesic requirements, JTS might be more robust due to its wider shape support and maturity.

Question 2

How to calculate distance between two points in Spatial4j?

Accepted Answer

Use the SpatialContext facade, such as SpatialContext.GEO, which provides distance methods. You can choose from three great-circle calculators: Law of Cosines, Haversine, or Vincenty, with Vincenty being most accurate but slower.

Question 3

Can Spatial4j parse GeoJSON files?

Accepted Answer

Yes, Spatial4j supports reading GeoJSON, but it requires the optional Noggit dependency for parsing. Writing GeoJSON does not need Noggit, so ensure you add the dependency if parsing is needed in your project.

Question 4

What's the best way to serialize shapes to JSON with Spatial4j?

Accepted Answer

Integrate with Jackson-databind using Spatial4j's built-in support. Configure a SpatialContext and use the provided serializers to easily convert shapes to and from JSON format, as mentioned in the Formats section.

Question 5

Does Spatial4j work well with Apache Lucene?

Accepted Answer

Yes, Spatial4j is optimized for spatial indexing and search applications like those in Lucene/Solr, with features like efficient distance calculations and shape approximations that are critical for information retrieval performance.

Question 6

Is Vincenty distance calculator worth the performance hit?

Accepted Answer

Vincenty is more accurate for geodesic distances but computationally intensive. For most applications, Haversine provides a good balance of speed and accuracy, while Law of Cosines is faster but less precise over long distances.

Spatial4j

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