Snap a Point to a Line

This example illustrates a common spatial operation: moving or snapping a point to lie on a nearby line. For instance, you might use this approach to align point locations from a mobile device with a map of roads. The JTS library is used for this sort of task day in and day out.

What you will learn:

  • Use of a spatial index to cache features in memory and search efficiently.

  • Going beyond the familiar JTS Geometry class methods and making direct use of other classes.

Related material:

To begin, we prompt the user for a shapefile containing line features and connect to it:

import java.util.List;
import java.util.Random;
import org.geotools.api.feature.Feature;
import org.geotools.api.feature.FeatureVisitor;
import org.geotools.api.feature.simple.SimpleFeature;
import org.geotools.feature.FeatureCollection;
import org.geotools.geometry.jts.ReferencedEnvelope;
import org.geotools.util.SuppressFBWarnings;
import org.locationtech.jts.geom.Coordinate;
import org.locationtech.jts.geom.Envelope;
import org.locationtech.jts.geom.Geometry;
import org.locationtech.jts.geom.LineString;
import org.locationtech.jts.geom.MultiLineString;
import org.locationtech.jts.index.SpatialIndex;
import org.locationtech.jts.index.strtree.STRtree;
import org.locationtech.jts.linearref.LinearLocation;
import org.locationtech.jts.linearref.LocationIndexedLine;

public class SnapToLine {

    public static void main(String[] args) throws Exception {

         * Open a shapefile. You should choose one with line features
         * (LineString or MultiLineString geometry)
        File file = JFileDataStoreChooser.showOpenFile("shp", null);
        if (file == null) {

        FileDataStore store = FileDataStoreFinder.getDataStore(file);
        FeatureSource source = store.getFeatureSource();

        // Check that we have line features
        Class<?> geomBinding = source.getSchema().getGeometryDescriptor().getType().getBinding();
        boolean isLine =
                geomBinding != null
                        && (LineString.class.isAssignableFrom(geomBinding)
                                || MultiLineString.class.isAssignableFrom(geomBinding));

        if (!isLine) {
            System.out.println("This example needs a shapefile with line features");

You might be used to working with shapefiles as a streaming data source, i.e. reading features from disk as required. Here we optimize things by extracting the line geometries from the features and caching them in a JTS SpatialIndex object. This gives us speed in two ways: we have the lines in memory and can search for them efficiently by location:

        final SpatialIndex index = new STRtree();
        FeatureCollection features = source.getFeatures();
        System.out.println("Slurping in features ...");
                new FeatureVisitor() {

                    public void visit(Feature feature) {
                        SimpleFeature simpleFeature = (SimpleFeature) feature;
                        Geometry geom = (MultiLineString) simpleFeature.getDefaultGeometry();
                        // Just in case: check for  null or empty geometry
                        if (geom != null) {
                            Envelope env = geom.getEnvelopeInternal();
                            if (!env.isNull()) {
                                index.insert(env, new LocationIndexedLine(geom));
                new NullProgressListener());

Notice that we wrapped each feature’s line geometry in a JTS LocationIndexedLine object which we will use to find the point on a line closest to a reference point. We could have loaded the lines directly into the spatial index, but this way we will avoid wrapping each line every time it is tested against a point.

Now let’s make some pretend point data:

         * For test data, we generate a large number of points placed randomly
         * within the bounding rectangle of the features.
        final int NUM_POINTS = 10000;
        ReferencedEnvelope bounds = features.getBounds();
        Coordinate[] points = new Coordinate[NUM_POINTS];
        Random rand = new Random(file.hashCode());
        for (int i = 0; i < NUM_POINTS; i++) {
            points[i] =
                    new Coordinate(
                            bounds.getMinX() + rand.nextDouble() * bounds.getWidth(),
                            bounds.getMinY() + rand.nextDouble() * bounds.getHeight());

At last we are ready to snap points. We create a search envelope of fixed size around each point and use this to query the lines in the spatial index.

In case your shapefile is large, we’ll set a time limit on how long snapping continues:

         * We defined the maximum distance that a line can be from a point
         * to be a candidate for snapping (1% of the width of the feature
         * bounds for this example).
        final double MAX_SEARCH_DISTANCE = bounds.getSpan(0) / 100.0;

        // Maximum time to spend running the snapping process (milliseconds)
        final long DURATION = 5000;

        int pointsProcessed = 0;
        int pointsSnapped = 0;
        long elapsedTime = 0;
        long startTime = System.currentTimeMillis();
        while (pointsProcessed < NUM_POINTS
                && (elapsedTime = System.currentTimeMillis() - startTime) < DURATION) {

            // Get point and create search envelope
            Coordinate pt = points[pointsProcessed++];
            Envelope search = new Envelope(pt);

             * Query the spatial index for objects within the search envelope.
             * Note that this just compares the point envelope to the line envelopes
             * so it is possible that the point is actually more distant than
             * MAX_SEARCH_DISTANCE from a line.
            List<LocationIndexedLine> lines = index.query(search);

            // Initialize the minimum distance found to our maximum acceptable
            // distance plus a little bit
            double minDist = MAX_SEARCH_DISTANCE + 1.0e-6;
            Coordinate minDistPoint = null;

            for (LocationIndexedLine line : lines) {
                LinearLocation here = line.project(pt);
                Coordinate point = line.extractPoint(here);
                double dist = point.distance(pt);
                if (dist < minDist) {
                    minDist = dist;
                    minDistPoint = point;

            if (minDistPoint == null) {
                // No line close enough to snap the point to
                System.out.println(pt + "- X");

            } else {
                System.out.printf("%s - snapped by moving %.4f\n", pt.toString(), minDist);

                "Processed %d points (%.2f points per second). \n" + "Snapped %d points.\n\n",
                pointsProcessed, 1000.0 * pointsProcessed / elapsedTime, pointsSnapped);

You can experiment with this code:

  • try some actual roads - using real data makes a difference

  • try using a QuadTree - it is often much slower (but you can add and remove things from a QuadTree at runtime)

  • are you getting wacky results? Check if your geometry.isValid() prior to using it

  • try simplifying the lines prior to creating the LocationIndexedLine - it should be much faster

  • If you are unsure how to do activities listed above consult the Secrets of JTS link provided at the top of the page.