Extracting Individual Points from a LineString in BigQuery

When working with geospatial data in BigQuery, you’ll often encounter LineString geometries representing routes, boundaries, or trajectories. Sometimes, you need to access the individual points that make up these LineStrings for detailed analysis or visualization.

In this tutorial, we’ll explore a powerful technique to extract all vertex points from a LineString using BigQuery’s spatial functions and array operations.

The Challenge

LineStrings in BigQuery are stored as single geometry objects, but for many analyses, you need access to the individual vertices. For example, you might want to:

Calculate the distance between consecutive points
Identify sharp turns or unusual segments
Sample points along a route for time-series analysis
Create a heatmap from trajectory density

The Solution: Combining ST_PointN with Array Generation

BigQuery provides the ST_PointN function to extract a specific point from a LineString, but it requires an index. By combining this with array generation, we can extract all points in a single query.

Here’s the technique:

WITH linestring AS (
    SELECT ST_GeogFromText('LINESTRING(1 1, 2 1, 3 2, 3 3)') AS g
)
SELECT 
    idx,
    ST_PointN(g, idx) AS point,
    ST_X(ST_PointN(g, idx)) AS longitude,
    ST_Y(ST_PointN(g, idx)) AS latitude
FROM linestring,
UNNEST(GENERATE_ARRAY(1, ST_NumPoints(g))) AS idx

Breaking Down the Solution

Let’s analyze how this works:

We create a sample LineString using ST_GeogFromText
ST_NumPoints(g) tells us how many points are in the LineString
GENERATE_ARRAY(1, ST_NumPoints(g)) creates an array of indices from 1 to the number of points
UNNEST expands this array into individual rows
ST_PointN(g, idx) extracts each point by its index
We also extract the longitude and latitude using ST_X and ST_Y

Practical Application: Analyzing Point-to-Point Distances

Once you have individual points, you can analyze the distances between consecutive points:

WITH linestring AS (
    SELECT ST_GeogFromText('LINESTRING(1 1, 2 1, 3 2, 3 3)') AS g
),
points AS (
    SELECT 
        idx,
        ST_PointN(g, idx) AS point
    FROM linestring,
    UNNEST(GENERATE_ARRAY(1, ST_NumPoints(g))) AS idx
)
SELECT 
    a.idx AS point_idx,
    b.idx AS next_point_idx,
    ST_Distance(a.point, b.point) AS distance_meters
FROM points a
JOIN points b ON a.idx = b.idx - 1
ORDER BY a.idx

This query calculates the distance between each consecutive pair of points in the LineString, which can be useful for identifying segments with unusual distances.

Advanced Example: Creating Equidistant Points Along a LineString

Sometimes you need points sampled at regular distance intervals rather than the original vertices. Here’s how to generate points every 100 meters along a LineString:

WITH linestring AS (
    SELECT ST_GeogFromText('LINESTRING(1 1, 2 1, 3 2, 3 3)') AS g
),
line_length AS (
    SELECT ST_Length(g) AS total_length
    FROM linestring
),
sample_points AS (
    SELECT 
        GENERATE_ARRAY(0, CAST(FLOOR(total_length/100) AS INT64)) AS point_indices
    FROM line_length
)
SELECT 
    idx AS sample_idx,
    idx*100 AS distance_along_line_meters,
    ST_LineInterpolatePoint(linestring.g, idx*100/line_length.total_length) AS point
FROM linestring, line_length, sample_points, 
UNNEST(sample_points.point_indices) AS idx

Performance Considerations

When working with very large LineStrings or many LineStrings in a table:

Ensure your table is properly partitioned and clustered
Consider materializing the extracted points if you query them frequently
Use column-level partitioning if you’re storing LineStrings with timestamps

Conclusion

Extracting points from LineStrings in BigQuery opens up powerful analytical possibilities. By combining spatial functions with array operations, you can transform complex geospatial data into more accessible formats for analysis and visualization.

This technique is particularly valuable for transportation analysis, movement tracking, and any application where routes or trajectories need to be analyzed at the point level.