Skip to main content
100%

Grid snapping only in SQL!

✓ Published0🌍 Public
Aandrewxhill
Last edited Jul 16, 2014
Created on Jul 16, 2014

This example demonstrates how to snap a hand-drawn path to a street grid using only SQL and PostGIS spatial functions. It takes an input line geometry, finds the nearest high-order road segments from New York OpenStreetMap data, and iteratively interpolates points along those roads to create a new, grid-aligned linestring. The process uses `ST_PointN`, `ST_Line_Interpolate_Point`, `line_locate_point`, and the `ORDER BY <->` operator for nearest-neighbor queries, building the snapped result by alternating between forward and reverse passes.

AI-generated description

Similar vizzes

Loading thumbnail…

Longer single line text

This example uses PostGIS’s ST_GeometryFromText function to load a single LINESTRING of GPS track points and render it as a path. The line is drawn from over two hundred coordinate pairs tracing a route through southern Idaho, with the SQL query creating the geometric line feature. The visualization highlights how raw coordinate data can be transformed into a continuous geographic path, emphasizing the shape and direction of the route. The author, andrewxhill, sourced this from a gist, demonstrating a minimal SQL approach to spatial data handling.

Aandrewxhill
70% match
Loading thumbnail…

PlpgSQL to cross dateline when drawing two points

This example demonstrates a PostGIS/PLpgSQL function that corrects lines crossing the 180-degree antimeridian when drawn on a web Mercator map. It takes two point geometries and constructs a MultiLineString that breaks the crossing segment at the map’s edge, inserting a vertical line at ±20037508.34 to create a continuous visual path. The code uses ST_Transform, ST_MakeLine, and ST_Collect to handle the geometry, and defines a custom aggregate (axh_crossdateline) to process ordered point sequences. The function expects SRID 3857 inputs and returns the adjusted line for seamless rendering.

Aandrewxhill
69% match
Loading thumbnail…

New SQL statement for bigline generation

This SQL snippet constructs a long, detailed line geometry from a sequence of latitude and longitude coordinates using PostGIS. The example demonstrates how to define a complex LINESTRING with over 180 vertices in a single SQL statement, likely for generating a "big line" for mapping or geospatial analysis. The path traced by the coordinates suggests a real-world route or boundary, showcasing the ability to handle dense, high-resolution geographic data directly within a database query.

Aandrewxhill
68% match
Loading thumbnail…

Gist 6114786

This example implements a private torque-style time-series visualization for geospatial data using PostgreSQL and PostGIS. It defines custom SQL functions that aggregate point features into web-Mercator grid cells, grouping counts by time steps and returning arrays of values and dates for rendering. The code uses `ST_SnapToGrid`, `CDB_XYZ_Resolution`, and `CDB_XYZ_Extent` to tile data at a given zoom level, with two variants: a standard response for instantaneous counts and a cumulative response that includes expiration dates for each cell. A metadata function returns the spatial bounds and time range from the source table, supporting both timestamped and numeric columns.

Aandrewxhill
67% match
Loading thumbnail…

CartoDB SQL tricks: Various things that as a SQL-newbie I had to search for >10 minutes to find answers for.

This example demonstrates a collection of SQL recipes for solving common spatial data problems in CartoDB, ranging from merging neighboring county polygons with ST_Union to creating great circle lines via ST_MakeLine and ST_Segmentize. It shows practical techniques like updating geometries with conditional CASE statements, extracting coordinates with ST_X and ST_Y, stripping HTML tags using regexp_replace, and formatting zip codes with to_char. The code also covers performance strategies for large updates and querying spatial relationships with st_contains. Each snippet targets PostGIS functions within the CartoDB platform, emphasizing data preparation and geometric transformations.

Aandrewbt
65% match
Loading thumbnail…

SQL for building a dynamic topo

This example builds a dynamic topographic map from traffic data by buffering and dissolving point geometries into nested contour layers. It first generates a series of buffer rings around each data point, scales the car counts across nine distance levels, and then unions those buffers into isolines representing traffic intensity. The SQL query uses PostGIS functions like `ST_Transform`, `ST_Buffer`, and `ST_Union`, while a second pass outputs the original points. The result combines colored topo bands and overlaid points, with the visualization likely rendered using a web-mapping library that consumes the `the_geom_webmercator` geometries.

Aandrewxhill
63% match
Loading thumbnail…

Create an equal area grid over a buffer of points

This example visualizes a rectangular grid of points covering a 50-kilometer buffer around input locations, with each point representing the centroid of a grid cell in an equal-area projection. The SQL query first buffers the original NAD83 geometries, then unions and reprojects them into the Lambert equal-area projection (SRID 97314) to create an envelope, and finally generates a 1000-by-1000-meter grid using CartoDB’s `CDB_RectangleGrid` function. Each cell’s centroid is reprojected back to WGS84 (SRID 4326) for display, ensuring spatially uniform sampling across the buffered area.

Aandrewxhill
63% match
Loading thumbnail…

parenthesis enclosed NYC open data lat/lon to the_geom

A SQL snippet converts NYC Open Data latitude/longitude coordinates stored as parenthesized text in a column into the `the_geom` geometry field for PostGIS. The example shows how to parse a string like `(lat, lon)` by stripping parentheses, splitting on commas, and reordering the values into `ST_MakePoint` before applying `ST_SetSRID` with EPSG:4326. This enables spatial queries and map rendering from raw tabular coordinate data. The command targets a placeholder table and column, making it adaptable to any dataset with similar text-encoded points.

Aandrewxhill
63% match