raster

This module contains procedures to access and operate with raster data that has been loaded into Snowflake with using Raster Loader.

Learn more about loading raster data as raster tables in Snowflake following this guide.

RASTER_VALUES

RASTER_VALUES(raster_table, vector_query, output_expression, output_table, options)

Description

Returns each pixel and associated values from a output_expression across all bands in a given area of interest of a raster table. The result will include the data from the vector_query as well as from all bands, corresponding to the pixels that intersect each geography.

• raster_table: VARCHAR the qualified table name of the raster table, e.g. 'database.schema.raster_table'.

• vector_query: VARCHAR query containing the area of interest in which to perform the extraction, stored in a column named geom. Additional columns can be included into this query in order to be referenced from the output_expression. It can be NULL, in which case all values stored in the raster table will be extracted.

• output_expression: VARCHAR contains the bands and values to be extracted from the raster. This expression support alias. It does not support aggregations. If you need to use aggregations, use the RASTER_AGG_VALUES function. This expression can be NULL if a pixel column is added using the include_pixel option.

• output_table: VARCHAR where the resulting table will be stored. It must be a VARCHAR of the form 'database.schema.output_table'. The schema must exist and the caller needs to have permissions to create a new table on it. The process will fail if the target table already exists.

• options: VARCHAR a JSON string with additional options:

  Option	Description
  include_pixel	BOOLEAN whether to include the pixel column of the extracted pixel values, in quadbin format. Default is false.

When intersecting large polygons with high-resolution pixels, it may encounter Snowflake's computational and memory limits due to the extensive data generated. To mitigate this, we recommend simplifying polygon geometries, reducing pixel resolution, or partitioning data into manageable subsets. These strategies help manage data efficiently and prevent exceeding Snowflake's quotas.

Result

The result is a table with the corresponding values extracted from the output_expression and, if selected, a pixel column with quadbin indexes.

Examples

Extract band_1 values for raster pixels intersected by each point in the vector query. The output will be stored in a table.

CALL CARTO.CARTO.RASTER_VALUES(
  'database.schema.raster_table',
  '
  SELECT point AS geom
  FROM database.schema.vector_table
  ',
  'band_1',
  'database.schema.output_table',
  NULL
);
-- The table database.schema.output_table will be created
-- with column: band_1 (one value per pixel boundary intersecting each point)

Extract band_1 values for the raster pixels intersected by each polygon in the vector query. The output will be stored in a table.

CALL CARTO.CARTO.RASTER_VALUES(
  'database.schema.raster_table',
  '
  SELECT polygon AS geom
  FROM database.schema.vector_table
  ',
  'band_1',
  'database.schema.output_table',
  NULL
);
-- The table database.schema.output_table will be created
-- with column: band_1 (one value per pixel boundary intersecting each polygon)

Extract band_1, band_2 values wih alias names for the raster pixels intersected by all the geographies in the vector table. It will include the input columns except geom. The output will be stored in a table.

CALL CARTO.CARTO.RASTER_VALUES(
  'database.schema.raster_table',
  'database.schema.vector_table', -- columns: id, name, geom (point)
  '
  band_1 AS alias_1,
  band_2 AS alias_2
  ',
  'database.schema.output_table',
  NULL
);
-- The table database.schema.output_table will be created
-- with columns: id, name, alias_1, alias_2 (one value per pixel boundary intersecting each point)

Extract band_1 values for raster pixels intersected by each point in the vector table. It will include the input columns except geom. The output will be stored in a table. The option "include_pixel" can be set to true to include the pixel value in quadbin format.

CALL CARTO.CARTO.RASTER_VALUES(
  'database.schema.raster_table',
  'database.schema.vector_table', -- columns: id, name, geom (point)
  'band_1',
  'database.schema.output_table',
  '{"include_pixel": true}'
);
-- The table database.schema.output_table will be created
-- with columns: id, name, pixel, band_1 (one value per pixel boundary intersecting each point)

RASTER_AGG_VALUES

RASTER_AGG_VALUES(raster_table, input_query, output_expression, output_table, options)

Description

Returns aggregated values for all pixels intersecting the specified geometries, according to an output_expression.

• raster_table: VARCHAR the qualified table name of the raster table, e.g. 'database.schema.raster_table'.

• input_query: VARCHAR query containing the area of interest in which to perform the aggregation, stored in a column named geom. Additional columns can be included into this query in order to be referenced from the output_expression. It can be NULL, in which case all values stored in the raster table will be used.

• output_expression: VARCHAR contains the aggregated values to be computed from the raster. For extracting non-aggregated values, use the RASTER_VALUES function. This expression cannot be NULL.
• output_table: VARCHAR where the resulting table will be stored. It must be a VARCHAR of the form 'database.schema.output_table'. The schema must exist and the caller needs to have permissions to create a new table on it. The process will fail if the target table already exists.

• options: VARCHAR a JSON string with additional options.

  Option	Description
  groupby_vector_columns	ARRAY group by extra columns included in the vector_query, in addition to the geom column. It does not take effect when vector_query is NULL.
  groupby_raster_columns	ARRAY group by extra columns included in the raster_table, in addition to the geom column.

When intersecting large polygons with high-resolution pixels, it may encounter Snowflake's computational and memory limits due to the extensive data generated. To mitigate this, we recommend simplifying polygon geometries, reducing pixel resolution, or partitioning data into manageable subsets. These strategies help manage data efficiently and prevent exceeding Snowflake's quotas.

**warning**
The aggregation of duplicated geographies may produce unexpected results. If the data provided in the `vector_query` contains duplicated geographies, either clean duplicates previously or use the option `groupby_vector_columns` with an existing unique-id column.

Result

The result is a table with the corresponding aggregated values from the output_expression.

Examples

Aggregate band_1 values for the raster pixels intersected by each polygon in the vector query. The output will be stored in a table.

CALL CARTO.CARTO.RASTER_AGG_VALUES(
  'database.schema.raster_table',
  '
  SELECT polygon AS geom
  FROM database.schema.vector_table
  ',
  'AVG(band_1) AS band_1_avg',
  'database.schema.output_table',
  NULL
);
-- The table database.schema.output_table will be created
-- with column: band_1_avg (one value per pixel boundary intersecting each polygon)

Aggregate band_1, band_2 values wih different aggregations for the raster pixels intersected by all the geographies in the vector table. It will include the input columns except geom. The output will be stored in a table.

CALL CARTO.CARTO.RASTER_AGG_VALUES(
  'database.schema.raster_table',
  'database.schema.vector_table', -- columns: id, name, geom (polygon)
  '
  AVG(band_1) AS band_1_avg,
  SUM(band_2) AS band_2_avg,
  SUM(band_1 + band_2) AS total_sum,
  COUNT(band_1) AS count,
  ',
  'database.schema.output_table',
  NULL
);
-- The table database.schema.output_table will be created
-- with columns: id, name, band_1_avg, band_2_avg, total_sum, count (one value per each pixel center intersecting each polygon)

Aggregate band_1 values for the raster pixels intersected by each polygon in the vector table. It will include the input columns except geom. The option groupby_vector_columns will be set to id (unique-id) to aggregate with duplicated geographies. The output will be stored in a table.

CALL CARTO.CARTO.RASTER_AGG_VALUES(
  'database.schema.raster_table',
  'database.schema.vector_table', -- columns: id, name, geom (polygon)
  'AVG(band_1) AS band_1_avg',
  'database.schema.output_table',
  '{"groupby_vector_columns": ["id"]}'
);
-- The table database.schema.output_table will be created
-- with columns: id, name, band_1_avg (one value per pixel boundary intersecting each polygon, and grouped by id)