NAME

gdal_grid - Creates regular grid from the scattered data.

SYNOPSIS

gdal_grid [--help] [--help-general]
          [-ot {Byte/Int16/UInt16/UInt32/Int32/Float32/Float64/
          CInt16/CInt32/CFloat32/CFloat64}]
          [-oo <NAME>=<VALUE>]...
          [-of <format>] [-co <NAME>=<VALUE>]...
          [-zfield <field_name>] [-z_increase <increase_value>] [-z_multiply <multiply_value>]
          [-a_srs <srs_def>] [-spat <xmin> <ymin> <xmax> <ymax>]
          [-clipsrc <xmin> <ymin> <xmax> <ymax>|<WKT>|<datasource>|spat_extent]
          [-clipsrcsql <sql_statement>] [-clipsrclayer <layer>]
          [-clipsrcwhere <expression>]
          [-l <layername>]... [-where <expression>] [-sql <select_statement>]
          [-txe <xmin> <xmax>] [-tye <ymin> <ymax>] [-tr <xres> <yres>] [-outsize <xsize> <ysize>]
          [-a {<algorithm>[[:<parameter1>=<value1>]...]}] [-q]
          <src_datasource> <dst_filename>

DESCRIPTION

This program creates a regular grid (raster) from the scattered data read from the OGR datasource. Input data will be interpolated to fill grid nodes with values, you can choose from various interpolation methods.

It is possible to set the GDAL_NUM_THREADS configuration option to parallelize the processing. The value to specify is the number of worker threads, or ALL_CPUS to use all the cores/CPUs of the computer.

If not set then a default type is used, which might not be supported by the relevant driver, causing a error.

INTERPOLATION ALGORITHMS

There are a number of interpolation algorithms to choose from.

More details about them can also be found in GDAL Grid Tutorial

DATA METRICS

Besides the interpolation functionality gdal_grid can be used to compute some data metrics using the specified window and output grid geometry. These metrics are:

All the metrics have the same set of options:

When min_points_per_quadrant or max_points_per_quadrant is specified, the search will start with the closest point to the point being interpolated from the first quadrant, then the closest point to the point being interpolated from the second quadrant, etc. up to the 4th quadrant, and will continue with the next closest point in the first quadrant, etc. until max_points and/or max_points_per_quadrant thresholds are reached.

READING COMMA SEPARATED VALUES

Often you have a text file with a list of comma separated XYZ values to work with (so called CSV file). You can easily use that kind of data source in gdal_grid. All you need is to create a virtual dataset header (VRT) for your CSV file and use it as an input datasource for gdal_grid. You can find details on the VRT format on the VRT -- Virtual Format description page.

Here is a small example. Let's say we have a CSV file called dem.csv containing

Easting,Northing,Elevation
86943.4,891957,139.13
87124.3,892075,135.01
86962.4,892321,182.04
87077.6,891995,135.01
...

For the above data we will create a dem.vrt header with the following content:

<OGRVRTDataSource>
    <OGRVRTLayer name="dem">
        <SrcDataSource>dem.csv</SrcDataSource>
        <GeometryType>wkbPoint</GeometryType>
        <GeometryField encoding="PointFromColumns" x="Easting" y="Northing" z="Elevation"/>
    </OGRVRTLayer>
</OGRVRTDataSource>

This description specifies so called 2.5D geometry with three coordinates X, Y and Z. The Z value will be used for interpolation. Now you can use dem.vrt with all OGR programs (start with ogrinfo to test that everything works fine). The datasource will contain a single layer called "dem" filled with point features constructed from values in the CSV file. Using this technique you can handle CSV files with more than three columns, switch columns, etc. OK, now the final step:

gdal_grid dem.vrt demv.tif

Or, if we do not wish to use a VRT file:

gdal_grid -l dem -oo X_POSSIBLE_NAMES=Easting \
-oo Y_POSSIBLE_NAMES=Northing -zfield Elevation dem.csv dem.tif

If your CSV file does not contain column headers then it can be handled in the VRT file in the following way:

<GeometryField encoding="PointFromColumns" x="field_1" y="field_2" z="field_3"/>

The Comma Separated Value (.csv) description page contains details on CSV format supported by GDAL/OGR.

CREATING MULTIBAND FILES

Creating multiband files is not directly possible with gdal_grid. One might use gdal_grid multiple times to create one band per file, and then use gdalbuildvrt -separate and then gdal_translate:

gdal_grid ... 1.tif; gdal_grid ... 2.tif; gdal_grid ... 3.tif
gdalbuildvrt -separate 123.vrt 1.tif 2.tif 3.tif
gdal_translate 123.vrt 123.tif

Or just gdal_merge.py, to combine the one-band files into a single one:

gdal_grid ... a.tif; gdal_grid ... b.tif; gdal_grid ... c.tif
gdal_merge.py -separate a.tif b.tif c.tif -o d.tif

C API

This utility is also callable from C with GDALGrid().

EXAMPLES

The following would create raster TIFF file from VRT datasource described in Reading comma separated values section using the inverse distance to a power method. Values to interpolate will be read from Z value of geometry record.

gdal_grid -a invdist:power=2.0:smoothing=1.0 -txe 85000 89000 -tye 894000 890000 \
    -outsize 400 400 -of GTiff -ot Float64 -l dem dem.vrt dem.tiff

The next command does the same thing as the previous one, but reads values to interpolate from the attribute field specified with -zfield option instead of geometry record. So in this case X and Y coordinates are being taken from geometry and Z is being taken from the "Elevation" field. The GDAL_NUM_THREADS is also set to parallelize the computation.

gdal_grid -zfield "Elevation" -a invdist:power=2.0:smoothing=1.0 -txe 85000 89000 \
    -tye 894000 890000 -outsize 400 400 -of GTiff -ot Float64 -l dem dem.vrt \
    dem.tiff --config GDAL_NUM_THREADS ALL_CPUS

AUTHOR

Andrey Kiselev <dron@ak4719.spb.edu>

COPYRIGHT

1998-2024