GDAL
GDAL Virtual Format Tutorial

Contents

  1. Introduction
  2. .vrt Format
  3. Overviews
  4. .vrt Descriptions for Raw Files
  5. Programmatic Creation of VRT Datasets
  6. Using Derived Bands (with pixel functions in C/C++)
  7. Using Derived Bands (with pixel functions in Python)
  8. Warped VRT
  9. Pansharpened VRT
  10. Multi-threading issues
  11. Performance considerations

Introduction

The VRT driver is a format driver for GDAL that allows a virtual GDAL dataset to be composed from other GDAL datasets with repositioning, and algorithms potentially applied as well as various kinds of metadata altered or added. VRT descriptions of datasets can be saved in an XML format normally given the extension .vrt.

The VRT format can also describe warping operations and pansharpening operations.

An example of a simple .vrt file referring to a 512x512 dataset with one band loaded from utm.tif might look like this:

<VRTDataset rasterXSize="512" rasterYSize="512">
<GeoTransform>440720.0, 60.0, 0.0, 3751320.0, 0.0, -60.0</GeoTransform>
<VRTRasterBand dataType="Byte" band="1">
<ColorInterp>Gray</ColorInterp>
<SimpleSource>
<SourceFilename relativeToVRT="1">utm.tif</SourceFilename>
<SourceBand>1</SourceBand>
<SrcRect xOff="0" yOff="0" xSize="512" ySize="512"/>
<DstRect xOff="0" yOff="0" xSize="512" ySize="512"/>
</SimpleSource>
</VRTRasterBand>
</VRTDataset>

Many aspects of the VRT file are a direct XML encoding of the GDAL Data Model which should be reviewed for understanding of the semantics of various elements.

VRT files can be produced by translating to VRT format. The resulting file can then be edited to modify mappings, add metadata or other purposes. VRT files can also be produced programmatically by various means.

This tutorial will cover the .vrt file format (suitable for users editing .vrt files), and how .vrt files may be created and manipulated programmatically for developers.

.vrt Format

A XML schema of the GDAL VRT format is available.

Virtual files stored on disk are kept in an XML format with the following elements.

VRTDataset: This is the root element for the whole GDAL dataset. It must have the attributes rasterXSize and rasterYSize describing the width and height of the dataset in pixels. It may have a subClass attributes with values VRTWarpedDataset (Warped VRT) or VRTPansharpenedDataset (Pansharpened VRT). It may have SRS, GeoTransform, GCPList, Metadata, MaskBand and VRTRasterBand subelements.

<VRTDataset rasterXSize="512" rasterYSize="512">

The allowed subelements for VRTDataset are :

Overviews

GDAL can make efficient use of overviews available in the sources that compose the bands when dealing with RasterIO() requests that involve downsampling. But in the general case, the VRT bands themselves will not expose overviews.

Except if (from top priority to lesser priority) :

  1. The Overview element is present in the VRTRasterBand element. See above.
  2. or external .vrt.ovr overviews are built
  3. (starting with GDAL 2.1) if the VRTRasterBand are made of a single SimpleSource or ComplexSource that has overviews. Those "virtual" overviews will be hidden by external .vrt.ovr overviews that might be built later.

.vrt Descriptions for Raw Files

So far we have described how to derive new virtual datasets from existing files supports by GDAL. However, it is also common to need to utilize raw binary raster files for which the regular layout of the data is known but for which no format specific driver exists. This can be accomplished by writing a .vrt file describing the raw file.

For example, the following .vrt describes a raw raster file containing floating point complex pixels in a file called l2p3hhsso.img. The image data starts from the first byte (ImageOffset=0). The byte offset between pixels is 8 (PixelOffset=8), the size of a CFloat32. The byte offset from the start of one line to the start of the next is 9376 bytes (LineOffset=9376) which is the width (1172) times the size of a pixel (8).

<VRTDataset rasterXSize="1172" rasterYSize="1864">
<VRTRasterBand dataType="CFloat32" band="1" subClass="VRTRawRasterBand">
<SourceFilename relativetoVRT="1">l2p3hhsso.img</SourceFilename>
<ImageOffset>0</ImageOffset>
<PixelOffset>8</PixelOffset>
<LineOffset>9376</LineOffset>
<ByteOrder>MSB</ByteOrder>
</VRTRasterBand>
</VRTDataset>

Some things to note are that the VRTRasterBand has a subClass specifier of "VRTRawRasterBand". Also, the VRTRawRasterBand contains a number of previously unseen elements but no "source" information. VRTRawRasterBands may never have sources (i.e. SimpleSource), but should contain the following elements in addition to all the normal "metadata" elements previously described which are still supported.

A few other notes:

Another example, in this case a 400x300 RGB pixel interleaved image.

<VRTDataset rasterXSize="400" rasterYSize="300">
<VRTRasterBand dataType="Byte" band="1" subClass="VRTRawRasterBand">
<ColorInterp>Red</ColorInterp>
<SourceFilename relativetoVRT="1">rgb.raw</SourceFilename>
<ImageOffset>0</ImageOffset>
<PixelOffset>3</PixelOffset>
<LineOffset>1200</LineOffset>
</VRTRasterBand>
<VRTRasterBand dataType="Byte" band="2" subClass="VRTRawRasterBand">
<ColorInterp>Green</ColorInterp>
<SourceFilename relativetoVRT="1">rgb.raw</SourceFilename>
<ImageOffset>1</ImageOffset>
<PixelOffset>3</PixelOffset>
<LineOffset>1200</LineOffset>
</VRTRasterBand>
<VRTRasterBand dataType="Byte" band="3" subClass="VRTRawRasterBand">
<ColorInterp>Blue</ColorInterp>
<SourceFilename relativetoVRT="1">rgb.raw</SourceFilename>
<ImageOffset>2</ImageOffset>
<PixelOffset>3</PixelOffset>
<LineOffset>1200</LineOffset>
</VRTRasterBand>
</VRTDataset>

Programmatic Creation of VRT Datasets

The VRT driver supports several methods of creating VRT datasets. As of GDAL 1.2.0 the vrtdataset.h include file should be installed with the core GDAL include files, allowing direct access to the VRT classes. However, even without that most capabilities remain available through standard GDAL interfaces.

To create a VRT dataset that is a clone of an existing dataset use the CreateCopy() method. For example to clone utm.tif into a wrk.vrt file in C++ the following could be used:

GDALDriver *poDriver = (GDALDriver *) GDALGetDriverByName( "VRT" );
GDALDataset *poSrcDS, *poVRTDS;
poSrcDS = (GDALDataset *) GDALOpenShared( "utm.tif", GA_ReadOnly );
poVRTDS = poDriver->CreateCopy( "wrk.vrt", poSrcDS, FALSE, NULL, NULL, NULL );

Note the use of GDALOpenShared() when opening the source dataset. It is advised to use GDALOpenShared() in this situation so that you are able to release the explicit reference to it before closing the VRT dataset itself. In other words, in the previous example, you could also invert the 2 last lines, whereas if you open the source dataset with GDALOpen(), you'd need to close the VRT dataset before closing the source dataset.

To create a virtual copy of a dataset with some attributes added or changed such as metadata or coordinate system that are often hard to change on other formats, you might do the following. In this case, the virtual dataset is created "in memory" only by virtual of creating it with an empty filename, and then used as a modified source to pass to a CreateCopy() written out in TIFF format.

poVRTDS = poDriver->CreateCopy( "", poSrcDS, FALSE, NULL, NULL, NULL );
poVRTDS->SetMetadataItem( "SourceAgency", "United States Geological Survey");
poVRTDS->SetMetadataItem( "SourceDate", "July 21, 2003" );
poVRTDS->GetRasterBand( 1 )->SetNoDataValue( -999.0 );
GDALDriver *poTIFFDriver = (GDALDriver *) GDALGetDriverByName( "GTiff" );
GDALDataset *poTiffDS;
poTiffDS = poTIFFDriver->CreateCopy( "wrk.tif", poVRTDS, FALSE, NULL, NULL, NULL );
GDALClose((GDALDatasetH) poTiffDS);

In the above example the nodata value is set as -999. You can set the HideNoDataValue element in the VRT dataset's band using SetMetadataItem() on that band.

poVRTDS->GetRasterBand( 1 )->SetMetadataItem( "HideNoDataValue" , "1" );

In this example a virtual dataset is created with the Create() method, and adding bands and sources programmatically, but still via the "generic" API. A special attribute of VRT datasets is that sources can be added to the VRTRasterBand (but not to VRTRawRasterBand) by passing the XML describing the source into SetMetadata() on the special domain target "new_vrt_sources". The domain target "vrt_sources" may also be used, in which case any existing sources will be discarded before adding the new ones. In this example we construct a simple averaging filter source instead of using the simple source.

// construct XML for simple 3x3 average filter kernel source.
const char *pszFilterSourceXML =
"<KernelFilteredSource>"
" <SourceFilename>utm.tif</SourceFilename><SourceBand>1</SourceBand>"
" <Kernel>"
" <Size>3</Size>"
" <Coefs>0.111 0.111 0.111 0.111 0.111 0.111 0.111 0.111 0.111</Coefs>"
" </Kernel>"
"</KernelFilteredSource>";
// Create the virtual dataset.
poVRTDS = poDriver->Create( "", 512, 512, 1, GDT_Byte, NULL );
poVRTDS->GetRasterBand(1)->SetMetadataItem("source_0",pszFilterSourceXML,
"new_vrt_sources");

A more general form of this that will produce a 3x3 average filtered clone of any input datasource might look like the following. In this case we deliberately set the filtered datasource as in the "vrt_sources" domain to override the SimpleSource created by the CreateCopy() method. The fact that we used CreateCopy() ensures that all the other metadata, georeferencing and so forth is preserved from the source dataset ... the only thing we are changing is the data source for each band.

int nBand;
GDALDriver *poDriver = (GDALDriver *) GDALGetDriverByName( "VRT" );
GDALDataset *poSrcDS, *poVRTDS;
poSrcDS = (GDALDataset *) GDALOpenShared( pszSourceFilename, GA_ReadOnly );
poVRTDS = poDriver->CreateCopy( "", poSrcDS, FALSE, NULL, NULL, NULL );
for( nBand = 1; nBand <= poVRTDS->GetRasterCount(); nBand++ )
{
char szFilterSourceXML[10000];
GDALRasterBand *poBand = poVRTDS->GetRasterBand( nBand );
sprintf( szFilterSourceXML,
"<KernelFilteredSource>"
" <SourceFilename>%s</SourceFilename><SourceBand>%d</SourceBand>"
" <Kernel>"
" <Size>3</Size>"
" <Coefs>0.111 0.111 0.111 0.111 0.111 0.111 0.111 0.111 0.111</Coefs>"
" </Kernel>"
"</KernelFilteredSource>",
pszSourceFilename, nBand );
poBand->SetMetadataItem( "source_0", szFilterSourceXML, "vrt_sources" );
}

The VRTDataset class is one of the few dataset implementations that supports the AddBand() method. The options passed to the AddBand() method can be used to control the type of the band created (VRTRasterBand, VRTRawRasterBand, VRTDerivedRasterBand), and in the case of the VRTRawRasterBand to set its various parameters. For standard VRTRasterBand, sources should be specified with the above SetMetadata() / SetMetadataItem() examples.

GDALDriver *poDriver = (GDALDriver *) GDALGetDriverByName( "VRT" );
GDALDataset *poVRTDS;
poVRTDS = poDriver->Create( "out.vrt", 512, 512, 0, GDT_Byte, NULL );
char** papszOptions = NULL;
papszOptions = CSLAddNameValue(papszOptions, "subclass", "VRTRawRasterBand"); // if not specified, default to VRTRasterBand
papszOptions = CSLAddNameValue(papszOptions, "SourceFilename", "src.tif"); // mandatory
papszOptions = CSLAddNameValue(papszOptions, "ImageOffset", "156"); // optional. default = 0
papszOptions = CSLAddNameValue(papszOptions, "PixelOffset", "2"); // optional. default = size of band type
papszOptions = CSLAddNameValue(papszOptions, "LineOffset", "1024"); // optional. default = size of band type * width
papszOptions = CSLAddNameValue(papszOptions, "ByteOrder", "LSB"); // optional. default = machine order
papszOptions = CSLAddNameValue(papszOptions, "relativeToVRT", "true"); // optional. default = false
poVRTDS->AddBand(GDT_Byte, papszOptions);
CSLDestroy(papszOptions);
delete poVRTDS;

Using Derived Bands (with pixel functions in C/C++)

A specialized type of band is a 'derived' band which derives its pixel information from its source bands. With this type of band you must also specify a pixel function, which has the responsibility of generating the output raster. Pixel functions are created by an application and then registered with GDAL using a unique key.

Using derived bands you can create VRT datasets that manipulate bands on the fly without having to create new band files on disk. For example, you might want to generate a band using four source bands from a nine band input dataset (x0, x3, x4, and x8):

band_value = sqrt((x3*x3+x4*x4)/(x0*x8));

You could write the pixel function to compute this value and then register it with GDAL with the name "MyFirstFunction". Then, the following VRT XML could be used to display this derived band:

<VRTDataset rasterXSize="1000" rasterYSize="1000">
<VRTRasterBand dataType="Float32" band="1" subClass="VRTDerivedRasterBand">
<Description>Magnitude</Description>
<PixelFunctionType>MyFirstFunction</PixelFunctionType>
<SimpleSource>
<SourceFilename relativeToVRT="1">nine_band.dat</SourceFilename>
<SourceBand>1</SourceBand>
<SrcRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
<DstRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
</SimpleSource>
<SimpleSource>
<SourceFilename relativeToVRT="1">nine_band.dat</SourceFilename>
<SourceBand>4</SourceBand>
<SrcRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
<DstRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
</SimpleSource>
<SimpleSource>
<SourceFilename relativeToVRT="1">nine_band.dat</SourceFilename>
<SourceBand>5</SourceBand>
<SrcRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
<DstRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
</SimpleSource>
<SimpleSource>
<SourceFilename relativeToVRT="1">nine_band.dat</SourceFilename>
<SourceBand>9</SourceBand>
<SrcRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
<DstRect xOff="0" yOff="0" xSize="1000" ySize="1000"/>
</SimpleSource>
</VRTRasterBand>
</VRTDataset>

In addition to the subclass specification (VRTDerivedRasterBand) and the PixelFunctionType value, there is another new parameter that can come in handy: SourceTransferType. Typically the source rasters are obtained using the data type of the derived band. There might be times, however, when you want the pixel function to have access to higher resolution source data than the data type being generated. For example, you might have a derived band of type "Float", which takes a single source of type "CFloat32" or "CFloat64", and returns the imaginary portion. To accomplish this, set the SourceTransferType to "CFloat64". Otherwise the source would be converted to "Float" prior to calling the pixel function, and the imaginary portion would be lost.

<VRTDataset rasterXSize="1000" rasterYSize="1000">
<VRTRasterBand dataType="Float32" band="1" subClass="VRTDerivedRasterBand">
<Description>Magnitude</Description>
<PixelFunctionType>MyFirstFunction</PixelFunctionType>
<SourceTransferType>CFloat64</SourceTransferType>
...

Default Pixel Functions

Starting with GDAL 2.2, GDAL provides a set of default pixel functions that can be used without writing new code:

Writing Pixel Functions

To register this function with GDAL (prior to accessing any VRT datasets with derived bands that use this function), an application calls GDALAddDerivedBandPixelFunc with a key and a GDALDerivedPixelFunc:

GDALAddDerivedBandPixelFunc("MyFirstFunction", TestFunction);

A good time to do this is at the beginning of an application when the GDAL drivers are registered.

GDALDerivedPixelFunc is defined with a signature similar to IRasterIO:

Parameters
papoSourcesA pointer to packed rasters; one per source. The datatype of all will be the same, specified in the eSrcType parameter.
nSourcesThe number of source rasters.
pDataThe buffer into which the data should be read, or from which it should be written. This buffer must contain at least nBufXSize * nBufYSize words of type eBufType. It is organized in left to right, top to bottom pixel order. Spacing is controlled by the nPixelSpace, and nLineSpace parameters.
nBufXSizeThe width of the buffer image into which the desired region is to be read, or from which it is to be written.
nBufYSizeThe height of the buffer image into which the desired region is to be read, or from which it is to be written.
eSrcTypeThe type of the pixel values in the papoSources raster array.
eBufTypeThe type of the pixel values that the pixel function must generate in the pData data buffer.
nPixelSpaceThe byte offset from the start of one pixel value in pData to the start of the next pixel value within a scanline. If defaulted (0) the size of the datatype eBufType is used.
nLineSpaceThe byte offset from the start of one scanline in pData to the start of the next.
Returns
CE_Failure on failure, otherwise CE_None.
typedef CPLErr
(*GDALDerivedPixelFunc)(void **papoSources, int nSources, void *pData,
int nXSize, int nYSize,
GDALDataType eSrcType, GDALDataType eBufType,
int nPixelSpace, int nLineSpace);

The following is an implementation of the pixel function:

#include "gdal.h"
CPLErr TestFunction(void **papoSources, int nSources, void *pData,
int nXSize, int nYSize,
GDALDataType eSrcType, GDALDataType eBufType,
int nPixelSpace, int nLineSpace)
{
int ii, iLine, iCol;
double pix_val;
double x0, x3, x4, x8;
// ---- Init ----
if (nSources != 4) return CE_Failure;
// ---- Set pixels ----
for( iLine = 0; iLine < nYSize; iLine++ )
{
for( iCol = 0; iCol < nXSize; iCol++ )
{
ii = iLine * nXSize + iCol;
/* Source raster pixels may be obtained with SRCVAL macro */
x0 = SRCVAL(papoSources[0], eSrcType, ii);
x3 = SRCVAL(papoSources[1], eSrcType, ii);
x4 = SRCVAL(papoSources[2], eSrcType, ii);
x8 = SRCVAL(papoSources[3], eSrcType, ii);
pix_val = sqrt((x3*x3+x4*x4)/(x0*x8));
GDALCopyWords(&pix_val, GDT_Float64, 0,
((GByte *)pData) + nLineSpace * iLine + iCol * nPixelSpace,
eBufType, nPixelSpace, 1);
}
}
// ---- Return success ----
return CE_None;
}

Using Derived Bands (with pixel functions in Python)

Starting with GDAL 2.2, in addition to pixel functions written in C/C++ as documented in the Using Derived Bands (with pixel functions in C/C++) section, it is possible to use pixel functions written in Python. Both CPython and NumPy are requirements at run-time.

The subelements for VRTRasterBand (whose subclass specification must be set to VRTDerivedRasterBand) are :

The signature of the Python pixel function must have the following arguments:

  1. in_ar: list of input NumPy arrays (one NumPy array for each source)
  2. out_ar: output NumPy array to fill. The array is initialized at the right dimensions and with the VRTRasterBand.dataType.
  3. xoff: pixel offset to the top left corner of the accessed region of the band. Generally not needed except if the processing depends on the pixel position in the raster.
  4. yoff line offset to the top left corner of the accessed region of the band. Generally not needed.
  5. xsize: width of the region of the accessed region of the band. Can be used together with out_ar.shape[1] to determine the horizontal resampling ratio of the request.
  6. ysize: height of the region of the accessed region of the band. Can be used together with out_ar.shape[0] to determine the vertical resampling ratio of the request.
  7. raster_xsize: total with of the raster band. Generally not needed.
  8. raster_ysize: total with of the raster band. Generally not needed.
  9. buf_radius: radius of the buffer (in pixels) added to the left, right, top and bottom of in_ar / out_ar. This is the value of the optional BufferRadius element that can be set so that the original pixel request is extended by a given amount of pixels.
  10. gt: geotransform. Array of 6 double values.
  11. kwargs: dictionary with user arguments defined in PixelFunctionArguments

Examples

Security implications

The ability to run Python code potentially opens the door to many potential vulnerabilities if the user of GDAL may process untrusted datasets. To avoid such issues, by default, execution of Python pixel function will be disabled. The execution policy can be controlled with the GDAL_VRT_ENABLE_PYTHON configuration option, which can accept 3 values:

Linking mechanism to a Python interpreter.

Currently only CPython - 2.6, 2.7 and 3.x - is supported. The GDAL shared object is not explicitly linked at build time to any of the CPython library. When GDAL will need to run Python code, it will first determine if the Python interpreter is loaded in the current process (which is the case if the program is a Python interpreter itself, or if another program, e.g. QGIS, has already loaded the CPython library). Otherwise it will look if the PYTHONSO configuration option is defined. This option can be set to point to the name of the Python library to use, either as a shortname like "libpython2.7.so" if it is accessible through the Linux dynamic loader (so typically in one of the paths in /etc/ld.so.conf or LD_LIBRARY_PATH) or as a full path name like "/usr/lib/x86_64-linux-gnu/libpython2.7.so". The same holds on Windows will shortnames like "python27.dll" if accessible through the PATH or full path names like "c:\python27\python27.dll". If the PYTHONSO configuration option is not defined, it will look for a "python" binary in the directories of the PATH and will try to determine the related shared object (it will retry with "python3" if no "python" has been found). If the above was not successful, then a predefined list of shared objects names will be tried. At the time of writing, the order of versions searched is 2.7, 2.6, 3.4, 3.5, 3.6, 3.3, 3.2. Enabling debug information (CPL_DEBUG=VRT) will show which Python version is used.

Just-in-time compilation

The use of a just-in-time compiler may significantly speed up execution times. Numba has been successfully tested. For better performance, it is recommended to use a offline pixel function so that the just-in-time compiler may cache its compilation.

Given the following mandelbrot.py file :

# Trick for compatibility with and without numba
try:
from numba import jit
#print('Using numba')
g_max_iterations = 100
except:
class jit(object):
def __init__(self, nopython = True, nogil = True):
pass
def __call__(self, f):
return f
#print('Using non-JIT version')
g_max_iterations = 25
# Use a wrapper for the entry point regarding GDAL, since GDAL cannot access
# the jit decorated function with the expected signature.
def mandelbrot(in_ar, out_ar, xoff, yoff, xsize, ysize, raster_xsize,
raster_ysize, r, gt, **kwargs):
mandelbrot_jit(out_ar, xoff, yoff, xsize, ysize, raster_xsize, raster_ysize,
g_max_iterations)
# Will make sure that the code is compiled to pure native code without Python
# fallback.
@jit(nopython=True, nogil=True, cache=True)
def mandelbrot_jit(out_ar, xoff, yoff, xsize, ysize, raster_xsize,
raster_ysize, max_iterations):
ovr_factor_y = float(out_ar.shape[0]) / ysize
ovr_factor_x = float(out_ar.shape[1]) / xsize
for j in range( out_ar.shape[0]):
y0 = 2.0 * (yoff + j / ovr_factor_y) / raster_ysize - 1
for i in range(out_ar.shape[1]):
x0 = 3.5 * (xoff + i / ovr_factor_x) / raster_xsize - 2.5
x = 0.0
y = 0.0
x2 = 0.0
y2 = 0.0
iteration = 0
while x2 + y2 < 4 and iteration < max_iterations:
y = 2*x*y + y0
x = x2 - y2 + x0
x2 = x * x
y2 = y * y
iteration += 1
out_ar[j][i] = iteration * 255 / max_iterations

the following VRT file can be used (to be opened with QGIS for example)

<VRTDataset rasterXSize="100000000" rasterYSize="100000000">
<VRTRasterBand dataType="Byte" band="1" subClass="VRTDerivedRasterBand">
<PixelFunctionLanguage>Python</PixelFunctionLanguage>
<PixelFunctionType>mandelbrot.mandelbrot</PixelFunctionType>
<Metadata>
<MDI key="STATISTICS_MAXIMUM">255</MDI>
<MDI key="STATISTICS_MEAN">127</MDI>
<MDI key="STATISTICS_MINIMUM">0</MDI>
<MDI key="STATISTICS_STDDEV">127</MDI>
</Metadata>
<ColorInterp>Gray</ColorInterp>
<Histograms>
<HistItem>
<HistMin>-0.5</HistMin>
<HistMax>255.5</HistMax>
<BucketCount>256</BucketCount>
<IncludeOutOfRange>0</IncludeOutOfRange>
<Approximate>1</Approximate>
<HistCounts>0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|
0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|
0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|
0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|
0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|
0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|
0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0</HistCounts>
</HistItem>
</Histograms>
</VRTRasterBand>
</VRTDataset>

Warped VRT

A warped VRT is a VRTDataset with subClass="VRTWarpedDataset". It has a GDALWarpOptions element which describe the warping options.

<VRTDataset rasterXSize="20" rasterYSize="20" subClass="VRTWarpedDataset">
<SRS>PROJCS["NAD27 / UTM zone 11N",GEOGCS["NAD27",DATUM["North_American_Datum_1927",SPHEROID["Clarke 1866",6378206.4,294.9786982138982,AUTHORITY["EPSG","7008"]],AUTHORITY["EPSG","6267"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4267"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-117],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","26711"]]</SRS>
<GeoTransform> 4.4072000000000000e+05, 6.0000000000000000e+01, 0.0000000000000000e+00, 3.7513200000000000e+06, 0.0000000000000000e+00, -6.0000000000000000e+01</GeoTransform>
<Metadata>
<MDI key="AREA_OR_POINT">Area</MDI>
</Metadata>
<VRTRasterBand dataType="Byte" band="1" subClass="VRTWarpedRasterBand">
<ColorInterp>Gray</ColorInterp>
</VRTRasterBand>
<BlockXSize>20</BlockXSize>
<BlockYSize>20</BlockYSize>
<WarpMemoryLimit>6.71089e+07</WarpMemoryLimit>
<ResampleAlg>NearestNeighbour</ResampleAlg>
<WorkingDataType>Byte</WorkingDataType>
<Option name="INIT_DEST">0</Option>
<SourceDataset relativeToVRT="1">byte.vrt</SourceDataset>
<Transformer>
<ApproxTransformer>
<MaxError>0.125</MaxError>
<BaseTransformer>
<GenImgProjTransformer>
<SrcGeoTransform>440720,60,0,3751320,0,-60</SrcGeoTransform>
<SrcInvGeoTransform>-7345.33333333333303,0.0166666666666666664,0,62522,0,-0.0166666666666666664</SrcInvGeoTransform>
<DstGeoTransform>440720,60,0,3751320,0,-60</DstGeoTransform>
<DstInvGeoTransform>-7345.33333333333303,0.0166666666666666664,0,62522,0,-0.0166666666666666664</DstInvGeoTransform>
</GenImgProjTransformer>
</BaseTransformer>
</ApproxTransformer>
</Transformer>
<BandList>
<BandMapping src="1" dst="1" />
</BandList>
</VRTDataset>

Pansharpened VRT

(Since GDAL 2.1)

A VRT can describe a dataset resulting from a pansharpening operation. The pansharpening VRT combines a panchromatic band with several spectral bands of lower resolution to generate output spectral bands of the same resolution as the panchromatic band.

VRT pansharpening assumes that the panchromatic and spectral bands have the same projection (or no projection). If that is not the case, reprojection must be done in a prior step. Bands might have different geotransform matrices, in which case, by default, the resulting dataset will have as extent the union of all extents.

Currently the only supported pansharpening algorithm is a "weighted" Brovey algorithm. The general principle of this algorithm is that, after resampling the spectral bands to the resolution of the panchromatic band, a pseudo panchromatic intensity is computed from a weighted average of the spectral bands. Then the output value of the spectral band is its input value multiplied by the ratio of the real panchromatic intensity over the pseudo panchromatic intensity.

Corresponding pseudo code:

pseudo_panchro[pixel] = sum(weight[i] * spectral[pixel][i] for i=0 to nb_spectral_bands-1)
ratio = panchro[pixel] / pseudo_panchro[pixel]
for i=0 to nb_spectral_bands-1:
output_value[pixel][i] = input_value[pixel][i] * ratio

A valid pansharpened VRT must declare subClass="VRTPansharpenedDataset" as an attribute of the VRTDataset top element. The VRTDataset element must have a child PansharpeningOptions element. This PansharpeningOptions element must have a PanchroBand child element and one of several SpectralBand elements. PanchroBand and SpectralBand elements must have at least a SourceFilename child element to specify the name of the dataset. They may also have a SourceBand child element to specify the number of the band in the dataset (starting with 1). If not specify, the first band will be assumed.

The SpectralBand element must generally have a dstBand attribute to specify the number of the output band (starting with 1) to which the input spectral band must be mapped. If the attribute is not specified, the spectral band will be taken into account in the computation of the pansharpening, but not exposed as an output band.

Panchromatic and spectral bands should generally come from different datasets, since bands of a GDAL dataset are assumed to have all the same dimensions. Spectral bands themselves can come from one or several datasets. The only constraint is that they have all the same dimensions.

An example of a minimalist working VRT is the following. It will generates a dataset with 3 output bands corresponding to the 3 input spectral bands of multispectral.tif, pansharpened with panchromatic.tif.

<VRTDataset subClass="VRTPansharpenedDataset">
<PansharpeningOptions>
<PanchroBand>
<SourceFilename relativeToVRT="1">panchromatic.tif</SourceFilename>
<SourceBand>1</SourceBand>
</PanchroBand>
<SpectralBand dstBand="1">
<SourceFilename relativeToVRT="1">multispectral.tif</SourceFilename>
<SourceBand>1</SourceBand>
</SpectralBand>
<SpectralBand dstBand="2">
<SourceFilename relativeToVRT="1">multispectral.tif</SourceFilename>
<SourceBand>2</SourceBand>
</SpectralBand>
<SpectralBand dstBand="3">
<SourceFilename relativeToVRT="1">multispectral.tif</SourceFilename>
<SourceBand>3</SourceBand>
</SpectralBand>
</PansharpeningOptions>
</VRTDataset>

In the above example, 3 output pansharpend bands will be created from the 3 declared input spectral bands. The weights will be 1/3. Cubic resampling will be used. The projection and geotransform from the panchromatic band will be reused for the VRT dataset.

It is possible to create more explicit and declarative pansharpened VRT, allowing for example to only output part of the input spectral bands (e.g. only RGB when the input multispectral dataset is RGBNir). It is also possible to add "classic" VRTRasterBands, in addition to the pansharpened bands.

In addition to the above mentioned required PanchroBand and SpectralBand elements, the PansharpeningOptions element may have the following children elements :

The below examples creates a VRT dataset with 4 bands. The first band is the panchromatic band. The 3 following bands are than red, green, blue pansharpened bands computed from a multispectral raster with red, green, blue and near-infrared bands. The near-infrared bands is taken into account for the computation of the pseudo panchromatic intensity, but not bound to an output band.

<VRTDataset rasterXSize="800" rasterYSize="400" subClass="VRTPansharpenedDataset">
<SRS>WGS84</SRS>
<GeoTransform>-180, 0.45, 0, 90, 0, -0.45</GeoTransform>
<Metadata>
<MDI key="DESCRIPTION">Panchromatic band + pan-sharpened red, green and blue bands</MDI>
</Metadata>
<VRTRasterBand dataType="Byte" band="1" >
<SimpleSource>
<SourceFilename relativeToVRT="1">world_pan.tif</SourceFilename>
<SourceBand>1</SourceBand>
</SimpleSource>
</VRTRasterBand>
<VRTRasterBand dataType="Byte" band="2" subClass="VRTPansharpenedRasterBand">
<ColorInterp>Red</ColorInterp>
</VRTRasterBand>
<VRTRasterBand dataType="Byte" band="3" subClass="VRTPansharpenedRasterBand">
<ColorInterp>Green</ColorInterp>
</VRTRasterBand>
<VRTRasterBand dataType="Byte" band="4" subClass="VRTPansharpenedRasterBand">
<ColorInterp>Blue</ColorInterp>
</VRTRasterBand>
<BlockXSize>256</BlockXSize>
<BlockYSize>256</BlockYSize>
<PansharpeningOptions>
<Algorithm>WeightedBrovey</Algorithm>
<AlgorithmOptions>
<Weights>0.25,0.25,0.25,0.25</Weights>
</AlgorithmOptions>
<Resampling>Cubic</Resampling>
<NumThreads>ALL_CPUS</NumThreads>
<BitDepth>8</BitDepth>
<NoData>0</NoData>
<SpatialExtentAdjustment>Union</SpatialExtentAdjustment>
<PanchroBand>
<SourceFilename relativeToVRT="1">world_pan.tif</SourceFilename>
<SourceBand>1</SourceBand>
</PanchroBand>
<SpectralBand dstBand="2">
<SourceFilename relativeToVRT="1">world_rgbnir.tif</SourceFilename>
<SourceBand>1</SourceBand>
</SpectralBand>
<SpectralBand dstBand="3">
<SourceFilename relativeToVRT="1">world_rgbnir.tif</SourceFilename>
<SourceBand>2</SourceBand>
</SpectralBand>
<SpectralBand dstBand="4">
<SourceFilename relativeToVRT="1">world_rgbnir.tif</SourceFilename>
<SourceBand>3</SourceBand>
</SpectralBand>
<SpectralBand> <!-- note the absence of the dstBand attribute, to indicate
that the NIR band is not bound to any output band -->
<SourceFilename relativeToVRT="1">world_rgbnir.tif</SourceFilename>
<SourceBand>4</SourceBand>
</SpectralBand>
</PansharpeningOptions>
</VRTDataset>

Multi-threading issues

The below section applies to GDAL <= 2.2. Starting with GDAL 2.3, the use of VRT datasets is subject to the standard GDAL dataset multi-threaded rules (that is a VRT dataset handle may only be used by a same thread at a time, but you may open several dataset handles on the same VRT file and use them in different threads)

When using VRT datasets in a multi-threading environment, you should be careful to open the VRT dataset by the thread that will use it afterwards. The reason for that is that the VRT dataset uses GDALOpenShared when opening the underlying datasets. So, if you open twice the same VRT dataset by the same thread, both VRT datasets will share the same handles to the underlying datasets.

The shared attribute, added in GDAL 2.0.0, on the SourceFilename indicates whether the dataset should be shared (value is 1) or not (value is 0). The default is 1. If several VRT datasets referring to the same underlying sources are used in a multithreaded context, shared should be set to 0. Alternatively, the VRT_SHARED_SOURCE configuration option can be set to 0 to force non-shared mode.

Performance considerations

A VRT can reference many (hundreds, thousands, or more) datasets. Due to operating system limitations, and for performance at opening time, it is not reasonable/possible to open them all at the same time. GDAL has a "pool" of datasets opened by VRT files whose maximum limit is 100 by default. When it needs to access a dataset referenced by a VRT, it checks if it is already in the pool of open datasets. If not, when the pool has reached its limit, it closes the least recently used dataset to be able to open the new one. This maximum limit of the pool can be increased by setting the GDAL_MAX_DATASET_POOL_SIZE configuration option to a bigger value. Note that a typical user process on Linux is limited to 1024 simultaneously opened files, and you should let some margin for shared libraries, etc... As of GDAL 2.0, gdal_translate and gdalwarp, by default, increase the pool size to 450.


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