# gdalwarp

Image reprojection and warping utility

## Synopsis

    Usage: gdalwarp [--help] [--long-usage] [--help-general]
                    [--quiet] [-overwrite] [-of <output_format>]
                    [-co <NAME>=<VALUE>]... [-s_srs <srs_def>] [-t_srs <srs_def>]
                    [[-srcalpha]|[-nosrcalpha]]
                    [-dstalpha] [-tr <xres> <yres>|square] [-ts <width> <height>]
                    [-te <xmin> <ymin> <xmax> <ymax>] [-te_srs <srs_def>]
                    [-r near|bilinear|cubic|cubicspline|lanczos|average|rms|mode|min|max|med|q1|q3|sum]
                    [-ot Byte|Int8|[U]Int{16|32|64}|CInt{16|32}|[C]Float{32|64}]
                    <src_dataset_name>... <dst_dataset_name>

    Advanced options:
                    [-wo <NAME>=<VALUE>]... [-multi] [-s_coord_epoch <epoch>]
                    [-t_coord_epoch <epoch>] [-ct <string>]
                    [[-tps]|[-rpc]|[-geoloc]]
                    [-order <1|2|3>] [-refine_gcps <tolerance> [<minimum_gcps>]]
                    [-to <NAME>=<VALUE>]... [-et <err_threshold>]
                    [-wm <memory_in_mb>] [-srcnodata "<value>[ <value>]..."]
                    [-dstnodata "<value>[ <value>]..."] [-tap]
                    [-wt Byte|Int8|[U]Int{16|32|64}|CInt{16|32}|[C]Float{32|64}]
                    [-cutline <datasource>|<WKT>] [-cutline_srs <srs_def>]
                    [-cwhere <expression>]
                    [[-cl <layername>]|[-csql <query>]]
                    [-cblend <distance>] [-crop_to_cutline] [-nomd]
                    [-cvmd <meta_conflict_value>] [-setci] [-oo <NAME>=<VALUE>]...
                    [-doo <NAME>=<VALUE>]... [-ovr <level>|AUTO|AUTO-<n>|NONE]
                    [[-vshift]|[-novshiftgrid]]
                    [-if <format>]... [-srcband <band>]... [-dstband <band>]...

## Description

The gdalwarp utility is an image mosaicing, reprojection and warping utility. The program can reproject to any supported projection, and can also apply GCPs stored with the image if the image is "raw" with control information.

--help

  Show this help message and exit

--help-general

  Gives a brief usage message for the generic GDAL commandline options and exit.

-b <n>

-srcband <n>

  Added in version 3.7.

  Specify an input band number to warp (between 1 and the number of bands of the source dataset).

  This option is used to warp a subset of the input bands. All input bands are used when it is not specified.

  This option may be repeated multiple times to select several input bands. The order in which bands are specified will be the order in which they appear in the output dataset (unless `-dstband` is specified).

  The alpha band should not be specified in the list, as it will be automatically retrieved (unless `-nosrcalpha` is specified).

  The following invocation will warp an input datasets with bands ordered as Blue, Green, Red, NearInfraRed in an output dataset with bands ordered as Red, Green, Blue.

      gdalwarp in_bgrn.tif out_rgb.tif -b 3 -b 2 -b 1 -overwrite

-dstband <n>

  Added in version 3.7.

  Specify the output band number in which to warp. In practice, this option is only useful when updating an existing dataset, e.g to warp one band at at time.

      gdal_create -if in_red.tif -bands 3 out_rgb.tif
      gdalwarp in_red.tif out_rgb.tif -srcband 1 -dstband 1
      gdalwarp in_green.tif out_rgb.tif -srcband 1 -dstband 2
      gdalwarp in_blue.tif out_rgb.tif -srcband 1 -dstband 3

  If `-srcband` is specified, there must be as many occurrences of `-dstband` as there are of `-srcband`.

  The output alpha band should not be specified, as it will be automatically created if the input dataset has an alpha band, or if `-dstalpha` is specified.

  If `-dstband` is not specified, then `-dstband 1 -dstband 2 ... -dstband N` is assumed where N is the number of input bands (specified explicitly either with `-srcband` or implicitly)

-s_srs <srs def>

  Set source spatial reference. If not specified the SRS found in the input dataset will be used.

  The coordinate reference systems that can be passed are anything supported by the OGRSpatialReference.SetFromUserInput() call, which includes EPSG Projected, Geographic or Compound CRS (i.e. EPSG:4296), a well known text (WKT) CRS definition, PROJ.4 declarations, or the name of a .prj file containing a WKT CRS definition.

  If the SRS has an explicit vertical datum that points to a geoid grid, and the input dataset is a single band dataset, a vertical correction will be applied to the values of the dataset.

-s_coord_epoch <epoch>

  Added in version 3.4.

  Assign a coordinate epoch, linked with the source SRS. Useful when the source SRS is a dynamic CRS. Only taken into account if `-s_srs` is used.

  Before PROJ 9.4, `-s_coord_epoch` and `-t_coord_epoch` were mutually exclusive, due to lack of support for transformations between two dynamic CRS.

-t_srs <srs_def>

  Set target spatial reference.

  A source SRS must be available for reprojection to occur. The source SRS will be by default the one found in the input dataset when it is available, or as overridden by the user with `-s_srs`

  The coordinate reference systems that can be passed are anything supported by the OGRSpatialReference.SetFromUserInput() call, which includes EPSG Projected, Geographic or Compound CRS (i.e. EPSG:4296), a well known text (WKT) CRS definition, PROJ.4 declarations, or the name of a .prj file containing a WKT CRS definition.

  If the SRS has an explicit vertical datum that points to a geoid grid, and the input dataset is a single band dataset, a vertical correction will be applied to the values of the dataset.

-t_coord_epoch <epoch>

  Added in version 3.4.

  Assign a coordinate epoch, linked with the target SRS. Useful when the target SRS is a dynamic CRS. Only taken into account if `-t_srs` is used.

  Before PROJ 9.4, `-s_coord_epoch` and `-t_coord_epoch` were mutually exclusive, due to lack of support for transformations between two dynamic CRS.

-ct <string>

  A PROJ string (single step operation or multiple step string starting with +proj=pipeline), a WKT2 string describing a CoordinateOperation, or a urn:ogc:def:coordinateOperation:EPSG::XXXX URN overriding the default transformation from the source to the target CRS.

  It must take into account the axis order of the source and target CRS, that is typically include a `step proj=axisswap order=2,1` at the beginning of the pipeline if the source CRS has northing/easting axis order, and/or at the end of the pipeline if the target CRS has northing/easting axis order.

  When creating a new output file, using `-t_srs` is still necessary to have the target CRS written in the metadata of the output file, but the parameters of the CoordinateOperation will override those of the standard transformation.

  Added in version 3.0.

-to <NAME>=<VALUE>

  Set a transformer option suitable to pass to `GDALCreateGenImgProjTransformer2()`. See `GDALCreateRPCTransformerV2()` for RPC specific options.

-vshift

  Force the use of vertical shift. This option is generally not necessary, except when using an explicit coordinate transformation (`-ct`), and not specifying an explicit source and target SRS.

  Added in version 3.4.

-novshift

  Disable the use of vertical shift when one of the source or target SRS has an explicit vertical datum, and the input dataset is a single band dataset.

  Note

  this option was named `-novshiftgrid` until GDAL 3.3.

  Added in version 3.4.

-order <n>

  order of polynomial used for warping (1 to 3). The default is to select a polynomial order based on the number of GCPs.

-tps

  Force use of thin plate spline transformer based on available GCPs.

-rpc

  Force use of RPCs.

-geoloc

  Force use of Geolocation Arrays.

-et <err_threshold>

  Error threshold for transformation approximation, expressed as a number of source pixels. Defaults to 0.125 pixels unless the `RPC_DEM` transformer option is specified, in which case an exact transformer, i.e. `err_threshold=0`, will be used.

-refine_gcps <tolerance> [<minimum_gcps>]

  Refines the GCPs by automatically eliminating outliers. Outliers will be eliminated until minimum_gcps are left or when no outliers can be detected. The tolerance is passed to adjust when a GCP will be eliminated. Note that GCP refinement only works with polynomial interpolation. The tolerance is in pixel units if no projection is available, otherwise it is in SRS units. If minimum_gcps is not provided, the minimum GCPs according to the polynomial model is used.

-te <xmin> <ymin> <xmax> <ymax>

  Set georeferenced extents of output file to be created (in target SRS by default, or in the SRS specified with `-te_srs`)

-te_srs <srs_def>

  Specifies the SRS in which to interpret the coordinates given with -te. The <srs_def> may be any of the usual GDAL/OGR forms, complete WKT, PROJ.4, EPSG:n or a file containing the WKT. This must not be confused with -t_srs which is the target SRS of the output dataset. `-te_srs` is a convenience e.g. when knowing the output coordinates in a geodetic long/lat SRS, but still wanting a result in a projected coordinate system.

-tr <xres> <yres> | -tr square

  Set output file resolution (in target georeferenced units).

  If not specified (or not deduced from -te and -ts), gdalwarp will, in the general case, generate an output raster with xres=yres.

  Starting with GDAL 3.7, if neither `-tr` nor `-ts` are specified, that no reprojection is involved (including taking into account geolocation arrays or RPC), the resolution of the source file(s) will be preserved (in previous version, an output raster with xres=yres was always generated). It is possible to ask square pixels to still be generated, by specifying `square` as the value for `-tr`.

-tap

  (target aligned pixels) align the coordinates of the extent of the output file to the values of the `-tr`, such that the aligned extent includes the minimum extent (edges lines/columns that are detected as blank, before actual warping, will be removed starting with GDAL 3.8). Alignment means that xmin / resx, ymin / resy, xmax / resx and ymax / resy are integer values. It does not necessarily mean that the output grid aligns with the input grid.

-ts <width> <height>

  Set output file size in pixels and lines. If width or height is set to 0, the other dimension will be guessed from the computed resolution. Note that `-ts` cannot be used with `-tr`

-ovr <level>|AUTO|AUTO-<n>|NONE

  To specify which overview level of source files must be used. The default choice, AUTO, will select the overview level whose resolution is the closest to the target resolution. Specify an integer value (0-based, i.e. 0=1st overview level) to select a particular level. Specify AUTO-n where n is an integer greater or equal to 1, to select an overview level below the AUTO one. Or specify NONE to force the base resolution to be used (can be useful if overviews have been generated with a low quality resampling method, and the warping is done using a higher quality resampling method).

-wo <NAME>=<VALUE>

  Set a warp option. The `GDALWarpOptions::papszWarpOptions` docs show all options. Multiple `-wo` options may be listed.

-ot <type>

  Force the output image bands to have a specific data type supported by the driver, which may be one of the following: `Byte`, `Int8`, `UInt16`, `Int16`, `UInt32`, `Int32`, `UInt64`, `Int64`, `Float32`, `Float64`, `CInt16`, `CInt32`, `CFloat32` or `CFloat64`.

-wt <type>

  Working pixel data type. The data type of pixels in the source image and destination image buffers.

-r <resampling_method>

  Resampling method to use. Available methods are:

  `near`: nearest neighbour resampling (default, fastest algorithm, worst interpolation quality).

  `bilinear`: bilinear resampling.

  `cubic`: cubic resampling.

  `cubicspline`: cubic spline resampling.

  `lanczos`: Lanczos windowed sinc resampling.

  `average`: average resampling, computes the weighted average of all non-NODATA contributing pixels.

  `rms` root mean square / quadratic mean of all non-NODATA contributing pixels (GDAL >= 3.3)

  `mode`: mode resampling, selects the value which appears most often of all the sampled points. In the case of ties, the first value identified as the mode will be selected.

  `max`: maximum resampling, selects the maximum value from all non-NODATA contributing pixels.

  `min`: minimum resampling, selects the minimum value from all non-NODATA contributing pixels.

  `med`: median resampling, selects the median value of all non-NODATA contributing pixels.

  `q1`: first quartile resampling, selects the first quartile value of all non-NODATA contributing pixels.

  `q3`: third quartile resampling, selects the third quartile value of all non-NODATA contributing pixels.

  `sum`: compute the weighted sum of all non-NODATA contributing pixels (since GDAL 3.1)

  Note

  When downsampling is performed (use of `-tr` or `-ts`), existing overviews (either internal/implicit or external ones) on the source image will be used by default by selecting the closest overview to the desired output resolution. The resampling method used to create those overviews is generally not the one you specify through the `-r` option. Some formats, like JPEG2000, can contain significant outliers due to how wavelet compression works. It might thus be useful in those situations to use the `-ovr` `NONE` option to prevent existing overviews to be used.

-srcnodata "<value>[ <value>]..."

  Set nodata masking values for input bands (different values can be supplied for each band). If more than one value is supplied all values should be quoted to keep them together as a single operating system argument. Masked values will not be used in interpolation (details given in Nodata / source validity mask handling)

  Use a value of `None` to ignore intrinsic nodata settings on the source dataset.

  When this option is set to a non-`None` value, it causes the `UNIFIED_SRC_NODATA` warping option (see `GDALWarpOptions::papszWarpOptions`) to be set to `YES`, if it is not explicitly set.

  If `-srcnodata` is not explicitly set, but the source dataset has nodata values, they will be taken into account, with `UNIFIED_SRC_NODATA` at `PARTIAL` by default.

-dstnodata "<value>[ <value>]..."

  Set nodata values for output bands (different values can be supplied for each band). If more than one value is supplied all values should be quoted to keep them together as a single operating system argument. New files will be initialized to this value and if possible the nodata value will be recorded in the output file. Use a value of `None` to ensure that nodata is not defined. If this argument is not used then nodata values will be copied from the source dataset.

-srcalpha

  Force the last band of a source image to be considered as a source alpha band.

-nosrcalpha

  Prevent the alpha band of a source image to be considered as such (it will be warped as a regular band)

-dstalpha

  Create an output alpha band to identify nodata (unset/transparent) pixels.

-wm <memory_in_mb>

  Set the amount of memory that the warp API is allowed to use for caching. Defaults to 64 MB. Since GDAL 3.10, the value can be specified either as a fixed amount of memory (e.g., `-wm 200MB`, `-wm 1G`) or as a percentage of usable RAM (`-wm 10%`). In earlier versions, or if a unit is not specified, the value is interpreted as being in megabytes if the value is less than 10000. For values >=10000, it is interpreted as bytes.

  The warper will total up the memory required to hold the input and output image arrays and any auxiliary masking arrays and if they are larger than the "warp memory" allowed it will subdivide the chunk into smaller chunks and try again.

  If the -wm value is very small there is some extra overhead in doing many small chunks so setting it larger is better but it is a matter of diminishing returns.

-multi

  Use multithreaded warping implementation. Two threads will be used to process chunks of image and perform input/output operation simultaneously. Note that computation is not multithreaded itself. To do that, you can use the `-wo` NUM_THREADS=val/ALL_CPUS option, which can be combined with `-multi`

-q

  Be quiet.

-if <format>

  Format/driver name to be attempted to open the input file(s). It is generally not necessary to specify it, but it can be used to skip automatic driver detection, when it fails to select the appropriate driver. This option can be repeated several times to specify several candidate drivers. Note that it does not force those drivers to open the dataset. In particular, some drivers have requirements on file extensions.

  Added in version 3.2.

-of <format>

  Select the output format. If not specified, the format is guessed from the extension. Use the short format name.

-co <NAME>=<VALUE>

  Many formats have one or more optional creation options that can be used to control particulars about the file created. For instance, the GeoTIFF driver supports creation options to control compression, and whether the file should be tiled.

  The creation options available vary by format driver, and some simple formats have no creation options at all. A list of options supported for a format can be listed with the --format command line option but the documentation for the format is the definitive source of information on driver creation options. See Raster drivers format specific documentation for legal creation options for each format.

-cutline <datasource>|<WKT>

  Enable use of a blend cutline from the name of a vector dataset. Starting with GDAL 3.9, a WKT geometry string starting with POLYGON or MULTIPOLYGON can also be specified.

-cutline_srs <srs_def>

  Added in version 3.9.

  Sets or overrides the SRS of the cutline.

-cl <layername>

  Select the named layer from the cutline datasource.

-cwhere <expression>

  Restrict desired cutline features based on attribute query.

-csql <query>

  Select cutline features using an SQL query instead of from a layer with `-cl`.

-cblend <distance>

  Set a blend distance to use to blend over cutlines (in pixels).

-crop_to_cutline

  Crop the extent of the target dataset to the extent of the cutline.

-overwrite

  Overwrite the target dataset if it already exists. Overwriting must be understood here as deleting and recreating the file from scratch. Note that if this option is not specified and the output file already exists, it will be updated in place.

-nomd

  Do not copy metadata. Without this option, dataset and band metadata (as well as some band information) will be copied from the first source dataset. Items that differ between source datasets will be set to * (see `-cvmd` option).

-cvmd <meta_conflict_value>

  Value to set metadata items that conflict between source datasets (default is "*"). Use "" to remove conflicting items.

-setci

  Set the color interpretation of the bands of the target dataset from the source dataset.

-oo <NAME>=<VALUE>

  Dataset open option (format specific)

-doo <NAME>=<VALUE>

  Output dataset open option (format specific)

<src_dataset_name>

  The source file name(s).

<dst_dataset_name>

  The destination file name.

## Overview

gdalwarp transforms images between different coordinate reference systems and spatial resolutions.

First, gdalwarp must determine the extent and resolution of the output, if these have not been specified using `-te` and `-tr`. These are determined by transforming a sample of points from the source CRS to the destination CRS. Details of the procedure can be found in the documentation for `GDALSuggestedWarpOutput()`. If multiple inputs are provided to gdalwarp, the output extent will be calculated to cover all of them, at a resolution consistent with the highest-resolution input.

Once the dimensions of the output image have been determined, gdalwarp divides the output image into chunks that can be processed independently within the amount of memory specified by `-wm`. gdalwarp then iterates over scanlines in these chunks, and for each output pixel determines a rectangular region of source pixels that contribute to the value of the output pixel. The dimensions of this rectangular region are typically determined by estimating the relative scales of the source and destination raster, but can be manually specified (see documentation of the `XSCALE` parameter in `GDALWarpOptions::papszWarpOptions`). Because the source region is a simple rectangle, it is not possible for an output pixel to be associated with source pixels from both sides of the antimeridian or pole (when transforming from geographic coordinates).

The rectangular region of source pixels is then provided to a function that performs the resampling algorithm selected with `-r`. Depending on the resampling algorithm and relative scales of the source and destination rasters, source pixels may be weighted either according to the approximate fraction of the source pixel that is covered by the destination pixel (e.g., "mean" and "sum" resampling), or by horizontal and vertical Cartesian distances between the center of the source pixel and the center of the target pixel (e.g., bilinear or cubic spline resampling). In the latter case, the relative weight of an individual source pixel is determined by the product of the weights determined for its row and column; the diagonal Cartesian distance is not calculated.

## Multiple input files

When multiple inputs are provided to gdalwarp, they are processed independently in the order they are listed. This may introduce edge effects near the boundaries of the input files, because output pixel values will be derived from the final input only. To avoid this, non-overlapping input files may first be combined into a VRT file (e.g., using gdalbuildvrt). This will allow gdalwarp to use pixels from all inputs when calculating output pixel values.

## Writing to an existing file

Mosaicing into an existing output file is supported if the output file already exists. The spatial extent of the existing file will not be modified to accommodate new data, so you may have to remove it in that case, or use the `-overwrite` option.

Polygon cutlines may be used as a mask to restrict the area of the destination file that may be updated, including blending. If the OGR layer containing the cutline features has no explicit SRS, the cutline features are assumed to be in the SRS of the destination file. When writing to a not yet existing target dataset, its extent will be the one of the original raster unless `-te` or `-crop_to_cutline` are specified.

## Nodata / source validity mask handling

Invalid values in source pixels, either identified through a nodata value metadata set on the source band, a mask band, an alpha band or the use of `-srcnodata` will not be used in interpolation. The details of how it is taken into account depends on the resampling kernel:

- for nearest resampling, for each target pixel, the coordinate of its center is projected back to source coordinates and the source pixel containing that coordinate is identified. If this source pixel is invalid, the target pixel is considered as nodata.

- for bilinear, cubic, cubicspline and lanczos, for each target pixel, the coordinate of its center is projected back to source coordinates and a corresponding source pixel is identified. If this source pixel is invalid, the target pixel is considered as nodata (in this case, valid pixels within the kernel radius would not be considered). Given that those resampling kernels have a non-null kernel radius, this source pixel is just one among other several source pixels, and it might be possible that there are invalid values in those other contributing source pixels. The weights used to take into account those invalid values will be set to zero to ignore them.

- for the other resampling methods, source pixels contributing to the target pixel are ignored if invalid. Only the valid ones are taken into account. If there are none, the target pixel is considered as nodata.

If using `-srcnodata` for multiple images with different invalid values, you need to either (a) pre-process them to have the same to-be-ignored value, or (b) set the nodata flag for each file. Use (b) if you need to preserve the original values for some reason, for example:

    # for this image we want to ignore black (0)
    gdalwarp -srcnodata 0 -dstnodata 0 orig-ignore-black.tif black-nodata.tif

    # and now we want to ignore white (0)
    gdalwarp -srcnodata 255 -dstnodata 255 orig-ignore-white.tif white-nodata.tif

    # and finally ignore a particular blue-grey (RGB 125 125 150)
    gdalwarp -srcnodata "125 125 150" -dstnodata "125 125 150" orig-ignore-grey.tif grey-nodata.tif

    # now we can mosaic them all and not worry about nodata parameters
    gdalwarp black-nodata.tif grey-nodata.tif white-nodata.tif final-mosaic.tif

## Approximate transformation

By default gdalwarp uses a linear approximator for the transformations with a permitted error of 0.125 pixels in the source dataset. The approximator precisely transforms three points per output scanline (the start, middle, and end) from a row and column in the output dataset to a row and column in the source dataset. It then compares a linear approximation of the center point coordinates to the precisely transformed value. If the sum of the horizontal and vertical errors is less than the error threshold then the remaining source points are approximated using linear interpolation between the start and middle point, and between the middle and end point. If the error exceeds the threshold, the scanline is split into two sections and the approximator is recursively applied to each section until the error is less than the threshold or all points have been exactly computed.

The error threshold (in source dataset pixels) can be controlled with the gdalwarp `-et` switch. If you want to compare a true pixel-by-pixel reprojection use `-et 0` which disables this approximator entirely.

## Vertical transformation

While gdalwarp is most commonly used to perform coordinate transformations in the 2D space, it can also perform vertical transformations. Vertical transformations are automatically performed when the following two conditions are met:

- at least one of the source or target CRS has an explicit vertical CRS (as part of a compound CRS) or is a 3D (generally geographic) CRS, and

- the raster has a single band

This mode can also be forced by using the `-vshift` (this is essentially useful when the CRS involved are not explicitly 3D, but a transformation pipeline is specified with `-ct`), or disabled with `-novshift`.

When a vertical transformation is involved, typically a shift value read in a geoid grid will be applied. This may require such grid(s) to be installed, or PROJ networking capabilities to be enabled. Consult PROJ documentation for more details. In addition to a shift, the raster values may be multiplied by a factor to take into account vertical unit changes. In priority, the value returned by `GDALRasterBand::GetUnitType()` is used. The following values are currently recognized: `m`, `metre`, `metre`, `ft`, `foot`, `US survey foot`. If there is no defined unit type at the band level, the vertical unit of the source CRS is used. The vertical unit of the target CRS is also used to determine that conversion factor. The conversion factor may be overridden by setting the `MULT_FACTOR_VERTICAL_SHIFT` warping option with `-wo`. For example `-wo MULT_FACTOR_VERTICAL_SHIFT=1` to disable any vertical unit change.

## Memory usage

Adding RAM will almost certainly increase the speed of gdalwarp. That's not at all the same as saying that it is worth it, or that the speed increase will be significant. Disks are the slowest part of the process. By default gdalwarp won't take much advantage of RAM. Using the flag `-wm 500` will operate on 500MB chunks at a time which is better than the default. The warp memory specified by `-wm` is shared among all threads, so it is especially beneficial to increase this value when running gdalwarp with `-wo NUM_THREADS` (or its equivalent `GDAL_NUM_THREADS`) greater than 1.

Increasing the I/O block cache size may also help. This can be done by setting the `GDAL_CACHEMAX` configuration like:

    gdalwarp --config GDAL_CACHEMAX 500 -wm 500 ...

This uses 500MB of RAM for read/write caching, and 500MB of RAM for working buffers during the warp. Beyond that it is doubtful more memory will make a substantial difference.

Check CPU usage while gdalwarp is running. If it is substantially less than 100% then you know things are IO bound. Otherwise they are CPU bound. The `--debug` option may also provide useful information. For instance, after running the following:

    gdalwarp --debug on abc.tif def.tif

a message like the following will be output:

    GDAL: 224 block reads on 32 block band 1 of utm.tif

In this case it is saying that band 1 of `utm.tif` has 32 blocks, but that 224 block reads were done, implying that lots of data was having to be re-read, presumably because of a limited IO cache. You will also see messages like:

    GDAL: GDALWarpKernel()::GWKNearestNoMasksByte()
    Src=0,0,512x512 Dst=0,0,512x512

The Src/Dst windows show you the "chunk size" being used. In this case my whole image which is very small. If you find things are being broken into a lot of chunks increasing `-wm` may help somewhat.

But far more important than memory are ensuring you are going through an optimized path in the warper. If you ever see it reporting `GDALWarpKernel()::GWKGeneralCase()` you know things will be relatively slow. Basically, the fastest situations are nearest neighbour resampling on 8bit data without nodata or alpha masking in effect.

## Compressed output

In some cases, the output of gdalwarp may be much larger than the original, even if the same compression algorithm is used. By default, gdalwarp operates on chunks that are not necessarily aligned with the boundaries of the blocks/tiles/strips of the output format, so this might cause repeated compression/decompression of partial blocks, leading to lost space in the output format.

The situation can be improved by using the `OPTIMIZE_SIZE` warping option (`-wo OPTIMIZE_SIZE=YES`), but note that depending on the source and target projections, it might also significantly slow down the warping process.

Another possibility is to use gdalwarp without compression and then follow up with gdal_translate with compression:

    gdalwarp infile tempfile.tif ...options...
    gdal_translate tempfile.tif outfile.tif -co compress=lzw ...etc.

Alternatively, you can use a VRT file as the output format of gdalwarp. The VRT file is just an XML file that will be created immediately. The gdal_translate operations will be of course a bit slower as it will do the real warping operation.

    gdalwarp -of VRT infile tempfile.vrt ...options...
    gdal_translate tempfile.vrt outfile.tif -co compress=lzw ...etc.

## Examples

- Basic transformation:

    gdalwarp -t_srs EPSG:4326 input.tif output.tif

- For instance, an eight bit spot scene stored in GeoTIFF with control points mapping the corners to lat/long could be warped to a UTM projection with a command like this:

    gdalwarp -t_srs '+proj=utm +zone=11 +datum=WGS84' -overwrite raw_spot.tif utm11.tif

- For instance, the second channel of an ASTER image stored in HDF with control points mapping the corners to lat/long could be warped to a UTM projection with a command like this:

    gdalwarp -overwrite HDF4_SDS:ASTER_L1B:"pg-PR1B0000-2002031402_100_001":2 \
        pg-PR1B0000-2002031402_100_001_2.tif

- To apply a cutline on a un-georeferenced image and clip from pixel (220,60) to pixel (1160,690):

    gdalwarp -overwrite -to SRC_METHOD=NO_GEOTRANSFORM -to DST_METHOD=NO_GEOTRANSFORM \
        -te 220 60 1160 690 -cutline cutline.csv in.png out.tif

where cutline.csv content is like:

    id,WKT
    1,"POLYGON((....))"

- To transform a DEM from geoid elevations (using EGM96) to WGS84 ellipsoidal heights:

    gdalwarp -overwrite in_dem.tif out_dem.tif -s_srs EPSG:4326+5773 -t_srs EPSG:4979

## C API

This utility is also callable from C with `GDALWarp()`.