# How to extract location from Strided GeoTIFF raster?
**URL:** https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973
**Category:** Geo
**Created:** [January 20, 2025, 3:43pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973 "2025-01-20T15:43:11Z")
**Posts on this page:** 15
**Page:** 1
### Author:  [@cshen](https://discourse.julialang.org/u/cshen)
#### Post date: [January 20, 2025, 3:43pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/1 "2025-01-20T15:43:11Z")
Hello,
I’ve been trying to read some geotiff datasets. Reading it with `GeoTIFF.jl` results in a `GeoTIFF.GeoTIFFImageIterator{TiffImages.StridedTaggedImage{...}}}`.
This case is not really documented anywhere neither in `GeoTIFF` nor in `TiffImages` so I am unsure on how one is supposed to manipulate it.
This is the full output:
> **GeoTIFF Output**
>
> ```julia
> GeoTIFF.GeoTIFFImageIterator{TiffImages.StridedTaggedImage{UInt64, Matrix{ColorTypes.Gray{Float32}}}, Base.Generator{Vector{TiffImages.IFD{UInt64}}, GeoTIFF.var"#19#20"}}(Any[ColorTypes.Gray{Float32}[Gray{Float32}(-7.5412407f0) Gray{Float32}(-7.70549f0) … Gray{Float32}(-2375.686f0) Gray{Float32}(-2376.507f0); Gray{Float32}(-8.608861f0) Gray{Float32}(-8.773109f0) … Gray{Float32}(-2374.7825f0) Gray{Float32}(-2376.425f0); … ; Gray{Float32}(43.62238f0) Gray{Float32}(45.018497f0) … Gray{Float32}(-1532.1022f0) Gray{Float32}(-1532.1842f0); Gray{Float32}(45.10062f0) Gray{Float32}(46.16824f0) … Gray{Float32}(-1532.1022f0) Gray{Float32}(-1532.1842f0)], ColorTypes.Gray{Float32}[Gray{Float32}(-8.157152f0) Gray{Float32}(-8.732026f0) … Gray{Float32}(-2377.2463f0) Gray{Float32}(-2375.85f0); Gray{Float32}(-10.087005f0) Gray{Float32}(-10.497636f0) … Gray{Float32}(-2377.6362f0) Gray{Float32}(-2375.727f0); … ; Gray{Float32}(43.66345f0) Gray{Float32}(43.499256f0) … Gray{Float32}(-1532.1227f0) Gray{Float32}(-1532.2664f0); Gray{Float32}(44.977463f0) Gray{Float32}(44.669476f0) … Gray{Float32}(-1532.1022f0) Gray{Float32}(-1532.1432f0)], ColorTypes.Gray{Float32}[Gray{Float32}(-9.368346f0) Gray{Float32}(-10.163881f0) … Gray{Float32}(-2377.9905f0) Gray{Float32}(-2376.6147f0); Gray{Float32}(-11.5189495f0) Gray{Float32}(-11.585778f0) … Gray{Float32}(-2375.5735f0) Gray{Float32}(-2376.148f0); … ; Gray{Float32}(43.396812f0) Gray{Float32}(43.288292f0) … Gray{Float32}(-1532.1022f0) Gray{Float32}(-1532.4409f0); Gray{Float32}(44.202477f0) Gray{Float32}(42.852448f0) … Gray{Float32}(-1532.1022f0) Gray{Float32}(-1532.1586f0)], ColorTypes.Gray{Float32}[Gray{Float32}(-10.659187f0) Gray{Float32}(-11.235324f0) … Gray{Float32}(-2376.605f0) Gray{Float32}(-2376.5815f0); Gray{Float32}(-11.747573f0) Gray{Float32}(-11.647497f0) … Gray{Float32}(-2372.8823f0) Gray{Float32}(-2375.5977f0); … ; Gray{Float32}(43.17711f0) Gray{Float32}(43.858208f0) … Gray{Float32}(-1531.9242f0) Gray{Float32}(-1532.7655f0); Gray{Float32}(43.435093f0) Gray{Float32}(44.234425f0) … Gray{Float32}(-1531.7432f0) Gray{Float32}(-1532.2009f0)], ColorTypes.Gray{Float32}[Gray{Float32}(-11.322267f0) Gray{Float32}(-11.448627f0) … Gray{Float32}(-2370.4438f0) Gray{Float32}(-2375.417f0); Gray{Float32}(-11.569621f0) Gray{Float32}(-11.449963f0) … Gray{Float32}(-2366.1345f0) Gray{Float32}(-2371.188f0); … ; Gray{Float32}(44.226574f0) Gray{Float32}(43.909412f0) … Gray{Float32}(-1531.3268f0) Gray{Float32}(-1532.9606f0); Gray{Float32}(43.67626f0) Gray{Float32}(44.4127f0) … Gray{Float32}(-1530.5358f0) Gray{Float32}(-1532.1583f0)], ColorTypes.Gray{Float32}[Gray{Float32}(-11.4475765f0) Gray{Float32}(-11.208084f0) … Gray{Float32}(-2365.8428f0) Gray{Float32}(-2370.7974f0); Gray{Float32}(-11.140415f0) Gray{Float32}(-11.298808f0) … Gray{Float32}(-2354.5442f0) Gray{Float32}(-2360.42f0); … ; Gray{Float32}(43.584164f0) Gray{Float32}(43.737946f0) … Gray{Float32}(-1529.1589f0) Gray{Float32}(-1533.4852f0); Gray{Float32}(44.05623f0) Gray{Float32}(44.68009f0) … Gray{Float32}(-1528.362f0) Gray{Float32}(-1531.7451f0)]], Base.Generator{Vector{TiffImages.IFD{UInt64}}, GeoTIFF.var"#19#20"}(GeoTIFF.var"#19#20"(), TiffImages.IFD{UInt64}[IFD, with tags:
> Tag(IMAGEWIDTH, 16666)
> Tag(IMAGELENGTH, 23333)
> Tag(BITSPERSAMPLE, 32)
> Tag(COMPRESSION, COMPRESSION_ADOBE_DEFLATE)
> Tag(PHOTOMETRIC, 1)
> Tag(SAMPLESPERPIXEL, 1)
> Tag(PLANARCONFIG, 1)
> Tag(PREDICTOR, 1)
> Tag(TILEWIDTH, 512)
> Tag(TILELENGTH, 512)
> Tag(TILEOFFSETS, UInt64[424318014, 424600685, 424898509, 425059230, 425180156, ...])
> Tag(TILEBYTECOUNTS, UInt32[282663, 297816, 160713, 120918, 132183, ...])
> Tag(SAMPLEFORMAT, 3)
> Tag(MODELPIXELSCALE, Float64[0.0002999999999999996, 0.0003000000000000001, 0.0])
> Tag(MODELTIEPOINT, Float64[0.0, 0.0, 0.0, 142.0000611111, -10.000138888905807, ...])
> Tag(GEOKEYDIRECTORY, UInt16[1, 1, 0, 7, 1024, ...])
> Tag(GEODOUBLEPARAMS, Float64[298.257223563, 6.378137e6])
> Tag(GEOASCIIPARAMS, "WGS 84|")
> Tag(GDALNODATA, "-9999"), IFD, with tags:
> Tag(SUBFILETYPE, 1)
> Tag(IMAGEWIDTH, 8333)
> Tag(IMAGELENGTH, 11667)
> Tag(BITSPERSAMPLE, 32)
> Tag(COMPRESSION, COMPRESSION_ADOBE_DEFLATE)
> Tag(PHOTOMETRIC, 1)
> Tag(SAMPLESPERPIXEL, 1)
> Tag(PLANARCONFIG, 1)
> Tag(PREDICTOR, 1)
> Tag(TILEWIDTH, 512)
> Tag(TILELENGTH, 512)
> Tag(TILEOFFSETS, UInt64[110023558, 110944836, 111707108, 112501107, 113298705, ...])
> Tag(TILEBYTECOUNTS, UInt32[921270, 762264, 793991, 797590, 899336, ...])
> Tag(SAMPLEFORMAT, 3)
> Tag(GDALNODATA, "-9999"), IFD, with tags:
> Tag(SUBFILETYPE, 1)
> Tag(IMAGEWIDTH, 4167)
> Tag(IMAGELENGTH, 5834)
> Tag(BITSPERSAMPLE, 32)
> Tag(COMPRESSION, COMPRESSION_ADOBE_DEFLATE)
> Tag(PHOTOMETRIC, 1)
> Tag(SAMPLESPERPIXEL, 1)
> Tag(PLANARCONFIG, 1)
> Tag(PREDICTOR, 1)
> Tag(TILEWIDTH, 512)
> Tag(TILELENGTH, 512)
> Tag(TILEOFFSETS, UInt64[27895940, 28804616, 29687974, 30614470, 31549359, ...])
> Tag(TILEBYTECOUNTS, UInt32[908668, 883350, 926488, 934881, 886679, ...])
> Tag(SAMPLEFORMAT, 3)
> Tag(GDALNODATA, "-9999"), IFD, with tags:
> Tag(SUBFILETYPE, 1)
> Tag(IMAGEWIDTH, 2084)
> Tag(IMAGELENGTH, 2917)
> Tag(BITSPERSAMPLE, 32)
> Tag(COMPRESSION, COMPRESSION_ADOBE_DEFLATE)
> Tag(PHOTOMETRIC, 1)
> Tag(SAMPLESPERPIXEL, 1)
> Tag(PLANARCONFIG, 1)
> Tag(PREDICTOR, 1)
> Tag(TILEWIDTH, 512)
> Tag(TILELENGTH, 512)
> Tag(TILEOFFSETS, UInt64[6818639, 7745514, 8691403, 9563744, 10427788, ...])
> Tag(TILEBYTECOUNTS, UInt32[926867, 945881, 872333, 864036, 64373, ...])
> Tag(SAMPLEFORMAT, 3)
> Tag(GDALNODATA, "-9999"), IFD, with tags:
> Tag(SUBFILETYPE, 1)
> Tag(IMAGEWIDTH, 1042)
> Tag(IMAGELENGTH, 1459)
> Tag(BITSPERSAMPLE, 32)
> Tag(COMPRESSION, COMPRESSION_ADOBE_DEFLATE)
> Tag(PHOTOMETRIC, 1)
> Tag(SAMPLESPERPIXEL, 1)
> Tag(PLANARCONFIG, 1)
> Tag(PREDICTOR, 1)
> Tag(TILEWIDTH, 512)
> Tag(TILELENGTH, 512)
> Tag(TILEOFFSETS, UInt64[1416326, 2378142, 3259160, 3293416, 4254955, ...])
> Tag(TILEBYTECOUNTS, UInt32[961808, 881010, 34248, 961531, 892386, ...])
> Tag(SAMPLEFORMAT, 3)
> Tag(GDALNODATA, "-9999"), IFD, with tags:
> Tag(SUBFILETYPE, 1)
> Tag(IMAGEWIDTH, 521)
> Tag(IMAGELENGTH, 730)
> Tag(BITSPERSAMPLE, 32)
> Tag(COMPRESSION, COMPRESSION_ADOBE_DEFLATE)
> Tag(PHOTOMETRIC, 1)
> Tag(SAMPLESPERPIXEL, 1)
> Tag(PLANARCONFIG, 1)
> Tag(PREDICTOR, 1)
> Tag(TILEWIDTH, 512)
> Tag(TILELENGTH, 512)
> Tag(TILEOFFSETS, UInt64[27052, 977349, 996614, 1407686])
> Tag(TILEBYTECOUNTS, UInt32[950289, 19257, 411064, 8632])
> Tag(SAMPLEFORMAT, 3)
> Tag(GDALNODATA, "-9999")]))
>
> ```
It seems that the dataset contains the same region but at different resolutions.
I can access the raw elevation data, by iterating manually or defining `nth(itr, n) = first(Iterators.drop(itr, n-1))` to access the images, but the extracted images don’t seem to have any metadata.
I would need the spatial information of the dataset, such as resolution, or extents, because I need to extract a cutout, but I can’t seem to find a way to do it with this dataset.
I have also tried with `Rasters.jl` but to no avail.
Am I using the wrong package? is `GeoTIFF.jl` too low level?
---
### Author:  [@Fliks](https://discourse.julialang.org/u/Fliks)
#### Post date: [January 20, 2025, 3:50pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/2 "2025-01-20T15:50:11Z")
What error do you have in Rasters.jl?
I don’t know whether GeoTIFF.jl can handle these overviews but Rasters should be able to handle this format when you load ArchGDAL.jl to load the data using GDAL in the background.
---
### Author:  [@juliohm](https://discourse.julialang.org/u/juliohm)
#### Post date: [January 20, 2025, 3:56pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/3 "2025-01-20T15:56:24Z")
@cshen take a look into the test suite of GeoTIFF.jl. We load these iterators all the time in CoordGridTransforms.jl as part of CoordRefSystems.jl. No need for GDAL.
@eliascarv can share more details if you get stuck.
---
### Author:  [@cshen](https://discourse.julialang.org/u/cshen)
#### Post date: [January 20, 2025, 4:01pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/4 "2025-01-20T16:01:16Z")
> [@Fliks](#):
>
> What error do you have in [Rasters.jl](https://juliaregistries.github.io/General/packages/redirect_to_repo/Rasters)?
with
```julia
imgs = GeoTIFF.load(file)
img = nth(imgs, 1) # 23333×16666 GeoTIFF.GeoTIFFImage{ColorTypes.Gray{Float32}, Matrix{ColorTypes.Gray{Float32}}}
Raster(img, dims=(23333,16666))
```
I have
```julia
ERROR: MethodError: no method matching _format(::Int64, ::Base.OneTo{Int64})
```
But I am most likely not using it correctly, so I don’t know how relevant this error is.
> [@juliohm](#):
>
> @cshen take a look into the test suite of [GeoTIFF.jl](https://juliaregistries.github.io/General/packages/redirect_to_repo/GeoTIFF). We load these iterators all the time in [GridTransforms.jl](https://juliaregistries.github.io/General/packages/redirect_to_repo/GridTransforms) as part of [CoordRefSystems.jl](https://juliaregistries.github.io/General/packages/redirect_to_repo/CoordRefSystems). No need for GDAL.
That’s seems an excellent idea! Thanks, I’ll see what I can do!
---
### Author:  [@Raf](https://discourse.julialang.org/u/Raf)
#### Post date: [January 20, 2025, 4:12pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/5 "2025-01-20T16:12:22Z")
`Raster(file)` if file is the path to a tiff
Trying random arguments is unlikely to succeed 😉
---
### Author:  [@cshen](https://discourse.julialang.org/u/cshen)
#### Post date: [January 20, 2025, 4:12pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/6 "2025-01-20T16:12:27Z")
Ok, I think `GeoTIFF.affineparams2D` was the missing piece I needed.
But interestingly, this works only for the first image.
```julia-repl
julia> geoimg = GeoTIFF.load(file)
julia> GeoTIFF.modeltype(GeoTIFF.metadata(nth(geoimg, 1)))
0x0002
julia> GeoTIFF.modeltype(GeoTIFF.metadata(nth(geoimg, 2)))
julia>
```
Now that I look back at the output when loading the file, there are a lot of repeating tags, that seem associated with the various images at different resolutions.
Is the dataset badly formatted?
---
### Author:  [@joa-quim](https://discourse.julialang.org/u/joa-quim)
#### Post date: [January 20, 2025, 4:16pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/7 "2025-01-20T16:16:20Z")
More options. I just picked one GeoTIFF file at random among those that I have in a work dir.
```julia
using GMT
julia> I = gmtread("KR_S2B_MSIL2A_20210614_20.tiff")
A GMTimage object with 10 bands of type UInt16
Pixel node registration used
x_min: 445000.0 x_max :463000.0 x_inc :20.0 n_columns :900
y_min: 5.106e6 y_max :5.124e6 y_inc :20.0 n_rows :900
z_min: 0.0 z_max :17936.0
Mem layout: BRBa
PROJ: +proj=utm +zone=33 +datum=WGS84 +units=m +no_defs
```
---
### Author:  [@juliohm](https://discourse.julialang.org/u/juliohm)
#### Post date: [January 20, 2025, 4:23pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/8 "2025-01-20T16:23:49Z")
Hi @cshen, I don’t remember the convention out of my head. But the metadata is stored at the top level, including these datasets with iterators. If you encounter any issue with the GeoTIFF.jl implementation, please feel free to suggest improvements.
---
### Author:  [@cshen](https://discourse.julialang.org/u/cshen)
#### Post date: [January 20, 2025, 6:20pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/9 "2025-01-20T18:20:54Z")
> [@Raf](#):
>
> `Raster(file)` if file is the path to a tiff
>
> Trying random arguments is unlikely to succeed 😉
It wasn’t completely random, just a bit.
I saw that `Raster(filepath)` was available but I didn’t want to bring in the whole GDAL, felt overkill for what I needed to do 🙂
> [@juliohm](#):
>
> Hi @cshen, I don’t remember the convention out of my head. But the metadata is stored at the top level, including these datasets with iterators. If you encounter any issue with the [GeoTIFF.jl](https://juliaregistries.github.io/General/packages/redirect_to_repo/GeoTIFF) implementation, please feel free to suggest improvements.
I don’t know the standard, nor the conventions, so I don’t know if this is something that whoever made the file decided or if it can be relied upon, but It would have been awesome, in this case, to have spatial information automatically inferred for all images in the iterator, based on the top level image metadata, and rescaled using the difference in image size.
for example:
```julia-repl
julia> GeoTIFF.affineparams2D(GeoTIFF.metadata(nth(geotiffs, 1)))
([0.0002999999999999996 0.0; 0.0 -0.0003000000000000001], [142.0000611111, -10.000138888905807])
julia> GeoTIFF.affineparams2D(GeoTIFF.metadata(nth(geotiffs, 2)))
([1.0 0.0; 0.0 1.0], [0.0, 0.0])
julia> size(nth(geotiffs, 1))
(23333, 16666)
julia> size(nth(geotiffs, 2))
(11667, 8333)
```
while it could be inferred to be:
```julia
modelpixelscale = [0.0006 0.0; 0.0 -0.0006] # rescaled from the size ratio
modeltiepoints = [142.0000611111, -10.000138888905807] #inherited from main image
```
or something like that.
EDIT: I did a little digging, It is actually possible to know that this is indeed the case using the `SUBFILETYPE` tag, in the TIFF Spec [0][1]:
> A general indication of the kind of data contained in this subfile.
>
> Replaces the old SubfileType field, due to limitations in the definition of that field.
>
> NewSubfileType is mainly useful when there are multiple subfiles in a single TIFF file.
>
> This field is made up of a set of 32 flag bits. Unused bits are expected to be 0. Bit 0 is the low-order bit. Currently defined values are:
>
> Bit 0 is 1 if the image is a reduced-resolution version of another image in this TIFF file; else the bit is 0.
> Bit 1 is 1 if the image is a single page of a multi-page image (see the PageNumber field description); else the bit is 0.
> Bit 2 is 1 if the image defines a transparency mask for another image in this TIFF file. The PhotometricInterpretation value must be 4, designating a transparency mask.
Which for my file is indeed a chain of `IFD`s with `Tag(SUBFILETYPE, 1)`
[0]: [Baseline TIFF Tag NewSubfileType (TIFFTAG\_SUBFILETYPE), code 254 (0x00FE)](https://web.archive.org/web/20181105215020/https://www.awaresystems.be/imaging/tiff/tifftags/newsubfiletype.html)
[1]: [PDF of TIFF SPEC](https://web.archive.org/web/20181030091707/https://www.awaresystems.be/imaging/tiff/specification/TIFF6.pdf)
---
### Author:  [@juliohm](https://discourse.julialang.org/u/juliohm)
#### Post date: [January 20, 2025, 6:31pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/10 "2025-01-20T18:31:01Z")
Thanks for digging into the spec @cshen. Feel free to submit a PR with any improvement that is compliant. GeoTIFF.jl should support any spec-compatible file.
---
### Author:  [@cshen](https://discourse.julialang.org/u/cshen)
#### Post date: [January 20, 2025, 7:42pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/11 "2025-01-20T19:42:45Z")
Sure, I’ll make an issue and setup a draft PR in the next days!
---
### Author:  [@juliohm](https://discourse.julialang.org/u/juliohm)
#### Post date: [January 20, 2025, 7:51pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/12 "2025-01-20T19:51:03Z")
As a side note, you may be interested in GeoIO.jl, which uses GeoTIFF.jl as the backend to load these datasets as geotables. All explained in the [GDSJL](https://juliaearth.github.io/geospatial-data-science-with-julia) book.
If you need a lightweight dependency, then GeoTIFF.jl is the way to go. Thanks for considering a contribution.
---
### Author:  [@cshen](https://discourse.julialang.org/u/cshen)
#### Post date: [January 20, 2025, 8:30pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/13 "2025-01-20T20:30:27Z")
By the way, it would be awesome to have GeoTIFF.jl instead of GDAL in Rasters.jl 😃 (lets julia all the things)
---
### Author:  [@Raf](https://discourse.julialang.org/u/Raf)
#### Post date: [January 20, 2025, 8:47pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/14 "2025-01-20T20:47:56Z")
Yes native tiff is something I’ve been thinking about for a while. One problem is the native julia compression with Inflate.jl is still slow, it would be nice to optimise it a bit more. Another is GeoTiff.jl isn’t DiskArrays.jl compatible so it wont work so well with Rasters.jl for larger than memory data, and it doesn’t read or write COG yet.
So while removing binary deps is a worthy goal, it may be a while until gdal is practically replaceable for all uses of geotiff.
---
### Author:  [@tlnagy](https://discourse.julialang.org/u/tlnagy)
#### Post date: [October 30, 2025, 4:32pm UTC](https://discourse.julialang.org/t/how-to-extract-location-from-strided-geotiff-raster/124973/15 "2025-10-30T16:32:44Z")
Author of `TiffImages` here, I agree with @Raf here that it would be great to rework the TIFF engine to work with `DiskArrays`, but sadly I don’t have the time to do something of that scale these days. It would solve a lot of performance issues with OOM indexing and performance.