Composing raster tiles?
Thiemo Kellner
thiemo at gelassene-pferde.biz
Fri Nov 8 09:15:36 PST 2024
Thanks for sharing your experience. Is that saying that PostGIS has considerable overhead? Sorry, if that is naiv. I might be suffering from the hammer nail deficiency. My background is very database heavy, so too much might look like a database to me.
08.11.2024 16:15:32 Vera Green <vera.green.ca at gmail.com>:
> We use command line GDAL for all our Easter processes, if your data is large I recommend you look into that option.
>
>
> On Fri, Nov 8, 2024, 6:12 AM David Haynes <haynesd2 at gmail.com> wrote:
>> I'll try and help you with A & B
>>
>> a) Is it more efficient to convert the raster to vector data and calculate on the those than to calculate directly on the raster?
>>>> I don't think it would be faster to convert to vector because that would be dumping the raster into polygons. I think for specifically calculating slope, you are better off staying in raster.
>>
>> b) To my understanding, if I calculate the slope on a raster tile, the slope,… of the borders will have accuracy problems. My I idea, was to "stitch" a tile with its direct neighbours, calculate on the composed tile, and either save a cropped calculated composed tile to its original dimension or save the calculated composed tile as is, probably the latter.
>>
>>>> Overall correct, some small adjustments. For any raster operation, the tiles are operated on independently, so you need to "stitch" them together. I've provided a couple of ways in pseduo code
>>
>> Way 1
>> 1) Use ST_Union and make a big tile,
>> 2) Do the spatial operation,
>> 3) Break it up using ST_Tile()
>> The downside is you might run out of memory doing this. Also consider ST_MemUnion()
>>
>> SELECT ST_Tile(ST_Slope(ST_Union(r1.ras)), 350,350)
>> FROM raster_table
>>
>> Way 2)
>> A second option is to basically create an aggregate, which is likely faster.
>> 1) Union the tiles based on ST_Touch - make mega_tiles
>> 2) Do the spatial operation on the mega_tiles
>> 3) Clip the mega_tiles by the old tiles bounding box
>>
>> WITH rtest as
>> (
>> SELECT r1.ras, ST_Union (r1.ras) as megatile
>> FROM raster_table r1
>> LEFT JOIN raster_table r2
>> ON ST_Touches (r1.geom, r2.geom)
>> GROUP BY r1.ras
>> )
>> SELECT ST_CLIP(ST_SLOPE(megatile), ST_Envelop(r1.rast) ) as ras
>> FROM rtest
>>
>> Maybe someone wants to make an aggregate for the raster functions?
>>
>> On Thu, Nov 7, 2024 at 3:31 PM <thiemo at gelassene-pferde.biz> wrote:
>>> Hi
>>>
>>> In my project
>>> https://sourceforge.net/p/treintaytres/code/HEAD/tree/trunk/code_files/data_storage/ I have the
>>> table
>>>
>>> TABLE_SCHEMA TABLE_NAME DATA_TYPE TYPE_NAME COLUMN_NAME
>>> treintaytres topo_files␟t 1111 uuid id
>>> treintaytres topo_files␟t 93 timestamptz entry_pit
>>> treintaytres topo_files␟t 1111 uuid source_id
>>> treintaytres topo_files␟t 12 text file_name
>>> treintaytres topo_files␟t 1111 raster tile
>>> treintaytres topo_files␟t 93 timestamptz file_creation_pit
>>> treintaytres topo_files␟t 12 text file_hash
>>>
>>> TILE contains topographical height raster data from OpenTopography.
>>> They are from different regions, let's say, some tiles cover
>>> Switzerland, some cover New Zealand. I want to create slope and other
>>> data from the height data and I have some questions I hope you can
>>> answer or point me to answers.
>>>
>>> a) Is it more efficient to convert the raster to vector data and
>>> calculate on the those than to calculate directly on the raster?
>>>
>>> b) To my understanding, if I calculate the slope on a raster tile, the
>>> slope,… of the borders will have accuracy problems. My I idea, was to
>>> "stitch" a tile with its direct neighbours, calculate on the composed
>>> tile, and either save a cropped calculated composed tile to its
>>> original dimension or save the calculated composed tile as is,
>>> probably the latter.
>>> Can I compose as follows?
>>> with RASTER_NEIGHBORS as ( select R1.TILE as CURRENT_TILE
>>> ,R2.TILE as NEIGHBOR_TILE
>>> ,R1.ID[http://R1.ID] as CURRENT_ID
>>> from TOPO_FILES␟T R1
>>> left outer join TOPO_FILES␟T R2
>>> on ST_Touches(R1.TILE
>>> ,R2.TILE)
>>> or ST_Intersects(R1.TILE
>>> ,R2.TILE)
>>> where TRUE
>>> --and R1.ID[http://R1.ID] =
>>> '6b8ca53a-bb5f-4c2b-a9c9-94b6a706e9b0'
>>> and TRUE)
>>> ,NION as (select CURRENT_TILE as TILE
>>> ,CURRENT_ID
>>> from RASTER_NEIGHBORS
>>> union
>>> select NEIGHBOR_TILE as TILE
>>> ,CURRENT_ID
>>> from RASTER_NEIGHBORS)
>>> select ST_Union(TILE) as COMPOSED_TILE
>>> ,CURRENT_ID
>>> from NION
>>> group by CURRENT_ID;
>>>
>>> c) Finally, I want to select all the areas where slope, TRI,… conform
>>> certain criteria and have a minium surface size. Do I do it this
>>> better on vector data and do I need to do this on data composed of all
>>> the contiguous areas?
>>>
>>> I would be grateful for any nudge into the right direction. Maybe URLs
>>> with samples.
>>>
>>> Kind regards
>>>
>>> Thiemo
>>>
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