This repo contains a Dockerfile
for the Cesum Terrain Builder (CTB)
app with support for the new Cesium terrain format quantized-mesh. It is build from a
fork
providing quantized-mesh support, as described in this
artice.
Information on the most recent development of this fork is available in this
pull request.
Thanks to @homme and @ahuarte47
for the great work on Cesium Terrain Builder and quantized-mesh support.
Note: The images are manually rebuild, when new commits are published at ahuarte47/cesium-terrain-builder/tree/master-quantized-mesh. If you miss an update in an image, please let us know by creating an issue.
If you experience problems or want to contribute please create an issue or pull request.
Follow the steps below to create your own quantized-mesh tiles for Cesium using this Docker image.
-
2023-08-06:
-
The additional
arm64
image ins now available from both Dockerhub and Github packages.docker pull ghcr.io/tum-gis/ctb-quantized-mesh:latest
docker pull ghcr.io/tum-gis/ctb-quantized-mesh:alpine
-
-
2023-07-31:
-
An additional
arm64
version of the image was added. This currently untested and I'm happy for any feedback on this, see #19. Thearm64
Docker images are hosted in Github packages.docker pull ghcr.io/tum-gis/ctb-quantized-mesh:latest
docker pull ghcr.io/tum-gis/ctb-quantized-mesh:alpine
-
-
2023-03-06:
- Updated both images to reflect latest changes in ahuarte47/cesium-terrain-builder:master-quantized-mesh
- Updated GDAL to 2.4.0 in
latest
image
-
2020-11: Updated
alpine
image to Alpine v3.12 and GDAL v3.14 -
2020-11: Reduced size of all images using multi stage builds.
The amd64
Docker images are available on DockerHub from tumgis or from
Github packages.
To get the image run:
docker pull tumgis/ctb-quantized-mesh:<TAG>
or
docker pull ghcr.io/tum-gis/ctb-quantized-mesh:<TAG>
The arm64
Docker images are ONLY available from
Github packages.
To get the image run:
docker pull ghcr.io/tum-gis/ctb-quantized-mesh:<TAG>
Following tags are available:
Tag | Build status | Arch | Description |
---|---|---|---|
latest |
amd64 arm64 |
Latest image build based on Debian and GDAL 2.4.0 | |
alpine |
amd64 arm64 |
Image based on leightweight Alpine Linux v3.12 and GDAL v3.14 |
- Cesium Terrain Builder Docker
The system resources Docker can use are limited by default on Windows systems. Goto Docker tray Icon -> Settings -> Advanced to adjust the number of cores and main memory Docker can use to increase performance.
It is highly recommended (but not required) to transform your data to the
WGS84 (EPSG:4326) coordinate reference system before using CTB. This helps to avoid
vertial or horizontal offsets of terrain datasets. Use the NTv2
transformation method
if available. This is e.g. supported by FME
using the EsriReprojector
transformer or ESRI ArcGIS.
Put your data in a folder, that can be mounted by Docker. On Windows, you will have to grant access to the drive where the data is located before being able to mount the folder. Goto Docker tray Icon -> Settings -> Shared Drives to share drives with Docker. Visit this blog post for a comprehensive guide on mounting host directories on Windows.
In the following we assume that your terrain data is stored in d:\docker\terrain
for a Windows Docker host and drive d:\
is shared with Docker.
For a Linux Docker host we assume your data is stored in /docker/terrain
.
When your data is transformed and copied to a location available for Docker your are ready for creating a Cesium terrain with CTB.
Before starting CTB it is recommended to pull the latest image version using
docker pull tumgis/ctb-quantized-mesh
.
After that, start a CTB container and mount your terrain data folder to /data
in the container.
Follow the examples below for different operating systems and shells.
docker run -it --name ctb \
-v "/docker/terrain:/data" \
tumgis/ctb-quantized-mesh
docker run -it --name ctb ^
-v "d:/docker/terrain:/data" ^
tumgis/ctb-quantized-mesh
winpty docker run --rm -it --name ctb \
-v "d:\\docker\\terrain:/data" \
tumgis/ctb-quantized-mesh
docker run -it --name ctb `
-v "d:\docker\terrain:/data" `
tumgis/ctb-quantized-mesh
If you dataset consists of a single file, continue to the next step.
If your dataset consists of multiple tiles (more than one file), a
GDAL Virtual Dataset needs to be created using the gdalbuildvrt
app.
gdalbuildvrt <output-vrt-file.vrt> <files>
For instance, if you have several *.tif
files, run:
gdalbuildvrt tiles.vrt *.tif
More options to create a GDAL Virtual Dataset e.g. using a list of files are described in the gdalbuildvrt documentation.
First, create an output folder for you terrain, e.g. mkdir -p terrain
.
Second, run CTB to create the terrain files:
ctb-tile -f Mesh -C -N -o terrain <inputfile.tif or input.vrt>
For example, if a tile.vrt
has been created as described above:
ctb-tile -f Mesh -C -N -o terrain tile.vrt
The ctb-tile
app supports several options. Run ctb-tile --help
to display all options.
For larger datasets consider setting the -m
option and the GDAL_CHACHEMAX
environment
variable as described here.
Finally, a layer description file needs to be created. Simply run the same
command you used for creating the terrain files again adding the -l
switch. For instance:
ctb-tile -f Mesh -C -N -o terrain tiles.vrt # Create terrain files
ctb-tile -f Mesh -C -N -l -o terrain tiles.vrt # Create layer description file
Finally, your terrain data folder should look similar to this:
$ tree -v -C -L 1 terrain/
terrain/
|-- 0
|-- 1
|-- 2
|-- 3
|-- 4
|-- 5
|-- 6
|-- 7
|-- 8
|-- 9
|-- 10
|-- 11
|-- 12
|-- 13
|-- 14
|-- 15
`-- layer.json
The quantized-mesh terrain is now ready for usage.
Read the recommendations for ctb-tile
carefully, especially when handling large datasets.
Datasets with a big extent can lead to overflow errors on lower zoom levels:
0...10...20...30...40...50...60...70...80...90...ERROR 1: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: IReadBlock failed at X offset 0, Y offset 0: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: IReadBlock failed at X offset 0, Y offset 0: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: IReadBlock failed at X offset 0, Y offset 0: IReadBlock failed at X offset 0, Y offset 0: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: IReadBlock failed at X offset 0, Y offset 0: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: IReadBlock failed at X offset 0, Y offset 0: IReadBlock failed at X offset 0, Y offset 0: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: IReadBlock failed at X offset 0, Y offset 0: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
ERROR 1: IReadBlock failed at X offset 0, Y offset 0: IReadBlock failed at X offset 0, Y offset 0: Integer overflow : nSrcXSize=41494, nSrcYSize=16585
As described here,
this is caused by GDAL trying to create overviews from input data.
A possible solution is to create simplified versions of the input data with lower resolutions and use them
for creating the mesh tiles on lower levels.
This can be done using e.g. gdal_translate.
After that, try to create mesh tiles using ctb-tile
with the resolutions that do not crash starting from
level 0.
Try to use the highest resolution possible that does not crash for each level.