This is a standalone (Python / Flask) and Lambda-based dynamic tiler for S3-hosted GeoTIFFs. It is also a set of utilities for transcoding and otherwise preparing raster data for rendering by the tiler.
More information:
Development is best done using Docker, as there are a number of dependencies, some of which remain unpackaged for common OSes (e.g. GDAL-2.2+).
If you're going to be experimenting with mosaicking in any form, docker-compose
makes things even
easier, as it packages marblecutter alongside a PostGIS database containing footprints and other
metadata about imagery.
# build
docker-compose build
# start (requires that Postgres has been populated with appropriate footprint data)
docker-compose up
The transcoding and metadata tools can be used from the images built by docker-compose
:
docker-compose run web bash
process.sh ...
project.json.hbs
defines an apex
project that can be deployed to AWS Lambda.
Create IAM role: tiler_lambda_function
with Trust Relationship policy document:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "lambda.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
Create IAM policy: tiler_lambda_logs
with policy document:
{
"Version": "2012-10-17",
"Statement": [
{
"Action": [
"logs:*"
],
"Effect": "Allow",
"Resource": "*"
}
]
}
Attach policy to the tiler_lambda_function
role.
Update project.json
with tiler_lambda_function
's Role ARN, e.g. arn:aws:iam::670261699094:role/tiler_lambda_function
.
Run apex deploy
. (Add -l debug
to see what's running.) This will build the Docker image defined
in deps/
to produce a task.zip
containing binary dependencies needed when deploying to the
Lambda runtime.
PixelCollection
A collection of pixels (as data
) associated with Bounds
.
Bounds
A bounding box (bounds
) with an associated CRS (crs
).