hls-landsat-historic

AWS Stack for querying historic Landsat inventory and notifying hls-orchestration

Requirements

• Python>=3.8
• tox
• aws-cli
• An IAM role with sufficient permissions for creating, destroying and modifying the relevant stack resources.

Environment Settings

$ export LANDSAT_HISTORIC_STACKNAME=<Name of your stack>
$ export LANDSAT_HISTORIC_LAST_DATE_INITIAL=<The date to start backwards historic processing YYYY/MM/DD>
$ export LANDSAT_HISTORIC_DAYS_RANGE=<The number of days to process in each execution >
$ export LANDSAT_HISTORIC_CRON_STRING=<AWS Cron string for execution frequency>
$ export LANDSAT_HISTORIC_GCC=<False>
$ export LANDSAT_HISTORIC_GCC_BOUNDARY_ARN=<GCC Boundary Policy Arn>

CDK Commands

Synth

Display generated cloud formation template that will be used to deploy.

$ tox -e dev -r -- synth

Diff

Display a diff of the current deployment and any changes created.

$ tox -e dev -r -- diff || true

Deploy

Deploy current version of stack.

$ tox -e dev -r -- deploy

Inventory Data

The subset_granules Lambda functions requires access to the USGS Historic Landsat Invetory. The USGS Historic Landsat Invetory is available via

$ s3://usgs-landsat/collection02/inventory/inventory_product_list.zip --request-payer requester

S3 Select only supports GZIP and BZIP2 compression. Recompress the inventory with

$ unzip inventory_product_list.zip
$ gzip inventory_product_list.csv

It can then be uploaded to the bucket created by your stack deploy

$ s3 cp inventory_product_list.csv.gz s3://<bucket_name>

Development

For active stack development run

$ tox -e dev -r -- version

This creates a local virtualenv in the directory devenv. To use it for development

$ source devenv/bin/activate

Then run the following to install the project's pre-commit hooks

$ pre-commit install

Tests

To run unit test for all included Lambda functions

tox -r