This is a Python-based lambda function that converts shapefiles to geojsons. Specifically, it converts the 7-day US (Conterminous and Hawaii) Fire data (375m resolution) via NASA/NOAA VIIRS (Suomi polar orbit) that is posted at: https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms/active-fire-data.
It also converts the GeoMAC/USGS fire name data posted at: https://rmgsc.cr.usgs.gov/outgoing/GeoMAC/current_year_fire_data/current_year_all_states/
The creation of this task was prompted by a note on Burrito Justice's sonoma-napa-fire-map-viirs about the manual conversion of the daily passes.
To make this all work, this tasks uses Development Seed's excellent Geolamdbda Docker images for buindling core geo liibraries into a deployable package. Their deployment write-up covers how this lambda is packaged and built.
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Build the base image that is referenced in the
docker-compose.yml:docker build -t modisviirs ./ -
Set up an s3 bucket and update the name referenced in
lambda/lambda_handler.py -
Package the lambda for deployment:
docker-compose run package -
Deploy to AWS:
aws lambda update-function-code --function-name modis-viirs-convert --zip-file fileb://lambda-deploy.zipNote: As discussed in the Development Seed docs, this presumes that you've already set up your function on AWS. Since we are making a number of network calls and dealing with File I/O, we need to bump up the timeout limit before we can run this; 2 minutes was enough.
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Create a test event in the AWS Lambda dashboard. I used the
Hello Worldtemplate. We don't do any processing with the event payload, so you can stick whatever you want in the payload space. Once you've configured your test, click theTestbutton and wait for the output to appear in your s3 bucket. -
Configure a CloudWatch event to execute the conversion script on a time table. Create a CloudWatch Rule and select your lambda function as the target. You can either run it on fixed intervals or pass in a more specific CRON style schedule.