feat(pipeline): fire burned area

pipeline/dags/fire.burned_area.py

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+from datetime import datetime
+import task_factories
+from airflow import DAG
+from airflow.models.param import Param
+from helper import get_default_layer_version
+
+# layer
+LAYER_ID = 'fire'
+LAYER_VARIABLE = 'burned_area'
+RESOLUTION = '1440 720'
+METADATA = {
+    "id": f'{LAYER_ID}.{LAYER_VARIABLE}',
+    "timestamps": [],  # will be injected
+    "min_value": 0,
+    "max_value": 400000000,
+    "type": "image",  # 'tiles' or 'image'
+    "zoom_levels": '0-3',
+    "units": "m2",
+    "basemap": 'dark',
+    "legend_values": [
+        "300 km\u00b2",
+        "200",
+        "100",
+        "0"
+    ],
+    "time_format": {
+        "year": "numeric",
+        "month": "long"
+    }
+}
+
+# dev
+BUCKET_ORIGIN = 'esa-cfs-cate-data'
+BUCKET_TMP = 'esa-cfs-pipeline-tmp'
+WORKDIR = '/workdir/files'
+COLOR_FILE = f'/opt/airflow/plugins/colors/{LAYER_ID}.{LAYER_VARIABLE}.txt'
+DEBUG = False
+
+default_layer_version = get_default_layer_version()
+dag_params = {
+    "max_files": Param(2, type=["null", "integer"], minimum=0,),
+    "output_bucket": Param("esa-cfs-pipeline-output", type=["string"], enum=['esa-cfs-pipeline-output', 'esa-cfs-tiles']),
+    "skip_downloads": Param(False, type="boolean"),
+    "layer_version": Param(default_layer_version, type="string")
+}
+
+with DAG(dag_id=METADATA["id"], start_date=datetime(2022, 1, 1), schedule=None, catchup=False, params=dag_params) as dag:
+
+    # create tasks
+    clean_workdir = task_factories.clean_dir_skippable(
+        task_id='clean_workdir', dir=WORKDIR)()
+    list_files = task_factories.gcs_list_files(
+        bucket_name=BUCKET_ORIGIN, layer_id=LAYER_ID, layer_variable=LAYER_VARIABLE)
+    download = task_factories.gcs_download_file(
+        bucket_name=BUCKET_ORIGIN, dir=WORKDIR, appendix='_downloaded')
+    legend_image = task_factories.legend_image(
+        workdir=WORKDIR, color_file=COLOR_FILE)
+    metadata = task_factories.metadata(workdir=WORKDIR, metadata=METADATA)
+    gdal_transforms = task_factories.gdal_transforms(
+        layer_variable=LAYER_VARIABLE, color_file=COLOR_FILE, layer_type=METADATA['type'], zoom_levels=METADATA['zoom_levels'], gdal_ts=RESOLUTION)
+    upload = task_factories.upload(
+        WORKDIR, LAYER_ID, LAYER_VARIABLE, METADATA['type'])
+
+    # connect tasks
+    files = list_files()
+    clean_workdir >> files
+    downloads = download.expand(filename=files)
+    gdal_transforms(downloads) >> upload()
+    clean_workdir >> legend_image
+    metadata(files)
+
+    if DEBUG:
+        downloads >> task_factories.gdal_info()

pipeline/plugins/colors/fire.burned_area.txt

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+300000000 51 26 26 255
+150000000 160 40 55 255
+25000000 255 124 27 255
+10000000 255 237 38 255
+1 255 237 38 0
+0 255 255 255 0