Import landsat example from tutorials

.gitignore

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+.DS_Store
+.venv/
+.vscode/
 credentials*
 config*
 token*

landsat/ReadMe.md

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+# LandSat tutorial for Essentials
+
+General data mananagement for landsat using native GCP tools.
+
+https://cloud.google.com/storage/docs/public-datasets/landsat
+
+
+Modeling after the Drew use-case.
+
+https://www.pnas.org/content/118/15/e2021219118#sec-6
+
+
+## Stage Zero
+
+Drew has identified the products by hand and manually downloaded the data files. 
+
+## Stage One
+
+Access data via command line tools.  Get the index and view.
+
+```
+mkdir -v data
+gsutil ls gs://gcp-public-data-landsat
+gsutil cp gs://gcp-public-data-landsat/index.csv.gz data/
+gzip -d index.csv.gz
+```
+
+## Stage Three
+
+Automate
+```
+bash get-index.sh
+python3 search.py | bash download.sh
+```

landsat/clean.sh

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+#!/bin/bash
+
+echo "=== clean.sh"
+rm -v -f data/index*
+rm -v -rf data/L*

landsat/download.sh

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+#!/bin/bash
+
+# Read space separated URL from STDIN and download 
+# -r do not interpret backslashes as an escape
+while read -r URL ; do
+    echo "+++ $URL"
+    # -m parallel
+    # -n no-clobber
+    # -r recursive
+    gsutil -m cp -n -r "${URL}/" data/
+done

landsat/get-index.sh

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+#!/bin/bash
+
+echo "=== get-index.sh"
+
+## Check connection by doing an ls
+gsutil ls gs://gcp-public-data-landsat
+
+## if the data is not there, get it and uncompress it
+if [ ! -r data/index.csv ] ; then
+    mkdir -v data
+    gsutil cp gs://gcp-public-data-landsat/index.csv.gz data/
+    gzip -d data/index.csv.gz
+fi

landsat/search.json

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+{
+    "top": 38.99,
+    "bottom":38.79,
+    "left": -92.56,
+    "right": -92.36
+}

landsat/search.py

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+#!/usr/bin/python3
+import json
+import csv
+
+DEBUG=False
+LIMIT=1000
+
+## Example search
+# Search for the Burr Oak Tree
+#  * 38.899313,-92.464562 (Lat north+, Long west-)
+#  * Landsat: Path 025, Row 033
+
+config=json.load(open("search.json"))
+left=config['left']
+right=config['right']
+top=config['top']
+bottom=config['bottom']
+
+# SCENE_ID,PRODUCT_ID,SPACECRAFT_ID,SENSOR_ID,DATE_ACQUIRED,COLLECTION_NUMBER,COLLECTION_CATEGORY,SENSING_TIME,DATA_TYPE,WRS_PATH,WRS_ROW,CLOUD_COVER,NORTH_LAT,SOUTH_LAT,WEST_LON,EAST_LON,TOTAL_SIZE,BASE_URL
+reader=csv.reader(open("data/index.csv"))
+header=next(reader)
+count=0
+
+# Iterate through CSV and print matching product BASE_URL
+for l in reader:
+    count+=1
+    if DEBUG and count>=LIMIT:
+        break
+
+    # Extract data
+    SCENE_ID,PRODUCT_ID,SPACECRAFT_ID,SENSOR_ID,DATE_ACQUIRED,COLLECTION_NUMBER,COLLECTION_CATEGORY,SENSING_TIME,DATA_TYPE,WRS_PATH,WRS_ROW,CLOUD_COVER,NORTH_LAT,SOUTH_LAT,WEST_LON,EAST_LON,TOTAL_SIZE,BASE_URL=l
+    west,east=float(WEST_LON),float(EAST_LON)
+    north,south=float(NORTH_LAT),float(SOUTH_LAT)
+    if DEBUG: print(west,left,east,right,north,top,south,bottom)
+
+    # Test if box is contained-ish by image
+    if west <= left and east >= right and north >= top and south <= bottom:
+        if DEBUG: print(west,left,east,right,north,top,south,bottom,WRS_PATH,WRS_ROW,BASE_URL)
+        print(BASE_URL) # output BASE_URL