v1-aoi.py

'''
Use case 1
Scrape the catalog for an AOI/TOI: Filter the RapidEye Grid-UTM catalog for products in an AOI 
(United States in Iowa) with an acquisition period between "2014-04-01" and "2014-09-15" with a maximum 
cloud cover value of "20%." Download all of the analytic assets.
'''

import requests
from datetime import datetime
import pytz
import geojson

url = "https://api.planet.com/v1/catalogs/grid-utm-25km-experimental/items/"
key = "YOUR-API-KEY"

#add AOI -- rectangle in Iowa drawn in geojson.io
poly = {
        "type": "Polygon",
        "coordinates": [
          [
            [
              -95.460205078125,
              41.97174336327968
            ],
            [
              -95.460205078125,
              42.17561739661684
            ],
            [
              -94.8724365234375,
              42.17561739661684
            ],
            [
              -94.8724365234375,
              41.97174336327968
            ],
            [
              -95.460205078125,
              41.97174336327968
            ]
          ]
        ]
      }
  


intersects = geojson.dumps(poly)

#set your filters here For example: cloud cover less than 20%

start = datetime(year=2014, month=4, day=1, tzinfo=pytz.utc).isoformat()
end = datetime(year=2014, month=9, day=15,  tzinfo=pytz.utc).isoformat()
cloud = 0.20

filters = {
    "catalog::acquired": start,
    "catalog::acquired": end,
    "catalog::cloud_cover": cloud,
    "intersects": intersects
}

data = requests.get(url, params=filters, auth=(key, ''))

image_data = data.json()["features"]

#show IDs for images that meet criteria

for s in scenes_data:
    print s["id"]



#r = requests.get(url, params=filters, auth=(key, ''))
#r.raise_for_status()
#data = r.json()

#for scene in scenes_data:
#    thumb_link = scene["properties"]["links"]["thumbnail"]
#    download_image(thumb_link, key)