Aircraft Detection¶

• Get Pleiades imagery for the given airports
• Execute tiling and aircraft detection blocks via parallel jobs

• Visualize the results

• The example costs around 1700 UP42 credits

Setup¶

Import required libraries

In [14]:

import up42
import geopandas as gpd
import rasterio
from rasterio.plot import show
import matplotlib.pyplot as plt
from shapely.geometry import box

import up42 import geopandas as gpd import rasterio from rasterio.plot import show import matplotlib.pyplot as plt from shapely.geometry import box

Configure areas of interest

In [15]:

aoi_txl = {"type":"FeatureCollection","features":[{"type":"Feature","properties":{},
                "geometry":{"type":"Polygon","coordinates":[[[13.286740779876709,52.5509016976356],
                                                             [13.300495147705078,52.5509016976356],
                                                             [13.300495147705078,52.556890079685594],
                                                             [13.286740779876709,52.556890079685594],
                                                             [13.286740779876709,52.5509016976356]]]}}]}
aoi_muc = {"type":"FeatureCollection","features":[{"type":"Feature","properties":{},
                "geometry":{"type":"Polygon","coordinates":[[[11.789016723632812,48.348577346994944],
                                                             [11.809401512145996,48.348577346994944],
                                                             [11.809401512145996,48.360155725059116],
                                                             [11.789016723632812,48.360155725059116],
                                                             [11.789016723632812,48.348577346994944]]]}}]}


aois = [{'title': 'TXL', 'geometry': aoi_txl},
        {'title': 'MUC', 'geometry': aoi_muc}]

aoi_txl = {"type":"FeatureCollection","features":[{"type":"Feature","properties":{}, "geometry":{"type":"Polygon","coordinates":[[[13.286740779876709,52.5509016976356], [13.300495147705078,52.5509016976356], [13.300495147705078,52.556890079685594], [13.286740779876709,52.556890079685594], [13.286740779876709,52.5509016976356]]]}}]} aoi_muc = {"type":"FeatureCollection","features":[{"type":"Feature","properties":{}, "geometry":{"type":"Polygon","coordinates":[[[11.789016723632812,48.348577346994944], [11.809401512145996,48.348577346994944], [11.809401512145996,48.360155725059116], [11.789016723632812,48.360155725059116], [11.789016723632812,48.348577346994944]]]}}]} aois = [{'title': 'TXL', 'geometry': aoi_txl}, {'title': 'MUC', 'geometry': aoi_muc}]

Authenticate with UP42

In [16]:

#up42.authenticate(project_id="123", project_api_key="456")
up42.authenticate(cfg_file="config.json")
up42.settings(log=False)

#up42.authenticate(project_id="123", project_api_key="456") up42.authenticate(cfg_file="config.json") up42.settings(log=False)

2020-12-03 13:49:53,328 - Got credentials from config file.
2020-12-03 13:49:53,769 - Authentication with UP42 successful!
2020-12-03 13:49:53,770 - Logging disabled - use up42.settings(log=True) to reactivate.

Catalog Search¶

Search cloudfree Pleiades image for the two aois and visualise the quicklooks.

In [17]:

catalog = up42.initialize_catalog()


for aoi in aois:
    print("\n---------" + aoi["title"] + "---------\n")
    search_paramaters = catalog.construct_parameters(geometry=aoi['geometry'], 
                                                     start_date="2020-04-01",
                                                     end_date="2020-04-30",
                                                     sensors=["pleiades"],
                                                     max_cloudcover=10,
                                                     sortby="acquisitionDate",
                                                     ascending=False,
                                                     limit=3)
    search_results = catalog.search(search_paramaters)
    
    # Download & Visualise quicklooks
    catalog.download_quicklooks(image_ids=search_results.id.to_list(), sensor="pleiades")
    display(search_results.head())
    catalog.plot_quicklooks(figsize=(18,5), titles=search_results.sceneId.to_list())

    # Select least cloud scene for further workflow
    aoi["sceneId"] = search_results.sceneId.to_list()[0]

catalog = up42.initialize_catalog() for aoi in aois: print("\n---------" + aoi["title"] + "---------\n") search_paramaters = catalog.construct_parameters(geometry=aoi['geometry'], start_date="2020-04-01", end_date="2020-04-30", sensors=["pleiades"], max_cloudcover=10, sortby="acquisitionDate", ascending=False, limit=3) search_results = catalog.search(search_paramaters) # Download & Visualise quicklooks catalog.download_quicklooks(image_ids=search_results.id.to_list(), sensor="pleiades") display(search_results.head()) catalog.plot_quicklooks(figsize=(18,5), titles=search_results.sceneId.to_list()) # Select least cloud scene for further workflow aoi["sceneId"] = search_results.sceneId.to_list()[0]

---------TXL---------

100%|██████████| 3/3 [00:02<00:00,  1.34it/s]

	geometry	id	acquisitionDate	constellation	providerName	blockNames	cloudCoverage	up42:usageType	providerProperties	sceneId
0	POLYGON ((13.20640 52.58098, 13.20616 52.45458...	c5497393-8f8d-4367-9527-c39344e220fe	2020-04-28T10:31:35Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	2.31	[DATA, ANALYTICS]	{'commercialReference': 'SO20025725', 'acquisi...	DS_PHR1B_202004281031350_FR1_PX_E013N52_0513_0...
1	POLYGON ((13.21800 52.58082, 13.21860 52.45684...	07e5eaba-7830-4aee-8c27-6b69fa1da89f	2020-04-23T10:19:52Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	0.00	[DATA, ANALYTICS]	{'commercialReference': 'SO20022129', 'acquisi...	DS_PHR1B_202004231019525_FR1_PX_E013N52_0513_0...
2	POLYGON ((13.20760 52.58274, 13.20828 52.45502...	11616f18-4002-44fc-bfeb-571c6657ccf4	2020-04-17T10:16:45Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	0.40	[DATA, ANALYTICS]	{'commercialReference': 'SO20017653', 'acquisi...	DS_PHR1A_202004171016453_FR1_PX_E013N52_0513_0...