Use case 1: selecting bursts

Notebook setup

[1]:

%matplotlib inline
%load_ext autoreload
%autoreload 2

[2]:

import sys
sys.path.append('../..')

[3]:

import numpy as np
import matplotlib.pyplot as plt

[4]:

import s1etad
from s1etad import Sentinel1Etad, ECorrectionType

Open the dataset

[5]:

filename = '../../sample-products/S1B_IW_ETA__AXDH_20200127T113414_20200127T113858_020002_025D72_0096.SAFE'

[6]:

eta = Sentinel1Etad(filename)

[7]:

eta

[7]:

Sentinel1Etad("../../sample-products/S1B_IW_ETA__AXDH_20200127T113414_20200127T113858_020002_025D72_0096.SAFE")  # 0x7facce683490
Number of Sentinel-1 slices: 11
Sentinel-1 products list:
  S1B_IW_SLC__1ADH_20200127T113414_20200127T113444_020002_025D72_FD42.SAFE
  S1B_IW_SLC__1ADH_20200127T113442_20200127T113510_020002_025D72_FC8F.SAFE
  S1B_IW_SLC__1ADH_20200127T113507_20200127T113534_020002_025D72_78DF.SAFE
  S1B_IW_SLC__1ADH_20200127T113532_20200127T113559_020002_025D72_1ABB.SAFE
  S1B_IW_SLC__1ADH_20200127T113557_20200127T113624_020002_025D72_6706.SAFE
  S1B_IW_SLC__1ADH_20200127T113622_20200127T113649_020002_025D72_78F0.SAFE
  S1B_IW_SLC__1ADH_20200127T113647_20200127T113715_020002_025D72_11FB.SAFE
  S1B_IW_SLC__1ADH_20200127T113712_20200127T113739_020002_025D72_FCC6.SAFE
  S1B_IW_SLC__1ADH_20200127T113737_20200127T113804_020002_025D72_1FED.SAFE
  S1B_IW_SLC__1ADH_20200127T113802_20200127T113829_020002_025D72_C434.SAFE
  S1B_IW_SLC__1ADH_20200127T113827_20200127T113858_020002_025D72_E443.SAFE
Number of swaths: 3
Swath list: IW1, IW2, IW3
Azimuth time:
  min: 2020-01-27 11:34:14.475597
  max: 2020-01-27 11:38:58.167033
Range time:
  min: 0.005371080957826855
  max: 0.006416814907377812
Grid sampling:
  x: 8.081406101630269e-07
  y: 0.028777788199999974
  unit: s
Grid spacing:
  x: 200.0
  y: 200.0
  unit: m
Processing settings:
  troposphericDelayCorrection: True
  ionosphericDelayCorrection: True
  solidEarthTideCorrection: True
  bistaticAzimuthCorrection: True
  dopplerShiftRangeCorrection: True
  FMMismatchAzimuthCorrection: True

Selecting the burst by filtering in time

The availability of the burst catalogue, allows to perform queries and filter the burst by performing time selection using the first_time and last_time keywords of the query_burst method.

If no time is provided then all the burst are selected:

[8]:

df = eta.query_burst()

print(f"Number of bursts: {len(df)}")
df.head()

Number of bursts: 306

[8]:

	bIndex	pIndex	sIndex	productID	swathID	azimuthTimeMin	azimuthTimeMax
0	1	1	1	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW1	2020-01-27 11:34:14.475597000	2020-01-27 11:34:17.641153701
102	2	1	2	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW2	2020-01-27 11:34:15.396486222	2020-01-27 11:34:18.619598500
204	3	1	3	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW3	2020-01-27 11:34:16.374931021	2020-01-27 11:34:19.569265511
1	4	1	1	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW1	2020-01-27 11:34:17.209486879	2020-01-27 11:34:20.403821369
103	5	1	2	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW2	2020-01-27 11:34:18.159153889	2020-01-27 11:34:21.353488379

It is possible to reduce the selection by start time in this case the stop time is the last available burst:

[9]:

import dateutil
first_time = dateutil.parser.parse('2020-01-27T11:38:51.231586')

df = eta.query_burst(first_time=first_time)

print(f"Number of bursts: {len(df)}")
df.head()

Number of bursts: 5

[9]:

	bIndex	pIndex	sIndex	productID	swathID	azimuthTimeMin	azimuthTimeMax
202	302	11	2	S1B_IW_SLC__1ADH_20200127T113827_20200127T1138...	IW2	2020-01-27 11:38:51.231586119	2020-01-27 11:38:54.425920609
304	303	11	3	S1B_IW_SLC__1ADH_20200127T113827_20200127T1138...	IW3	2020-01-27 11:38:52.181253129	2020-01-27 11:38:55.404365408
101	304	11	1	S1B_IW_SLC__1ADH_20200127T113827_20200127T1138...	IW1	2020-01-27 11:38:53.044586775	2020-01-27 11:38:56.238921266
203	305	11	2	S1B_IW_SLC__1ADH_20200127T113827_20200127T1138...	IW2	2020-01-27 11:38:53.994253786	2020-01-27 11:38:57.188588276
305	306	11	3	S1B_IW_SLC__1ADH_20200127T113827_20200127T1138...	IW3	2020-01-27 11:38:54.943920797	2020-01-27 11:38:58.167033075

It is possible to reduce the selection by the stop time in this case the start time is the first available burst:

[10]:

last_time =  dateutil.parser.parse('2020-01-27T11:34:20.403822')

df = eta.query_burst(last_time=last_time)

print(f"Number of bursts: {len(df)}")
df.head()

Number of bursts: 4

[10]:

	bIndex	pIndex	sIndex	productID	swathID	azimuthTimeMin	azimuthTimeMax
0	1	1	1	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW1	2020-01-27 11:34:14.475597000	2020-01-27 11:34:17.641153701
102	2	1	2	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW2	2020-01-27 11:34:15.396486222	2020-01-27 11:34:18.619598500
204	3	1	3	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW3	2020-01-27 11:34:16.374931021	2020-01-27 11:34:19.569265511
1	4	1	1	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW1	2020-01-27 11:34:17.209486879	2020-01-27 11:34:20.403821369

It is possible to reduce the selection by the start and stop time:

[11]:

first_time = dateutil.parser.parse('2020-01-27T11:34:17.209487')
last_time =  dateutil.parser.parse('2020-01-27T11:34:21.353489')

# query the catalogues for of all the swaths
df = eta.query_burst(first_time=first_time, last_time=last_time)
print(f"Number of bursts: {len(df)}")
df.head()

Number of bursts: 1

[11]:

	bIndex	pIndex	sIndex	productID	swathID	azimuthTimeMin	azimuthTimeMax
103	5	1	2	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW2	2020-01-27 11:34:18.159153889	2020-01-27 11:34:21.353488379

Selecting by swath (and time)

The time selection can be combined with a selection by swath using the swath keyword. If not used all the swath are used

[12]:

first_time = dateutil.parser.parse('2020-01-27T11:34:17.209487')
last_time =  dateutil.parser.parse('2020-01-27T11:34:21.353489')

# query the catalogue for a subset of the swaths
df = eta.query_burst(first_time=first_time, last_time=last_time, swath='IW1')
print(f"Number of bursts: {len(df)}")
df

Number of bursts: 0

[12]:

	bIndex	pIndex	sIndex	productID	swathID	azimuthTimeMin	azimuthTimeMax

Query the catalogue for a subset of the swaths:

[13]:

first_time = dateutil.parser.parse('2020-01-27T11:34:17.209487')
last_time =  dateutil.parser.parse('2020-01-27T11:34:28.663047')

df = eta.query_burst(first_time=first_time, last_time=last_time, swath=['IW1', 'IW2'])

print(f"Number of bursts: {len(df)}")
df.head()

Number of bursts: 6

[13]:

	bIndex	pIndex	sIndex	productID	swathID	azimuthTimeMin	azimuthTimeMax
103	5	1	2	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW2	2020-01-27 11:34:18.159153889	2020-01-27 11:34:21.353488379
2	7	1	1	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW1	2020-01-27 11:34:19.972154546	2020-01-27 11:34:23.166489036
104	8	1	2	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW2	2020-01-27 11:34:20.921821556	2020-01-27 11:34:24.116156047
3	10	1	1	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW1	2020-01-27 11:34:22.734822213	2020-01-27 11:34:25.929156703
105	11	1	2	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW2	2020-01-27 11:34:23.684489224	2020-01-27 11:34:26.878823714

Selecting by Sentinel-1 product name (swath and time)

The time selection can be combined with a selection by swath using the product_name keyword.

[14]:

first_time = dateutil.parser.parse('2020-01-27T11:34:30.159492')
last_time =  dateutil.parser.parse('2020-01-27T11:34:56.260946')

product_name = 'S1B_IW_SLC__1ADH_20200127T113414_20200127T113444_020002_025D72_FD42.SAFE'
df = eta.query_burst(first_time=first_time, last_time=last_time, product_name=product_name, swath=['IW3'])

print(f"Number of bursts: {len(df)}")
df.head()

Number of bursts: 4

[14]:

	bIndex	pIndex	sIndex	productID	swathID	azimuthTimeMin	azimuthTimeMax
210	21	1	3	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW3	2020-01-27 11:34:32.922159236	2020-01-27 11:34:36.116493726
211	24	1	3	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW3	2020-01-27 11:34:35.684826903	2020-01-27 11:34:38.879161393
212	27	1	3	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW3	2020-01-27 11:34:38.447494570	2020-01-27 11:34:41.641829060
213	30	1	3	S1B_IW_SLC__1ADH_20200127T113414_20200127T1134...	IW3	2020-01-27 11:34:41.181384449	2020-01-27 11:34:44.404496728