Sentinel-1 SLC Burst Mode

Overview 

Sentinel-1 SLC Burst Mode allows you to search for and access individual radar bursts from Sentinel-1 Single Look Complex (SLC) products without downloading entire scenes. This feature is particularly useful for InSAR time series analysis, regional studies, and efficient data access.

Key Benefits:

Access individual bursts instead of full SLC products (typically 1-2 GB per burst vs 5-8 GB per product)
Search by specific burst IDs for consistent time series
Filter by swath, polarization, and orbit parameters
Combine with spatial (AOI) and temporal filters
Available for data from August 2, 2024 onwards

What are Sentinel-1 Bursts?

Sentinel-1 SLC products are composed of multiple bursts - individual radar acquisitions captured during a satellite pass. Each burst represents a specific geographic area with the following characteristics:

Burst Properties:

Burst ID: Unique integer identifier for a specific burst location
Absolute Burst ID: Global unique identifier across all Sentinel-1 data
Swath: Part of the imaging swath (IW1, IW2, IW3 for Interferometric Wide; EW1-EW5 for Extra Wide)
Coverage: Each burst covers approximately 20-25 km in azimuth direction
Overlap: Adjacent bursts overlap to ensure continuous coverage

Parent Product Structure:

Sentinel-1 SLC Product (e.g., IW mode)
├── IW1 Swath
│   ├── Burst 1
│   ├── Burst 2
│   └── ...
├── IW2 Swath
│   ├── Burst 1
│   ├── Burst 2
│   └── ...
└── IW3 Swath
    ├── Burst 1
    ├── Burst 2
    └── ...

Getting Started 

Basic Burst Search 

To search for bursts, set burst_mode=True in the query_by_filter() method:

from phidown.search import CopernicusDataSearcher

# Create searcher instance
searcher = CopernicusDataSearcher()

# Search for bursts with temporal filter
searcher.query_by_filter(
    burst_mode=True,
    start_date='2024-08-01T00:00:00',
    end_date='2024-08-03T00:00:00',
    top=10,
    count=True
)

# Execute the query
df = searcher.execute_query()
print(f'Found {len(df)} bursts')
print(f'Total available: {searcher.num_results}')

# Display results
searcher.display_results(top_n=5)

Burst-Specific Parameters 

The following parameters are available exclusively in burst mode:

Core Identifiers 

Parameter	Type	Description
`burst_id`	int	Unique identifier for a specific burst location
`absolute_burst_id`	int	Global unique burst identifier across all Sentinel-1 data
`parent_product_id`	str	UUID of the parent SLC product
`parent_product_name`	str	Name of the parent SLC product (e.g., ‘S1A_IW_SLC__1SDV_…’)

Swath and Acquisition 

Parameter	Type	Description
`swath_identifier`	str	Swath name: ‘IW1’, ‘IW2’, ‘IW3’, ‘EW1’, ‘EW2’, ‘EW3’, ‘EW4’, ‘EW5’
`operational_mode`	str	Acquisition mode: ‘IW’ (Interferometric Wide), ‘EW’ (Extra Wide)
`parent_product_type`	str	Parent product type: ‘IW_SLC__1S’ or ‘EW_SLC__1S’

Polarization and Platform 

Parameter	Type	Description
`polarisation_channels`	str	Polarization: ‘VV’, ‘VH’, ‘HH’, ‘HV’
`platform_serial_identifier`	str	Sentinel-1 satellite: ‘A’ (Sentinel-1A), ‘B’ (Sentinel-1B)

Orbit Parameters 

Parameter	Type	Description
`relative_orbit_number`	int	Relative orbit number (1-175)
`datatake_id`	int	Datatake identifier

Common Use Cases 

1. InSAR Time Series Analysis 

Search for the same burst across multiple dates for interferometric analysis:

# Search for specific burst ID over time
searcher.query_by_filter(
    burst_mode=True,
    burst_id=15804,
    relative_orbit_number=8,
    orbit_direction='DESCENDING',
    start_date='2024-08-01T00:00:00',
    end_date='2024-09-01T00:00:00',
    top=100,
    count=True
)

df = searcher.execute_query()
print(f'Found {len(df)} acquisitions of burst 15804')

2. Regional Coverage Analysis 

Find all bursts covering a specific area of interest:

# Define area of interest
aoi_wkt = """POLYGON((12.4 41.8, 12.5 41.8,
                      12.5 41.9, 12.4 41.9,
                      12.4 41.8))"""

# Search for bursts intersecting AOI
searcher.query_by_filter(
    burst_mode=True,
    aoi_wkt=aoi_wkt,
    swath_identifier='IW2',
    polarisation_channels='VV',
    start_date='2024-08-01T00:00:00',
    end_date='2024-08-03T00:00:00',
    top=50
)

df = searcher.execute_query()

3. Parent Product Decomposition 

Retrieve all bursts from a specific SLC product:

# Get all bursts from a parent product
parent_product = 'S1A_IW_SLC__1SDV_20240802T060719_20240802T060746_055030_06B44E_E7CC.SAFE'

searcher.query_by_filter(
    burst_mode=True,
    parent_product_name=parent_product,
    start_date='2024-08-01T00:00:00',
    end_date='2024-08-15T00:00:00',
    top=1000
)

df = searcher.execute_query()
print(f'Parent product contains {len(df)} bursts')

4. Multi-Parameter Filtering 

Combine multiple criteria for precise searches:

# Advanced multi-parameter search
searcher.query_by_filter(
    burst_mode=True,
    burst_id=15804,
    swath_identifier='IW2',
    polarisation_channels='VV',
    orbit_direction='DESCENDING',
    relative_orbit_number=8,
    operational_mode='IW',
    platform_serial_identifier='A',
    start_date='2024-08-01T00:00:00',
    end_date='2024-08-15T00:00:00',
    count=True
)

df = searcher.execute_query()

Burst Result Structure 

Burst searches return DataFrames with the following columns:

Core Metadata:

Id: Unique burst identifier (UUID)
Name: Burst product name
ContentType: Content type identifier
S3Path: S3 storage path for the burst

Burst-Specific Fields:

BurstId: Burst ID (integer)
AbsoluteBurstId: Global burst identifier
SwathIdentifier: Swath name (IW1/IW2/IW3/EW1-EW5)
PolarisationChannels: Polarization (VV/VH/HH/HV)
OperationalMode: Acquisition mode (IW/EW)

Parent Product Information:

ParentProductId: Parent product UUID
ParentProductName: Parent SLC product name
ParentProductType: Parent product type

Orbit and Timing:

OrbitDirection: ASCENDING or DESCENDING
RelativeOrbitNumber: Relative orbit number
PlatformSerialIdentifier: Satellite (A or B)
ContentDate: Acquisition date/time
AzimuthTime: Azimuth time
AzimuthAnxTime: Azimuth time from ascending node crossing

Geometric Information:

Footprint: WKT footprint geometry
GeoFootprint: Geographic footprint
ByteOffset: Byte offset in parent product
Lines: Number of lines
LinesPerBurst: Lines per burst
SamplesPerBurst: Samples per burst

Temporal Coverage:

BeginningDateTime: Burst start time
EndingDateTime: Burst end time
DatatakeID: Datatake identifier

Combining with Standard Filters 

Burst mode works seamlessly with standard search parameters:

Temporal Filtering 

searcher.query_by_filter(
    burst_mode=True,
    start_date='2024-08-01T00:00:00',
    end_date='2024-08-31T23:59:59',
    # ... other burst parameters
)

Spatial Filtering (AOI)

searcher.query_by_filter(
    burst_mode=True,
    aoi_wkt='POLYGON((...)))',  # WKT polygon
    # ... other burst parameters
)

Orbit Direction 

searcher.query_by_filter(
    burst_mode=True,
    orbit_direction='DESCENDING',  # or 'ASCENDING'
    # ... other burst parameters
)

Result Pagination 

searcher.query_by_filter(
    burst_mode=True,
    top=1000,        # Maximum results to return
    count=True,      # Get total count
    order_by='ContentDate/Start desc',  # Sort order
    # ... other burst parameters
)

Best Practices 

Temporal Coverage
- Burst data is available from August 2, 2024 onwards
- Use count=True to check total available results before downloading
Burst ID Consistency
- Use the same burst_id across dates for time series analysis
- Combine with relative_orbit_number for guaranteed consistency
Swath Selection
- IW mode has 3 swaths (IW1, IW2, IW3)
- EW mode has 5 swaths (EW1, EW2, EW3, EW4, EW5)
- Central swath (IW2) often provides best coverage
Polarization
- VV polarization most common for IW mode
- Check available polarizations: ‘VV’, ‘VH’, ‘HH’, ‘HV’
Performance Optimization
- Use specific burst IDs when known
- Limit search with top parameter
- Apply swath and polarization filters to reduce results
Validation
- Always validate parameters are within allowed values
- Use count=True to verify result counts before processing
- Check searcher.num_results for total available bursts

API Endpoint 

Burst searches use a different endpoint than standard product searches:

Burst Endpoint:

https://catalogue.dataspace.copernicus.eu/odata/v1/Bursts

Product Endpoint (standard):

https://catalogue.dataspace.copernicus.eu/odata/v1/Products

The library automatically uses the correct endpoint based on the burst_mode parameter.

Examples Notebook 

A comprehensive Jupyter notebook with 9 detailed examples is available:

Location: notebooks/6_burst_search_examples.ipynb

Examples Include:

Basic burst search with temporal filter
Burst search with spatial filter (AOI)
Search by specific Burst ID
Filter by swath identifier and polarization
Search bursts from parent products
Orbit direction and relative orbit filtering
Advanced multi-parameter searches
Burst result analysis and statistics
Visualization of burst footprints

To run the examples:

cd notebooks
jupyter notebook 6_burst_search_examples.ipynb

Troubleshooting 

Common Issues 

Issue: No results returned

Check date range is after August 2, 2024
Verify AOI polygon format (WKT with EPSG:4326)
Confirm burst parameters are valid values

Issue: Invalid parameter error

Check swath_identifier is one of: IW1, IW2, IW3, EW1-EW5
Verify parent_product_type is: IW_SLC__1S or EW_SLC__1S
Ensure operational_mode is: IW or EW

Issue: Date format error

Use ISO 8601 format: YYYY-MM-DDTHH:MM:SS
Do not include .000Z suffix
Correct: '2024-08-01T00:00:00'
Incorrect: '2024-08-01T00:00:00.000Z'

Issue: Column not found in display_results()

Burst mode uses different columns than product mode
The library automatically selects appropriate columns
Or specify custom columns: searcher.display_results(columns=['BurstId', 'SwathIdentifier'])

Debugging 

Enable query debugging:

# View the generated query URL
print(searcher._build_query())

# Check what columns are available
if searcher.df is not None:
    print(searcher.df.columns.tolist())

# Verify burst mode is enabled
print(f'Burst mode: {searcher.burst_mode}')

API Reference 

For detailed API documentation, see:

API Reference - Complete API documentation
Sentinel-1 Reference Guide - Sentinel-1 general reference