Quick Overview#

This section provides brief examples of using icesat2db.IceSat2Processor and icesat2db.IceSat2Provider to process and query IceSat2 data. For advanced features and detailed use cases, refer to the icesat2DB Fundamentals.

Start by importing the icesat2db package:

import icesat2db as isdb
import concurrent.futures

Processing ICESat-2 Data#

To process ICESat-2 data, specify paths to a YAML configuration file (config_file). See Configuration files for more information on the data configuration files.

This setup initiates the download, processing, and storage of ICESat-2 data in your database.

# Paths to configuration files
config_file = 'path/to/config_file.yml'
geometry = 'path/to/test.geojson'

# Initialize a parallel engine
concurrent_engine= concurrent.futures.ThreadPoolExecutor(max_workers=10)

# Initialize the IceSat2Processor and compute
with isdb.IceSat2Processor(
    config_file=config_file,
    geometry=geometry,
    start_date='2020-01-01',
    end_date='2020-12-31',
    earth_data_dir= '/path/to/earthdata_credential/folder',
    parallel_engine=concurrent_engine,
) as processor:
    processor.compute(consolidate=True)

In this example, the icesat2db.IceSat2Processor performs:

  • Downloading ICESat-2 ATL08 product.

  • Filtering data by quality.

  • Storing the processed data in the tileDB database.

Querying ICESat-2 Data#

Once the data is processed and stored, use icesat2db.IceSat2Provider to query it. The results can be returned in either Xarray or Pandas format, providing flexibility for various workflows.

Example query using icesat2db.IceSat2Provider:

import geopandas as gpd
import icesat2db as gdb

# Create IceSat2Provider instance
provider = gdb.IceSat2Provider(storage_type='local',
                            local_path= "path/to/your/database/")

# Load region of interest
region_of_interest = gpd.read_file('./data/geojson/BR-Sa1.geojson')

# Define the columns to query and additional parameters
vars_selected = ["brightness_flag"]

# Profile the provider's `get_data` function
icesat2_data = provider.get_data(
    variables=vars_selected,
    query_type="bounding_box",
    geometry=region_of_interest,
    start_time="2018-01-01",
    end_time="2024-07-25",
    return_type='xarray'
)

This provider.get_data() function allows you to:

  • Select specific columns (e.g., brightness_flag).

  • Apply spatial and temporal filters using geometry, start_time, and end_time.

  • Return data in either xarray or pandas format based on return_type.

This functionality offers a flexible, scalable approach to querying ICESat-2 data, streamlining its integration into your data workflows.

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