SMAP soil moisture (NASA Earthdata)¶

Download a daily SMAP enhanced L3 radiometer soil-moisture granule from the NSIDC DAAC and map the morning (AM) retrieval. The granule is an HDF5 raster on the EASE-2 grid.

This is a live query — it needs the [earthdata] extra and Earthdata Login (EDL) credentials. Each step is wrapped in a try/except so the notebook stays nbval-lax safe and skips gracefully offline.

Setup¶

Imports and an output directory for the downloaded granule. earthlens provides the unified EarthLens entry point; Path gives us a tidy place to write the HDF5 file.

In [ ]:

from pathlib import Path

from earthlens import EarthLens

OUT_DIR = Path('earthdata_output')
OUT_DIR.mkdir(exist_ok=True)

from pathlib import Path from earthlens import EarthLens OUT_DIR = Path('earthdata_output') OUT_DIR.mkdir(exist_ok=True)

Download the granule¶

Build the request¶

We describe the granule we want — the SPL3SMP_E_006 enhanced L3 product, the soil_moisture variable, a single day, and a global bounding box. Earthdata is a raster backend, so we use download() to write the granule to disk.

In [ ]:

smap = EarthLens(
    data_source='earthdata',
    dataset='SPL3SMP_E_006',
    variables=['soil_moisture'],
    start='2023-06-01',
    end='2023-06-01',
    aoi=[-180.0, -90.0, 180.0, 90.0],
    path=str(OUT_DIR),
)

smap = EarthLens( data_source='earthdata', dataset='SPL3SMP_E_006', variables=['soil_moisture'], start='2023-06-01', end='2023-06-01', aoi=[-180.0, -90.0, 180.0, 90.0], path=str(OUT_DIR), )

Fetch it¶

download() runs the live NSIDC query and returns the list of written paths. The whole call is guarded so a missing [earthdata] extra or absent EDL credentials just prints a skip message instead of raising.

In [ ]:

paths = None
try:
    paths = smap.download(progress_bar=False)
    print(len(paths), 'granule(s):', [Path(p).name for p in paths])
except Exception as exc:
    print(f'skipped live query: {type(exc).__name__}: {exc}')

paths = None try: paths = smap.download(progress_bar=False) print(len(paths), 'granule(s):', [Path(p).name for p in paths]) except Exception as exc: print(f'skipped live query: {type(exc).__name__}: {exc}')

Map the AM retrieval¶

If the download succeeded, read the morning (AM) soil-moisture array out of the HDF5 granule, mask the fill values, and map it. This step is wrapped too, so it skips cleanly when the granule is missing or the plotting deps are unavailable.

In [ ]:

if paths:
    try:
        import h5py
        import matplotlib.pyplot as plt
        import numpy as np

        with h5py.File(paths[0], 'r') as h5:
            sm = h5['Soil_Moisture_Retrieval_Data_AM/soil_moisture'][:]
        sm = np.where(sm < 0, np.nan, sm)
        fig, ax = plt.subplots(figsize=(10, 5))
        im = ax.imshow(sm, cmap='YlGnBu', vmin=0, vmax=0.5)
        fig.colorbar(im, ax=ax, label='Soil moisture (cm3/cm3)')
        ax.set_title('SMAP enhanced L3 soil moisture (AM), 2023-06-01')
        plt.tight_layout()
        plt.show()
    except Exception as exc:
        print(f'read/plot step skipped: {type(exc).__name__}: {exc}')

if paths: try: import h5py import matplotlib.pyplot as plt import numpy as np with h5py.File(paths[0], 'r') as h5: sm = h5['Soil_Moisture_Retrieval_Data_AM/soil_moisture'][:] sm = np.where(sm < 0, np.nan, sm) fig, ax = plt.subplots(figsize=(10, 5)) im = ax.imshow(sm, cmap='YlGnBu', vmin=0, vmax=0.5) fig.colorbar(im, ax=ax, label='Soil moisture (cm3/cm3)') ax.set_title('SMAP enhanced L3 soil moisture (AM), 2023-06-01') plt.tight_layout() plt.show() except Exception as exc: print(f'read/plot step skipped: {type(exc).__name__}: {exc}')