CYGNSS: Soil Moisture Estimates at 6-Hour Resolution from Satellite Reflectivity

CYGNSS Level 3 Soil Moisture Version 3.2 provides volumetric water content estimates for soils between 0-5 cm depth. The dataset is derived from NASA's CYGNSS satellite constellation reflectivity measurements, processed using a linear regression trained against SMAP data. It offers daily files with 9 km and 36 km gridding resolutions, covering subtropical regions from August 2018 to present.

Use Cases

• Modeling soil moisture dynamics for climate studies based on 6-hour discretization data.
• Analyzing land surface hydrology patterns based on gridded volumetric water content estimates.
• Training machine learning models for agricultural water management based on satellite-derived soil moisture.
• Monitoring environmental changes in subtropical regions based on the dataset's spatial coverage.
• Comparing satellite soil moisture products based on the algorithm trained against SMAP data.

Strengths

• Provides soil moisture estimates at two specific spatial resolutions: 9x9 km and 36x36 km.
• Offers data at a defined temporal resolution with six-hour intervals and daily averages.
• Coverage spans a specific time period from August 2018 to present.
• Algorithm is based on a calibration period from 8/1/2018 to 11/15/2023 using SMAP data.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Geographic coverage is limited to 'most of the subtropics', which may introduce spatial bias.

Provenance

Source

CYGNSS Science Team of the University of Michigan and NASA.

Collection Method

Derived from CYGNSS L1 SDR reflectivity measurements using a linear regression algorithm trained against SMAP soil moisture.

Time Range

August 2018 to present.

Freshness

Last updated 2026-03-13 03:19:08.768792; freshness should be verified.

Geography

Most of the subtropics.