A global 400-m high-resolution soil moisture dataset derived from multi-sensor remote sensing observations.

Bin Fang, Venkataraman Lakshmi, Christopher Hain, Vikalp Mishra

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In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Bin FangDepartment of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA, 22902, USA. bf3fh@virginia.edu.ORCID http://orcid.org/0000-0002-0448-7616

Venkataraman LakshmiDepartment of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA, 22902, USA.

Christopher HainNational Aeronautics and Space Administration, Marshall Space Flight Center, Huntsville, AL, 35808, USA.

Vikalp MishraNASA Short-term Prediction Research and Transition (SPoRT) Center, MSFC, Huntsville, USA.

Funding

NASA | Goddard Space Flight Center (NASA's Goddard Space Flight Center) 80NSSC19K0993

6 · The paper itself

Abstract

Soil Moisture (SM) has been monitored by satellite remote sensing for the past five decades. Among recent missions, the Soil Moisture Active Passive (SMAP) mission, launched by the National Aeronautics and Space Administration's (NASA), has been providing high-quality global SM observations from an L-band passive microwave radiometer with a revisit time of 1-2 days, although its spatial resolution remains on the order of tens of kilometers. To address this limitation, an algorithm was developed and applied to downscale the SMAP enhanced Level-2 radiometer half-orbit SM product from 9 km to 400 m resolution by incorporating land surface temperature (LST) and leaf area index (LAI) products from the Visible Infrared Imaging Radiometer Suite (VIIRS). The 400 m downscaled SM product was validated against in situ observations acquired from the International Soil Moisture Network (ISMN) and compared with both 1 km downscaled and original 9 km SMAP products. Overall, the 400 m product outperformed the other two in terms of Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). It also revealed finer-scale spatial patterns of SM supporting local and regional hydrological applications.

Identifiers

PMID41392295

DOI10.1038/s41597-025-06356-z

PMCPMC12820223

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LicenceCC BY-NC-ND

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.