A multi-decadal assessment dataset of soil organic matter in the Sanjiang Plain black soil region (1984–2023)

Accurate estimation of soil organic matter (SOM) content in cultivated land is essential for food security and climate change mitigation. Here we present SOM-SJP-40y, a 40-year (1984-2023) dataset of topsoil SOM dynamics for the Sanjiang Plain, a typical black soil region in China. The dataset integrates 364 field samples (0-20 cm) with decadal median composites of bare soil imagery derived from Landsat time series on the Google Earth Engine platform. SOM predictions were generated using a probabilistic hybrid modeling approach combined with K-means clustering, achieving a model performance of R² = 0.72, RMSE = 8.66 g kg⁻¹, and RPD = 1.75. Using SOM-SJP-40y, we observe spatially heterogeneous SOM dynamics, with localized SOM increases in some areas since the 2010s that may be associated with recent conservation policies. This dataset offers a valuable resource for soil quality assessment, farmland protection, and carbon management in black soil regions.

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Publication Details

Journal
Scientific Data
Published
2026-05-09
DOI
https://doi.org/10.1038/s41597-026-07401-1
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
0.00

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article

A multi-decadal assessment dataset of soil organic matter in the Sanjiang Plain black soil region (1984–2023)

Chong Luo, Huanjun Liu, Yu Zhang
Scientific Data
Soil Geostatistics and Mapping
article

A multi-decadal assessment dataset of soil organic matter in the Sanjiang Plain black soil region (1984–2023)

Chong Luo, Huanjun Liu, Yu Zhang
article en

Abstract

Accurate estimation of soil organic matter (SOM) content in cultivated land is essential for food security and climate change mitigation. Here we present SOM-SJP-40y, a 40-year (1984-2023) dataset of topsoil SOM dynamics for the Sanjiang Plain, a typical black soil region in China. The dataset integrates 364 field samples (0-20 cm) with decadal median composites of bare soil imagery derived from Landsat time series on the Google Earth Engine platform. SOM predictions were generated using a probabilistic hybrid modeling approach combined with K-means clustering, achieving a model performance of R² = 0.72, RMSE = 8.66 g kg⁻¹, and RPD = 1.75. Using SOM-SJP-40y, we observe spatially heterogeneous SOM dynamics, with localized SOM increases in some areas since the 2010s that may be associated with recent conservation policies. This dataset offers a valuable resource for soil quality assessment, farmland protection, and carbon management in black soil regions.

Scientific Data
Chinese Academy of Sciences (CN), Northeast Institute of Geography and Agroecology (CN), Northwest Institute of Eco-Environment and Resources (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 8%
Soil Geostatistics and Mapping
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