Spatial Distribution Characteristics of Soil Organic Carbon Under Different

Description

Description of Data This dataset includes soil organic carbon (SOC) content measurements from 95 sampling points across Dali County, China, collected at five soil depths (0–10 cm, 10–20 cm, 20–40 cm, 40–60 cm, and 60–100 cm). Data were obtained through field surveys and laboratory analyses using the potassium dichromate oxidation method. The dataset also incorporates land use types (cropland, garden land, forest land, and grassland) and spatial autocorrelation analysis results derived from geostatistical methods. Key findings include: SOC content decreased with soil depth, showing a pronounced epipedon phenomenon. Strong spatial autocorrelation was observed at 10–20 cm, 20–40 cm, and 60–100 cm depths, driven by structural factors. Cropland and garden land were the dominant carbon sinks, contributing significantly to regional carbon stocks. The data can be used to understand SOC spatial distribution, identify high carbon sequestration areas, and support land use optimization for carbon neutrality goals. The dataset is available in Excel format, including SOC measurements and land use classifications.

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The dataset includes SOC content measurements from 95 sampling points across Dali County, collected at five soil depths: 0–10 cm, 10–20 cm, 20–40 cm, 40–60 cm, and 60–100 cm. The data were obtained through field surveys and laboratory analyses using the potassium dichromate oxidation method (K₂Cr₂O₇-H₂SO₄). Additionally, the dataset incorporates land use types (cropland, garden land, forest land, and grassland).

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