A spatially explicit dataset of soil organic carbon across 0–100 cm under contrasting urban land-use types in Zhengzhou, China (2022–2023)

Description

This dataset provides a spatially explicit characterization of soil organic carbon (SOC) across contrasting urban land-use types in Zhengzhou, collected between June 2022 and April 2023. A total of 64 georeferenced sampling sites were established under three representative land-use categories, including impervious (closed) soils (n = 20), urban green spaces (n = 28), and suburban croplands (n = 16). At each site, soil profiles were sampled at five depth intervals (0–20, 20–40, 40–60, 60–80, and 80–100 cm), yielding 320 soil samples in total. All samples were processed following standardized protocols, including air-drying, removal of visible roots and debris, grinding, and sieving prior to SOC determination using consistent laboratory methods. The dataset includes SOC concentrations (g·kg⁻¹), geographic coordinates (latitude and longitude), land-use classification, and depth information, enabling integrated analyses of vertical distribution and three-dimensional spatial variability. Geostatistical analyses, including semivariogram modeling and ordinary kriging interpolation implemented in ArcGIS, reveal pronounced spatial heterogeneity and depth-dependent patterns of SOC across the urban landscape. Croplands exhibit the highest SOC levels, followed by urban green spaces and impervious soils, reflecting the combined effects of land-use intensity, vegetation inputs, and anthropogenic disturbance. This dataset provides a robust empirical foundation for investigating urban soil carbon dynamics, validating spatial prediction models, and supporting carbon management strategies in rapidly urbanizing regions.

Institutions

• Henan University

  Henan, Kaifeng

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