Comparing geospatial techniques to predict SOC stocks

@inproceedings{Liu2015ComparingGT,
  title={Comparing geospatial techniques to predict SOC stocks},
  author={Yaolin Liu and Long Guo and Qinghu Jiang and Haitao Zhang and Yiyun Chen},
  year={2015}
}
Soil organic carbon density (SOCD) has strong spatial variability and dependency, and its impact factors vary with changes in scale and geographic location. With 272 topsoil samples (0–30 cm) collected from Chahe Town in the Jianghan Plain, China, we (i) investigated the impacts of environmental variables and land cover types on the spatial distribution of SOCD; (ii) estimated the spatial distribution of SOCD by using global and local spatial interpolation models, including geographically… CONTINUE READING

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