Prediction of regional cropland soil organic carbon content and distribution using deep learning: a case study of the Northeast China Plain.

Zhang S, Dai H, Chen C, Wei J, Guan Z, Niu X

DOI: 10.1007/s10661-025-14622-1
Published: 2025 Sep 29
Container: Environmental monitoring and assessment
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1007/s10661-025-14622-1,
  title = {Prediction of regional cropland soil organic carbon content and distribution using deep learning: a case study of the Northeast China Plain.},
  author = {Zhang S and Dai H and Chen C and Wei J and Guan Z and Niu X},
  year = {2025},
  journal = {Environmental monitoring and assessment},
  doi = {10.1007/s10661-025-14622-1},
  url = {https://doi.org/10.1007/s10661-025-14622-1}
}

RIS

TY  - JOUR
TI  - Prediction of regional cropland soil organic carbon content and distribution using deep learning: a case study of the Northeast China Plain.
AU  - Zhang S
AU  - Dai H
AU  - Chen C
AU  - Wei J
AU  - Guan Z
AU  - Niu X
PY  - 2025
JO  - Environmental monitoring and assessment
DO  - 10.1007/s10661-025-14622-1
UR  - https://doi.org/10.1007/s10661-025-14622-1
ER  -

APA

S, Z., H, D., C, C., J, W., Z, G., & X, N. (2025). Prediction of regional cropland soil organic carbon content and distribution using deep learning: a case study of the Northeast China Plain.. Environmental monitoring and assessment. https://doi.org/10.1007/s10661-025-14622-1

Source records

pubmed · retrieved 2026-09-26T21:49:20.027Z
europe-pmc · retrieved 2026-09-26T21:49:20.037Z