This vegetation water content data set is derived from the ground synchronous observation in the Luanhe River Basin soil moisture remote sensing experiment, including 55 sampled plots.The vegetation types involved in these sampled plots include grass, corn, potatoes, naked oats and carrots. The data measurement time is from September 13, 2018 to September 26, 2018.

File naming and required software

File name: Vegetation water content data is stored in Excel format, including "North-South flight line. xlsx", "Southwest-Northeast flight line. xlsx" and "microwave radiometer. xlsx".

Data reading method: directly use Excel software to read.

Data reading method: Excel.

Data Citations Data citation guideline What's data citation?

Cite as:

Zheng, X., Jiang, T. (2021). Ground-based dataset of vegetation water content in Shandian watershed (2018). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Ecolo.tpdc.271668. CSTR: 18406.11.Ecolo.tpdc.271668. (Download the reference： RIS | Bibtex )

Related Literatures:

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2. Yan, G.J., Zhao, T.J., Mu, X.H., Wen, J.G., Pang, Y., Zhang, Y.G., Chen, D.Q., Yao, C.Z., Cao, Z.Y., Lei, Y.H., Ji, D.B., Chen, L.F., Liu, Q.H., Lv, L.Q., Chen, J.M., & Shi, J.C. (2021). Comprehensive remote sensing experiment of carbon cycle, water cycle and energy balance in Luan River Basin. Journal of Remote Sensing, 25(4), 856-870.( View Details | Bibtex)

3. Zhao, T.J., Shi, J.C., Lv, L.Q., Xu, H.X., Chen, D.Q., Cui, Q., Jackson, T.J., Yan, G.J., Jia, L., Chen, L.F., Zhao, K., Zheng, X.M., Zhao, L.M., Zheng, C.L., Ji, D.B., Xiong, C., Wang, T.X., Li, R., Pan, J.M., Wen, J.G., Yu, C., Zheng, Y.M., Jiang, L.M., Chai, L.N., Lu, H., Yao, P.P., Ma, J.W., Lv, H.S., Wu, J.J., Zhao, W., Yang, N., Guo, P., Li, Y.X., Hu, L., Geng, D.Y., & Zhang, Z.Q. (2020). Soil moisture experiment in the Luan River supporting new satellite mission opportunities. Remote Sensing of Environment, 240.( View Details | Download | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)