Multi-frequency and multi-angular ground-based microwave radiometer and radar cooperative experimental data for grassland in 2018- A Big Earth Data Platform for Three Poles

This data set was collected in 2018 during the ground-based microwave radiometry and radar cooperative experiment, which is part of the Soil Moisture Experiment in the Luan River (SMELR). The experiment site is located in Zhenglan Banner, Inner Mongolia (115.93° E, 42.04° N, at 1362 m in altitude). The data set contains four parts, namely brightness temperature data, radar backscatter coefficient, soil data and vegetation data. The microwave brightness temperature data was observed by a vehicle-mounted dual-polarized multi-frequency radiometer (RPG-6CH-DP), including the horizontal (H) and vertical (V) polarization brightness temperatures at L-, C- and X-bands. The brightness temperature data was acquired every 30 minutes from 30° to 65° with an interval of 2.5°. The active microwave data is obtained by ground-based synthetic aperture radar (GBSAR), including the L- and C-band backscattering coefficients under four polarization modes (VV, VH, HH, HV), and the incidence varies from 30° to 65° (2.5° interval). The soil data contains the surface roughness, soil moisture and temperature at six depths of layer (1 cm, 3 cm, 5 cm, 10 cm, 20 cm, 50 cm). The vegetation data is mainly the vegetation water content of the grassland.

The experimental period lasted from August 18 to September 25, 2018, and it provided important data for the land surface microwave radiation modeling and validation, as well as the development of soil moisture retrieval algorithms.

File naming and required software

The data file is saved in xlsx format and is named as: ZhenglanqiExp+ '_ParaName'. 'ParaName' represents the abbreviation of the observed parameter. For example, the brightness temperature is named as 'ZhenglanqiExp_TB.xlsx', the soil data set is named as 'ZhenglanqiExp_Soil.xlsx' .
Data reading method: The data set can be directly opened with Excel.

Data Citations Data citation guideline What's data citation?

Cite as:

Zhao, T., Hu, L., Geng, D., Shi, J. (2021). Multi-frequency and multi-angular ground-based microwave radiometer and radar cooperative experimental data for grassland in 2018. A Big Earth Data Platform for Three Poles, DOI: 10.11888/Soil.tpdc.271656. CSTR: 18406.11.Soil.tpdc.271656. (Download the reference： RIS | Bibtex )

Related Literatures:

1. 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)

2. Zhao, T.J., Shi, J.C., Entekhabi, D., Jackson, T.J., Hu, L., Peng, Z.Q., Yao, P.P., Li, S.N., & Kang, C.S. (2021). Retrievals of soil moisture and vegetation optical depth using a multi-channel collaborative algorithm. Remote Sensing of Environment, 257, 112321.( View Details | Bibtex)

3. Zhao, T.J., Shi, J.C., Xu, H.X., Sun, Y.L. Chen, D.Q, Cui, Q., Jia, L., Huang, S., Niu, S.D., Li, X.W., Yan, G.J.,Chen, F.L., Liu, Q.H. 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., Mu, X.H., 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., Hu, J.F., & Du, A.P. (2021). Comprehensive remote sensing experiment of water cycle and energy balance in the Shandian river basin. Journal of Remote Sensing, 25(4), 871-887.( View Details | Bibtex)

4. 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)

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

Support Program

Satellite observation and simulation studies of the land surface water and energy exchange processes and its effects on global changes (No:2015CB953700)

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)