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File naming and required software

File Naming Convention: Daily：YYYDOY_YYYYMMDD_daily_ET.tif (YYYY: year, DOY: Day of the year, MM: month, DD: day), as follow: 2013001_20130101_ET_daily.tif. Monthly: YYYY_MM_ET_monthly.tif (YYYY: year, MM: month), as follow: 2013_01_ET_monthly.tif. Year: YYYY_ET_yearly.tif (YYYY: year), as follow: 2013_ET_yearly.tif.
Projection: WGS_1984_UTM_Zone_47N;
Data Format, Size and Data type: GeoTIFF, 5505 rows*4027 columns and float;
Unit: daily (mm/day), monthly(mm/month), yearly(mm/year);
Data Version：Version 1.0.

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Data Citations Data citation guideline What's data citation?

Cite as:

Ma, Y., Liu, S. (2020). High-Temporal and Landsat-Like surface evapotranspiration in Heihe River Basin (2010-2016) (HiTLL ET V1.0). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Hydro.tpdc.271081. CSTR: 18406.11.Hydro.tpdc.271081. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Ma, Y.F., Liu, S.M., Song, L.S., Xu, Z.W., Liu, Y.L., Xu, T.R., Zhu, Z.L. (2018). Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data. Remote Sensing of Environment, 216, 715-734. doi:10.1016/j.rse.2018.07.019.( View Details | Bibtex)

2. Liu, S., Li, X., Xu, Z., Che, T., Xiao, Q., Ma, M., Liu, Q., Jin, R., Guo, J., Wang, L., Wang, W., Qi, Y., Li, H., Xu, T., Ran, Y., Hu, X., Shi, S., Zhu, Z., Tan, J., Zhang, Y., Ren, Z. (2018). The Heihe Integrated Observatory Network: A basin‐scale land surface processes observatory in China. Vadose Zone Journal, 17,180072. https://doi.org/10.2136/vzj2018.04.0072.( View Details | Bibtex)

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

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References literature

1.Li, X., Liu, S., Li, H., Ma, Y., Wang, J., Zhang, Y., Xu, Z., Xu, T., Song, L., Yang, X., Lu, Z., Wang, Z., Guo, Z. (2018). Intercomparison of six upscaling evapotranspiration methods: From site to the satellite pixel. Journal of Geophysical Research: Atmospheres, 123(13), 6777-6803. https://doi.org/10.1029/2018JD028422. (View Details )

2.Xu, T., Guo, Z., Liu, S., He, X., Meng, Y., Xu, Z., Xia, Y., Xiao, J., Zhang, Y., Ma, Y., Song, L. (2018). Evaluating different machine learning methods for upscaling evapotranspiration from towers to the regional scale. Journal of Geophysical Research: Atmospheres, 123(16), 8674-8690. https://doi.org/10.1029/2018JD028447. (View Details )

3.Liu, S., Xu, Z., Song, L., Zhao, Q., Ge, Y., Xu, T., Ma, Y., Zhu, Z., Jia, Z., Zhang, F. (2016). Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology, 230-231, 97-113. https://doi.org/10.1016/j.agrformet.2016.04.008. (View Details )

4.Xu, Z., Ma, Y., Liu, S., Shi, W., Wang, J., 2017. Assessment of the energy balance closure under advective conditions and its impact using remote sensing data. Journal of Applied Meteorology and Climatology, 56 (1), 127–140. https://doi.org/10.1175/JAMC-D-16-0096.1. (View Details )

5.Ma, Y., Liu, S., Zhang, F., Zhou, J., Jia, Z., Song, L., 2015. Estimations of regional surface energy fluxes over heterogeneous oasis–desert surfaces in the middle reaches of the Heihe River during HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 12 (3), 671–675. https://doi.org/10.1109/LGRS.2014.2356652. (View Details )

6.Su, Z. (2002). The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Sciences, 6 (1), 85–100. https://doi.org/10.5194/hess-6-85-2002. (View Details )

7.Jia, L., Su, Z., van den Hurk, B., Menenti, M., Moene, A., De Bruin, H.A., Yrisarry, J.J.B., Ibanez, M., Cuesta, A. (2003). Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements. Physics and Chemistry of the Earth, Parts A/B/C, 28 (1–3), 75–88. https://doi.org/10.1016/S1474-7065(03)00009-3. (View Details )

8.He, J., Yang, K., Tang, W. Lu, H., Qin, J., Chen, Y.Y., Li, X. (2020). The first high-resolution meteorological forcing dataset for land process studies over China. Scientific Data, 7, 25, https://doi.org/10.1038/s41597-020-0369-y. (View Details )

9.Yang, K., He, J.,Tang, W.J., Qin, J., Cheng, C.C.K. (2010). On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau. Agricultural and Forest Meteorology, 150(1), 38-46. https://doi.org/10.1016/j.agrformet.2009.08.004. (View Details )

10.YANG Kun, HE Jie. China meteorological forcing dataset (1979-2018). National Tibetan Plateau Data Center, 2019. DOI: 10.11888/Atmosp hericPhysics.tpe.249369.file. CSTR: 18046.11.AtmosphericPhysics.tpe.249369.file. (View Details )

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Support Program

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)

Youth Program of National Natural Science Foundation of China (grant number: 41701426)

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.

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

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