The 30 m / month vegetation index (NDVI / EVI) data set of Heihe River basin provides the monthly NDVI / EVI composite products from 2011 to 2014. This data uses the characteristics of HJ / CCD data of China's domestic satellite, which has both high time resolution (2 days after Networking) and spatial resolution (30 m), to construct multi angle observation data set. The average composite MC method is used as the main algorithm for synthesis, and the backup algorithm uses VI method. At the same time, the main observation angles of the multi-source data set are used as part of the quality descriptor to help analyze the angle effect of the composite vegetation index residue. The remote sensing data acquired every month can provide more angles and more observations than the single day sensor data, but the quality of multi-phase and multi angle observation data is uneven due to the difference of on orbit operation time and performance of the sensor. Therefore, in order to effectively use the multi-temporal and multi angle observation data, before using the multi-source data set to synthesize the vegetation index, the algorithm designs the data quality inspection of the multi-source data set, removing the observation with large error and inconsistent observation. The verification results in the middle reaches of Heihe River show that the NDVI / EVI composite results of the combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.89, RMSE = 0.092). In a word, the 30 m / month NDVI / EVI data set of Heihe River Basin comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, so as to realize the stable standardized products from scratch and better serve the application of remote sensing data products.

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Li, J., Liu, Q., Zhong, B., Wu, J., Wu, S. (2016). HiWATER: 30m month compositing vegetation index (NDVI/EVI) product of Heihe River Basin (2011-2014). A Big Earth Data Platform for Three Poles, DOI: 10.3972/hiwater.295.2016.db. CSTR: 18406.11.hiwater.295.2016.db. (Download the reference： RIS | Bibtex )

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1. Li, X., Liu, S.M., Xiao, Q., Ma, M.G., Jin, R., Che, T., Wang, W.Z., Hu, X.L., Xu, Z.W., Wen, J.G., Wang, L.X. (2017). A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system. Scientific Data, 4, 170083. doi:10.1038/sdata.2017.83.( View Details | Download | Bibtex)

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References literature

1.Long, X., Li, J., Liu, Q. (2013). Review on VI Compositing Algorithm. Remote Sensing Technology and Application, 28(6), 969–977. (View Details | Download )

2.Li Xin, Liu Shaomin, Ma Mingguo, Xiao Qing, Liu Qinhuo, Jin Rui, Che Tao. HiWATER: An Integrated Remote Sensing Experiment on Hydrological and Ecological Processes in the Heihe River Basin. Advances in Earth Science, 2012, 27(5): 481-498. (View Details | Download )

3.Long, X. (2013). Study on Vegetation Compositing Algorithm from Multi-sensor Remote Sensing Data. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China. (View Details | Download )

4.Li X, Cheng GD, Liu SM, Xiao Q, Ma MG, Jin R, Che T, Liu QH, Wang WZ, Qi Y, Wen JG, Li HY, Zhu GF, Guo JW, Ran YH, Wang SG, Zhu ZL, Zhou J, Hu XL, Xu ZW. Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific objectives and experimental design. Bulletin of the American Meteorological Society, 2013, 94(8): 1145-1160, 10.1175/BAMS-D-12-00154.1. (View Details )

Support Program

The CAS (Chinese Academy of Sciences) Action Plan for West Development Project (No:KZCX2-XB3-15)

National High-tech R&D Program of China (863 Program) (No:2012AA12A304)

National High-tech R&D Program of China (863 Program) (No:2013AA12A301)

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