Digital Heihe

HiWATER: 30m month compositing Leaf Area Index (LAI) product of the Heihe River Basin

The 30 m / month synthetic leaf area index (LAI) data set of Heihe River basin provides the monthly Lai synthetic products from 2011 to 2014. This data uses the domestic satellite HJ / CCD data with high time resolution (2 days after Networking) and spatial resolution (30 m) to construct the multi angle observation data set. Considering the impact of surface classification and terrain fluctuation, the algorithm is selected according to the characteristics of different vegetation types Choosing a suitable parameterization scheme of integrated model, inversion Lai based on look-up table method. 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 multi temporal and multi angle observation data, a data quality inspection scheme is designed. Using the Lai ground observation data of 9 forest quadrats, 20 farmland quadrats and 14 savanna quadrats from dayokou area in the upper reaches of Heihe River and Yingke and Linze areas in the middle reaches to verify the Lai in July, the inversion results are in good agreement with the measurement results, and the average error is less than 1; in addition, the Lai inversion results of the combined multi temporal and multi angle observation data are in good agreement with the ground measurement data （R2=0.9，RMSE=0.42）。 In a word, the 30 m / month synthetic leaf area index (LAI) 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 better serve the application of remote sensing data products.

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Related Literatures:

1. Liao, Y. , Fan, W. , & Xu, X. . (2013). Algorithm of leaf area index product for HJ-CCD over Heihe River Basin. IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE.(View Details)

2. Zhao J, Li J, Liu QH, et al. Leaf Area Index Retrieval Combining HJ1/CCD and Landsat8/OLI Data in the Heihe River Basin, China. Remote sensing, 2015, 7(6): 6862-6885.(View Details |Download )

3. 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 )

Cite as:

Liu, Q., Fan, W., Zhong, B. (2016). < b>HiWATER: 30m month compositing Leaf Area Index (LAI) product of the Heihe River Basin</b>2016. doi: 10.3972/hiwater.288.2016.db. (Download the reference： RIS | Bibtex )

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References literature

1.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)

2.Fan W, Yan B, Xu X. Crop area and leaf area index simultaneous retrieval based on spatial scaling transformation. Sci. China Earth Sci., 2010, 53: 1709–1716. (View Details |Download)

3.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 )

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