TY  - Data
T1  - Heihe River eco hydrological remote sensing experiment: 30m / month synthetic leaf area index (LAI) data set of Heihe River Basin (2011-2014)
A1  - Liu qinghuo
A1  - Fan wenjie
A1  - Zhong bo
DO  - 10.12072/ncdc.nieer.db3542.2023
PY  - 2021
DA  - 2021-09-14
PB  - National Cryosphere Desert Data Center
AB  - The 30m / month synthetic leaf area index (LAI) data set of Heihe River basin provides the monthly Lai synthetic products from 2011 to 2014. The data uses the characteristics of domestic satellite HJ / CCD data with high temporal resolution (2 days after Networking) and spatial resolution (30M) to construct a multi angle observation data set, considering the influence of surface classification and terrain fluctuation, According to the characteristics of different vegetation types, the algorithm selects the appropriate parameterization scheme of the integrated model, and inverts the Lai based on the look-up table method. The monthly remote sensing data can provide more angles and more observations than the single day sensor data, but the quality of multi temporal and multi angle observation data is uneven due to the differences in the on orbit operation time and performance of the sensor. Therefore, in order to make effective use of multi temporal and multi angle observation data, a data quality inspection scheme is designed first. The Lai ground observation data of 9 forest quadrats, 20 farmland quadrats and 14 savanna quadrats in Dayekou area in the upper reaches of Heihe River and Yingke and Linze areas in the middle reaches of Heihe River are used 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 combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.9, RMSE = 0.42)In short, the 30m / month synthetic leaf area index (LAI) data set in Heihe River basin makes comprehensive use of multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products and better serve the application of remote sensing data products
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/09423505-1ee8-400a-a0ee-fa3ba652817c
ER  -