The vegetation phenological data set of Heihe River basin provides remote sensing phenological products from 2012 to 2015. The spatial resolution is 1km and the projection type is sinusoidal projection. The data is extracted using MODIS Lai product mod15a2 as phenological remote sensing monitoring data source and MODIS land cover classification product mcd12q1 as auxiliary data set
Firstly, the product algorithm uses the time series data reconstruction method (bise method) to control the data quality of the input time series; Then the vegetation phenological parameters are extracted by the combination of the main algorithm (logistic function fitting method) and the standby algorithm (piecewise linear fitting method), so as to realize the complementarity of the algorithm, ensure the accuracy and improve the inversion rate. The algorithm can extract up to three growth cycles in a year. Each growth cycle contains 6 data sets, including vegetation growth start point, growth peak start point, growth peak end point, growth end point, fastest growth and fastest fading. At the same time, 25 data sets are recorded, such as growth cycle type, growth season length and quality identification. The phenological product reduces the inversion missing rate and improves the product stability. The data set is rich in information and is relatively reliable
The data is extracted using MODIS Lai product mod15a2 as phenological remote sensing monitoring data source and MODIS land cover classification product mcd12q1 as auxiliary data set
Firstly, the product algorithm uses the time series data reconstruction method (bise method) to control the data quality of the input time series; Then the vegetation phenological parameters are extracted by the combination of the main algorithm (logistic function fitting method) and the standby algorithm (piecewise linear fitting method), so as to realize the complementarity of the algorithm, ensure the accuracy and improve the inversion rate
The algorithm can extract up to three growth cycles in a year. Each growth cycle contains 6 data sets, including vegetation growth start point, growth peak start point, growth peak end point, growth end point, fastest growth and fastest fading. At the same time, 25 data sets are recorded, such as growth cycle type, growth season length and quality identification. The phenological product reduces the inversion missing rate and improves the product stability. The data set is rich in information and is relatively reliable
Good data quality
| # | number | name | type |
| 1 | 2012AA12A304 | National Natural Science Foundation of China | |
| 2 | 2013AA12A301 | National High-tech R&D Program of China (863 Program) |
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CSTR:11738.11.ncdc.nieer.2020.1637
10.12072/ncdc.nieer.db3564.2023