TY  - Data
T1  - Heihe River eco hydrological remote sensing test: 1km / 5-day synthetic leaf area index (LAI) data set of Heihe River Basin (2015)
A1  - Zhao Jing
A1  - Zhong bo
A1  - Wu junjun
DO  - 10.12072/ncdc.nieer.db3553.2023
PY  - 2021
DA  - 2021-09-14
PB  - National Cryosphere Desert Data Center
AB  - The 2015 1km / 5-day synthetic leaf area index (LAI) data set of Heihe River basin provides the 5-day Lai synthesis results in 2015. The data uses Terra / MODIS, Aqua / MODIS, domestic satellites fy3a / MERSI and fy3b / MERSI sensor data to build a multi-source remote sensing data set with spatial resolution of 1km and temporal resolution of 5 days Multi-source remote sensing data sets can provide more angles and more observations than a single sensor in a limited time. However, the observation quality of multi-source data sets is uneven due to the difference of on orbit running time and performance of sensors. Therefore, in order to make more effective use of multi-source data sets, the algorithm first classifies the quality of multi-source data sets, which are divided into primary data, secondary data and tertiary data according to the observation rationality.Level III data are observations polluted by thin clouds and are not used for calculation. The purpose of quality evaluation and classification is to provide basis for the selection of optimal data set and the design of inversion algorithm flow in Lai inversion. The inversion algorithm of leaf area index product is designed to distinguish mountain and flat land and vegetation types, and the neural network method of different models is used for inversion.Based on global DEM map and surface classification map, PROSAIL model is adopted for continuous vegetation such as grassland and crops, and slope gost model is adopted for forest and mountain vegetation. The reference map generated by using the ground measured data of forests in the upper reaches of Heihe River and oases in the middle reaches of Heihe River, and the corresponding high-resolution reference map is scaled up to 1km resolution. Compared with Lai products, the products have good correlation between farmland and forest areas and the reference value, and the overall accuracy basically meets the accuracy threshold that the error specified by GCOS does 
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/5abf078f-5fc0-498d-9cdc-4fe9af31943b
ER  -