This data set is hyperspectral observation data of typical vegetation along Sichuan Tibet Railway in September 2019, using the airborne spectrometer of Dajiang M600 resonon imaging system. Including the hyperspectral data observed in the grassland area of Lhasa in 2019, with its own latitude and longitude. The hyperspectral survey was mainly sunny. Before flight, whiteboard calibration was carried out; when data were collected, there was a target (that is, the standard reflective cloth suitable for the grass), which was used for spectral calibration; there were ground mark points (that is, letters with foam plates), and the longitude and latitude coordinates of each mark were recorded for geometric precise calibration. The DN value recorded by Hyperspectral camera of UAV can be converted into reflectivity by using Spectron Pro software. Hyperspectral data is used to extract spectral characteristics of different vegetation types, vegetation classification, inversion of vegetation coverage and so on.
2022-04-18
The monthly average vegetation index data of Heihe River Basin is based on MODIS 1 km and 250 m NDVI products. From 250 m products, the grid value of Heihe River Basin is proposed as precision control, and the 1 km product is modified by HASM method. The monthly average vegetation index of Heihe River Basin from 2001 to 2011 was obtained by fusing multi-source NDVI data using HASM method. Resolution: 1km * 1km The average precipitation data set of Heihe River Basin adopts the data information of 21 meteorological conventional observation stations in Heihe River Basin and its surrounding areas and 13 national reference stations around Heihe River basin provided by Heihe planning data management center. The daily precipitation data of each station from 1961 to 2010 is calculated. If the coefficient of variation is greater than 100%, the daily precipitation distribution trend can be obtained by using the geographic weighted regression to calculate the relationship between the station and the geographical terrain factors; if the coefficient of variation is less than or equal to 100%, the relationship between the station precipitation value and the geographical terrain factors (longitude, latitude, elevation) is calculated by ordinary least square regression, and the daily precipitation score is obtained HASM (high accuracy surface modeling method) was used to fit and modify the residual error after removing the trend. Finally, the trend surface results and residual correction results are added to get the annual average precipitation distribution of Heihe River Basin from 1961 to 2010. Time resolution: annual average precipitation from 1961 to 2010. Spatial resolution: 500M.
2020-10-09
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