Using the vegetation-solar radiation (VSr) model to estimate the short-term gross primary production (GPP) of vegetation in Jinghe county, XinJiang, China

- Investigate relationship between Solar radiation and GPP.
- Analyze GPP simulation results of grassland, forest land and cultivated land.
- Validate the Vsr model simulation accuracy with the standard MODIS GPP products.
- Establish a short-term GPP estimation model in areas lacking ground measurements.

Gross Primary Production (GPP) is the sum of ecosystem photosynthetic production and is an important variable in the study of the carbon cycle. Remote sensing methods were used to calculate GPP and compare the GPP of different regions with various land cover types (LCTs). We used a remote sensing-based vegetation-solar radiation (VSr) GPP estimation model to simulate changes in short-term GPP where vegetation ecosystem measurements are lacking. The study was conducted in 2011 at a typical arid and semi-arid oasis site in Jinghe County, Xinjiang, North China. The VSr model was appraised using 254 global radiation and MODIS GPP data points, including 84 grassland vegetation points (GP), 86 forest vegetation points (FP), and 84 cultivated land vegetation points (CP). The model was developed using the enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and solar radiation was obtained by calculation. Our results indicated that the updated VSr model improved the GPP accuracy compared with the standard MODIS GPP product by decreasing the root mean square errors (RMSEs) by 5.083, 4.802 and 3.076 for the GP, FP and CP sites, respectively. A comparison of test samples of GPP MODIS products and the VSr GPP model calculation showed that the VSr model had higher accuracy and stability. The VSr model can be used to simulate changes in short-term GPP where vegetation ecosystem measurements are lacking.

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