# GPP of a Chinese Savanna Ecosystem during Different
## 5 Conclusions  
A few years after the introduction of the HLS concept, we conducted HLS remote sensing GPP model simulations in the most typical savanna in China. This is the first case study of VPM simulations using HLS remote sensing data and considering different phenological phases for savanna GPP estimation on the basis of phenocam images. We used the GEE cloud computing platform to synthesize HLS data for a typical savanna in China and extracted the meteorological and vegetation parameters needed for VPM simulations. VPM simulations were performed by combining important vegetation parameters with ecosystem flux and meteorological data. The simulation results were compared with MODIS satellite data, which are commonly used in other studies. The consistency of the savanna ecosystem GPP was also verified for the global product MOD17A2. In this study, we found that the HLS VPM provided a notable advantage over the MODIS VPM in estimating the GPP in the savanna, and the HLS VPM attained a satisfactory performance during all phenological phases in this savanna ecosystem. Moreover, this study confirmed the usefulness of the MOD17A2 product for annual large-scale savanna GPP estimation, but this product could not track seasonal savanna GPP dynamics and was not suitable for use in research on the relationship between the savanna GPP and phenology. Our study is the first comparative study of satellite remote sensing data and EC flux observations of the GPP in savanna ecosystems in China, which is important for determining the changes in the GPP in savanna ecosystems during different phenological phases against the background of climate change and for managing and protecting savanna ecosystems.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs16183475/s1](https://www.mdpi.com/article/10.3390/rs16183475/s1)]([https://www.mdpi.com/article/10.3390/rs16183475/s1](https://www.mdpi.com/article/10.3390/rs16183475/s1)), Figure S1: Light-response curve function based on two weeks of Yuanjiang flux tower measurements during the selected periods (2015-2018); Figure S2: VPM GPP estimates based on MODIS (a) and HLS (b) compared with eddy flux tower EC GPP for the Yuanjiang site; Figure S3: Examples of curve fitting and phenophase delineation for 2016 via phenopix; Figure S4: Linear regression equations with an intercept of 0 for VPM simulations compared with EC at different phenophases for 4 years (2015-2018); Table S1: RMSE values for different phenological stages from MODIS, HLS, and MOD17A2H VPM GPP simulation.  
Conceptualization, X.Z. and Y.Z.; methodology, S.X. and X.Z.; software, S.X., X.Z. and G.F.; validation, S.X. and G.F.; formal analysis, X.Z. and Y.Z.; investigation, Q.S. and D.Q.; resources, Y.Z. and Q.S.; writing--original draft preparation, X.Z. and Y.Z.; writing--review and editing, X.Z. and Y.Z.; supervision, Y.Z.; funding acquisition, Y.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant numbers (42075119, 31770528, 4191101289, and 41975147), and the National Key Research and Development Program of China, grant number (2016 YFC0502105).  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
This study was supported by CAS, the Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna, China. We thank [PERSON] and his student [PERSON] from the University of Oklahoma and [PERSON] from the USDA-ARS Grazinglands Research Laboratory for their help in the VPM. We acknowledge the European Commission and the Copernicus program team for their free access to Sentinel-2 data. We would like to acknowledge the staff and technicians of the Yuanjiang Savanna Ecosystem Research Station of Xishuangbanna Tropical Botanical Garden of CAS.  
The authors declare no conflicts of interest.