## 5 Conclusions  
The CI is a crucial vegetation structure parameter that plays an important role in LAI estimations and the building of ecological, hydrological, and land surface models. Its seasonality is also critical in LAI mapping and ecosystem modeling. The MODIS BRDF/Albedo product is the most widely used input data for CI retrieval. As the newly released C6 product presents significant improvements in data quality and temporal resolution, it is imperative for the application of MODIS CI products to determine the impacts of updating the MCD43 product as an important input for the consistency and performance of CI retrievals. In this study, CI retrievals from the C5 and C6 MCD43 products were compared and validated in terms of spatial distributions and seasonal variations. The results are described as follows:  
1. The C5 and C6 CI data show similar spatial distributions globally. These two versions of data exhibit similar spatial patterns and latitudinal distributions globally in January and July, which relate to the distribution of vegetation types and leaf-on/leaf-off seasons. Forest areas have lower CI values, while grass, shrub, crop, and savanna regions display higher CI values. In the Northern Hemisphere, the January CI is generally higher than that in July, and the opposite is true in the Southern Hemisphere. 2. The C5 and C6 CI QA data show similar patterns globally, while the C6 CI data have an improved quality with more main algorithm retrievals and fewer missing values. For both versions of data, the overall proportion of main algorithm retrievals is higher in July than in January, while the C6 data show a higher rate of main algorithm retrievals and a lower rate of missing value in the summer hemisphere and a lower rate of backup algorithm retrieval in most of the world. 3. In general, the C5 and C6 CI data show similar seasonal variations in the three latitude zones (NH, SH, and Trop) and different land cover types, which is consistent with the vegetation phenology. Through quality screening and averaging, the monthly CI data have higher data quality and are recommended to characterize the overall seasonal patterns of the surface CIs well, with less uncertainty than using C5 8-day, monthly, and C6 daily CI data. 4. Through a comparison with field-measured CI data, both versions of the MODIS CI data agree with the field-measured CIs and their seasonal variations, while the C6 CI data (R\({}^{2}\) = 0.89, RMSE = 0.05, bias = 0.02) show better consistency with the field measurements than the C5 CI data (R\({}^{2}\) = 0.80, RMSE = 0.07, bias = 0.03). Remote sensing CI retrieval products are susceptible to the performance of upstream data. Comprehensive evaluation and analysis of updated derived data as input are crucial for choosing the correct and reasonable CI products for downstream applications for user communities. As improvements in remote sensing instruments and processing algorithms are ongoing, further studies are needed for updated products, such as the MODIS C6.1 product and even the Visible Infrared Imaging Radiometer Suite (VIIRS) BRDF/Albedo product [120]. In addition, the within-pixel variability of CI measurements in satellite CI product validation and the influence of spatial resolution on CI retrievals from different satellite sensors deserve to be further explored in near future. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs14163997/s1](https://www.mdpi.com/article/10.3390/rs14163997/s1)]([https://www.mdpi.com/article/10.3390/rs14163997/s1](https://www.mdpi.com/article/10.3390/rs14163997/s1)), Figure S1, a scatter plot for comparison of C5 8-day CI and C6 daily CI data with the field CI data at 7 sites with seasonal profiles of field-measured CIs (Table 2). Different symbols denote CI data of different sites, and the red and blue colors indicate C5 and C6 CIs, respectively.