Topography significantly affects remotely sensed reflectance data and subsequently impacts the retrieval of the leaf area index (LAI) from surface reflectance data over rugged terrains. However, most LAI inversion algorithms ignore the influence of terrain. This paper quantitatively analyzes the topographic effects on LAI values retrieved from remote sensing data at various spatial scales (30, 90, 270, 540, 1080, and 5400 m) over rugged terrains. The PRO4SAILT (PROSPECT + 4SAILT) model and the Proy algorithm were used to simulate multiscale surface reflectance for different LAI values over rugged terrains. Based on Gaussian process regression (GPR), an LAI inversion algorithm that ignores terrain effects was first developed. The simulated multiscale reflectance data were subsequently input into the inversion algorithm to retrieve LAI values. Finally, the retrieved LAI values were compared with the corresponding reference LAI values. The results demonstrate that the finer the spatial resolution is, the more significant the topographic effects on the retrieved LAI values are. When the reference LAI is five, as the spatial resolution increases from 5400 m to 30 m, the mean percentage error (MPE) of the retrieved LAI increases from 10.46% to 13.72%, and the root mean square error (RMSE) increases from 0.5376 to 1.005. Regardless of the spatial resolution, the error in the retrieved LAI values increases with an increasing terrain slope. When the reference LAI is five and the spatial resolution is 30 m, the MPE at a slope of 15°–30° is close to 5%, and the RMSE is close to 0.3. The MPE at a slope of 30°–45° is close to 20%, and the RMSE is close to one. In addition, the accuracy of the retrieved LAI values is closely related to the sky view factor (SVF). In general, the larger the SVF is, the smaller the error in the retrieved LAI values. In addition, the conversion relationships between the retrieved LAI values using the algorithm that ignores terrain effects and the true LAI values are provided in this study.

The fraction of absorbed photosynthetically active radiation (FAPAR) is a key biophysical variable directly associated with the photosynthetic activity of plants. Several global FAPAR products with different spatial resolutions have been generated from remote sensing data, and much work has focused on validating them. However, those studies have primarily evaluated global FAPAR products at a spatial resolution of 1 km or more, whereas few studies have evaluated the global 500 m resolution FAPAR product distributed in recent years. Furthermore, there are a few FAPAR products, including black-sky, white-sky and blue-sky FAPAR datasets, and almost no studies have evaluated these products. In this article, three global FAPAR products at 500 m resolution, namely MODIS (only black-sky FAPAR), MUSES and EBR (black-sky, white-sky and blue-sky FAPAR) were compared to evaluate their temporal and spatial discrepancies and direct validation was conducted to compare these FAPAR products with the FAPAR values derived from the high-resolution reference maps from the Validation of Land European Remote Sensing Instrument (VALERI) and Implementing Multi-Scale Agricultural Indicators Exploiting Sentinels (IMAGINES) projects. The results showed that the MUSES FAPAR product exhibited the best spatial integrity, whereas the MODIS and EBR FAPAR products had many missing pixels in the equatorial rainforest regions and at high latitudes in the Northern Hemisphere. The MODIS, MUSES and EBR FAPAR products were generally consistent in their spatial patterns. However, a relatively large discrepancy among these FAPAR products was present in the equatorial rainforest regions and the middle and high latitude regions where the main vegetation type was forest. The differences between the black-sky and white-sky FAPAR datasets at the global scale were significant. In January, the MUSES and EBR black-sky FAPAR values were larger than their white-sky FAPAR values in the region north of 30° north latitude but they were smaller than their white-sky FAPAR values in the region south of 30° north latitude. In July, the MUSES and EBR black-sky FAPAR values were lower than their white-sky FAPAR values in the region north of 30° south latitude and they were larger than their white-sky FAPAR values in the region south of 30° south latitude. The temporal profiles of the MUSES FAPAR product were continuous and smooth, whereas those of the MODIS and EBR FAPAR products showed many fluctuations, particularly during the growing seasons. Direct validation indicated that the MUSES FAPAR product had the best accuracy (R² = 0.6932, RMSE = 0.1495) compared to the MODIS FAPAR product (R² = 0.6202, RMSE = 0.1710) and the EBR FAPAR product (R² = 0.5746, RMSE = 0.1912).