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Understanding the spatio-temporal dynamics of land surface phenology is important to understanding changes in landscape ecological processes of semi-arid savannas in Southern Africa. The first contribution of this study is to account for grassland heterogeneity while working at the object level by modeling its pixels distributions by a Gaussian distribution.
Azimuth is from top to bottom; range from left to right.
Darker regions represent larger numbers of points. Both approaches have their limitations and combining them with a data fusion may overcome some of these limitations. Therefore, either a corner reflector design tailored to a specific data type or a compromise design for multiple data types is required. Meanwhile, solar-cloud-satellite geometry SCSG makes the effect of clouds and shadows on derived land surface biophysical parameters more complicated. The reference information included environmental data, vegetation growth status, and region drought-affected RDA information at diverse scales pixel, county, and region for three types of land cover forest steppe, steppe, and desert steppe. Uncertainties in the estimates of water constituents are among the main issues concerning the orbital remote sensing of inland waters.