ABSTRACT As thick crustal layers form on dryland surfaces, they affect the spectral information that is originally dominated by sand or rock. The spectral characteristics of organic matter replace the… Click to show full abstract
ABSTRACT As thick crustal layers form on dryland surfaces, they affect the spectral information that is originally dominated by sand or rock. The spectral characteristics of organic matter replace the mineral elements as prominent features. In this case, the growth patterns and spectral characteristics of biological soil crusts (BSCs) can be observed. Satellite spectral data have been used for BSC spatial information extraction. However, the dynamic changes in BSCs can affect the spectra. Two aspects are involved here: moisture change and BSC growth. When these changes are superimposed with BSC succession, they lead to an increase in spectral complexity. This study explored three BSC types, including algal crust, lichen and moss, and discussed their spectra. By selecting BSC samples at different succession states and by combining coverage and simulated precipitation, the response of the spectra to BSC coverage and the spectral characteristics of BSCs under dry and wet conditions were measured and analysed. In addition, the spectral index variations caused by coverage and moisture of three types of BSCs were discussed, where the spectral indices include the normalized difference vegetation index (NDVI), brightness index (BI), crust index (CI), and biological soil crust index (BSCI). The results showed that the succession, moisture and growth of BSCs were the main factors affecting their spectra. BSC types can be distinguished in a particular climatic context to determine the degree of BSC succession. Precipitation in the monitoring areas needs to be considered to avoid the effects of dry and wet BSC variations on remote sensing monitoring. The coverage of different types of BSCs in mixed pixels can be determined by multiple indices. The results of this study will provide a basis for monitoring BSCs using satellite spectral information to guide regional ecological management.
               
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