A long-term spatiotemporal analysis of biocrusts across a diverse arid environment: The case of the Israeli-Egyptian sandfield.

Spatiotemporal data can be analyzed using spatial, time-series, and machine learning algorithms to extract regional biocrust trends. Analyzing the spatial trends of biocrusts through time, using satellite imagery, may improve the quantification and understanding of their change drivers. The current work strives to develop a unique framework for analyzing spatiotemporal trends of the spectral Crust Index (CI), thus identifying the drivers of the biocrusts' spatial and temporal patterns.