(AI), machine learning, and other cutting edge data analysis tools to analyze a range and scale of data that was previously not possible.Nearly 40% of the United States are arid and semiarid ecosystems, thus these drylands are both vast and important. At the same time, remote sensing challenges unique to drylands have made landscape-scale assessments of drylands challenging and thus the power of remote sensing tools has lagged behind their use in more mesic ecosystems. Nevertheless, the utility of improving our ability to use remote sensing for assessing and understanding drylands has myriad uses, including those that directly inform resource managers and decision makers. This would include the creation of innovative remote sensing options for mapping, assessing, and managing for biological soil crusts. Biocrusts are a soil surface community that represent the dominant cover type in many U.S. drylands. It has been proposed to blend emerging remote sensing technology from drones, satellites, and on-the-ground with ground-based ecology and novel dryland experiments to improve the tools and options dryland land managers have to manage for essential ecosystem services. New remote sensing technologies could vastly improve ability to predict biocrust abundance, rangeland productivity, and exotic grass invasion, which would be of significant use for resource managers, ranchers, hunters and anyone needing to consider forage quality for livestock and wildlife, fire regimes for the upcoming year, dust production, and restoration prioritization options.