Quantifying plant-soil-nutrient dynamics in rangelands: Fusion of UAV hyperspectral-LiDAR, UAV multispectral-photogrammetry, and ground-based LiDAR-digital photography in a shrub-encroached desert grassland

Rangelands cover 70% of the world's land surface, and provide critical ecosystem services primary production, soil carbon storage, nutrient cycling. These are governed by very fine-scale spatial patterning carbon, nutrients, plant species at centimeter-to-meter scales, a phenomenon known as “islands fertility”. Such dynamics challenging to detect with most satellite manned airborne platforms. Remote sensing from unmanned aerial vehicles (UAVs) provides an alternative option for detecting changes in rangelands tn0020 smaller extents. We demonstrate that model incorporating fusion UAV multispectral structure-from-motion photogrammetry classifies functional types bare overall accuracy 95% degraded shrub encroachment disturbed fire. further employing hyperspectral LiDAR greatly improves upon these results classifying 9 different fertility microsite (SFMT) 87%. Among them, creosote bush black grama, important native rangeland, have highest producer's accuracies 98% 94%, respectively. The integration LiDAR-derived height differences was improvements. Finally, we use synthesis datasets ground-based surveys lab characterization soils estimate burned rangeland potentially lost 1474 kg/ha C 113 N owing erosion processes during first year after prescribed However, second-year post-fire, grass plant-interspace SFMT functioned net sinks sediment nutrients gained approximately 175 14 N, combined. site-specific insight is relevant 423 Mha grasslands shrublands globally each year. While fire, specifically post-fire erosion, can degrade some rangelands, plant-soil-nutrient might competitive advantage grasses encroachment. novel remote approaches thus details towards more accurate accounting surface rangelands.