气候变化领域集成服务门户(CCPortal): 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

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DOI	10.1016/j.rse.2020.112223
	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
	Sankey J.B.; Sankey T.T.; Li J.; Ravi S.; Wang G.; Caster J.; Kasprak A.
发表日期	2021
ISSN	00344257
卷号	253
英文摘要	Rangelands cover 70% of the world's land surface, and provide critical ecosystem services of primary production, soil carbon storage, and nutrient cycling. These ecosystem services are governed by very fine-scale spatial patterning of soil carbon, nutrients, and plant species at the centimeter-to-meter scales, a phenomenon known as “islands of fertility”. Such fine-scale dynamics are challenging to detect with most satellite and manned airborne platforms. Remote sensing from unmanned aerial vehicles (UAVs) provides an alternative option for detecting fine-scale soil nutrient and plant species changes in rangelands tn0020 smaller extents. We demonstrate that a model incorporating the fusion of UAV multispectral and structure-from-motion photogrammetry classifies plant functional types and bare soil cover with an overall accuracy of 95% in rangelands degraded by shrub encroachment and disturbed by fire. We further demonstrate that employing UAV hyperspectral and LiDAR fusion greatly improves upon these results by classifying 9 different plant species and soil fertility microsite types (SFMT) with an overall accuracy of 87%. Among them, creosote bush and black grama, the most important native species in the rangeland, have the highest producer's accuracies at 98% and 94%, respectively. The integration of UAV LiDAR-derived plant height differences was critical in these improvements. Finally, we use synthesis of the UAV datasets with ground-based LiDAR surveys and lab characterization of soils to estimate that the burned rangeland potentially lost 1474 kg/ha of C and 113 kg/ha of N owing to soil erosion processes during the first year after a prescribed fire. However, during the second-year post-fire, grass and plant-interspace SFMT functioned as net sinks for sediment and nutrients and gained approximately 175 kg/ha C and 14 kg/ha N, combined. These results provide important site-specific insight that is relevant to the 423 Mha of grasslands and shrublands that are burned globally each year. While fire, and specifically post-fire erosion, can degrade some rangelands, post-fire plant-soil-nutrient dynamics might provide a competitive advantage to grasses in rangelands degraded by shrub encroachment. These novel UAV and ground-based LiDAR remote sensing approaches thus provide important details towards more accurate accounting of the carbon and nutrients in the soil surface of rangelands. © 2020
英文关键词	Airborne data; Change detection; Digital elevation model (DEM); Digital elevation model of difference (DOD); Drone; Fire; Grass; Hyperspectral; Islands of fertility; Lidar; Machine learning; Nutrient; Photogrammetry; Rangeland; Shrub; Soil; Structure from motion (SFM); Terrestrial laser scanning; Unmanned aerial system (UAS); Unmanned aerial vehicle (UAV)
语种	英语
scopus关键词	Aircraft detection; Antennas; Competition; Ecosystems; Erosion; Fires; Forestry; Optical radar; Photogrammetry; Plants (botany); Remote sensing; Soils; Storage as a service (STaaS); Unmanned aerial vehicles (UAV); Competitive advantage; Digital photography; Ground-based lidars; Overall accuracies; Plant functional type; Shrub encroachments; Soil carbon storage; Structure from motion; Nutrients; carbon storage; ecosystem service; grassland; lidar; photogrammetry; rangeland; remote sensing; soil carbon; soil nutrient; spectral analysis; unmanned vehicle; Bouteloua eriopoda; Larrea tridentata; Poaceae
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179018
作者单位	Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86004, United States; School of Informatics, Computing, and Cyber Systems, Northern Arizona University, 1295 S. Knoles Driver, Flagstaff, AZ 86011, United States; Department of Geosciences, The University of Tulsa, Tulsa, OK 74104, United States; Department of Earth and Environmental Science, Temple University, 1901 N. 13th Street, Philadelphia, PA 19122, United States; Geosciences Department and Four Corners Water Center, Fort Lewis College, Durango, CO 81301, United States
推荐引用方式 GB/T 7714	Sankey J.B.,Sankey T.T.,Li J.,et al. 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[J],2021,253.
APA	Sankey J.B..,Sankey T.T..,Li J..,Ravi S..,Wang G..,...&Kasprak A..(2021).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.Remote Sensing of Environment,253.
MLA	Sankey J.B.,et al."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".Remote Sensing of Environment 253(2021).