干旱区生态环境知识资源中心(Arid): 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

Arid

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, Joel B.; Sankey, Temuulen T.; Li, Junran; Ravi, Sujith; Wang, Guan; Caster, Joshua; Kasprak, Alan
通讯作者	Sankey, JB (corresponding author), N Gemini Dr, Flagstaff, AZ 86001 USA.
来源期刊	REMOTE SENSING OF ENVIRONMENT
ISSN	0034-4257
EISSN	1879-0704
出版年	2021
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.
英文关键词	Airborne data Drone Unmanned aerial system (UAS) Unmanned aerial vehicle (UAV) Terrestrial laser scanning Photogrammetry Structure from motion (SFM) Lidar Hyperspectral Machine learning Digital elevation model (DEM) Digital elevation model of difference (DOD) Change detection Rangeland Shrub Grass Soil Nutrient Fire Islands of fertility
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000604328800005
WOS关键词	SOUTHERN NEW-MEXICO ; WIND EROSION ; SATELLITE IMAGERY ; SAGEBRUSH STEPPE ; ORGANIC-CARBON ; VEGETATION ; FIRE ; COVER ; TRANSPORT ; JUNIPER
WOS类目	Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	United States Geological Survey
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/348146
作者单位	[Sankey, Joel B.; Caster, Joshua; Kasprak, Alan] US Geol Survey, Southwest Biol Sci Ctr, Grand Canyon Monitoring & Res Ctr, Flagstaff, AZ 86004 USA; [Sankey, Temuulen T.] No Arizona Univ, Sch Informat Comp & Cyber Syst, 1295 S Knoles Driver, Flagstaff, AZ 86011 USA; [Li, Junran; Wang, Guan] Univ Tulsa, Dept Geosci, Tulsa, OK 74104 USA; [Ravi, Sujith] Temple Univ, Dept Earth & Environm Sci, 1901 N 13th St, Philadelphia, PA 19122 USA; [Kasprak, Alan] Ft Lewis Coll, Dept Geosci, Durango, CO 81301 USA; [Kasprak, Alan] Ft Lewis Coll, Four Corners Water Ctr, Durango, CO 81301 USA
推荐引用方式 GB/T 7714	Sankey, Joel B.,Sankey, Temuulen T.,Li, Junran,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]. United States Geological Survey,2021,253.
APA	Sankey, Joel B..,Sankey, Temuulen T..,Li, Junran.,Ravi, Sujith.,Wang, Guan.,...&Kasprak, Alan.(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, Joel 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).