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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

Remote sensing of environment, 2021-02, Vol.253, p.112223, Article 112223 [Periódico revisado por pares]

New York: Elsevier Inc

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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
Autor: Sankey, Joel B. ; Sankey, Temuulen T. ; Li, Junran ; Ravi, Sujith ; Wang, Guan ; Caster, Joshua ; Kasprak, Alan
Assuntos: Aerial surveys ; Airborne data ; Airborne sensing ; Carbon ; Carbon cycle ; Carbon sequestration ; Carbon storage ; Change detection ; Creosote ; Degradation ; Deserts ; Digital elevation model (DEM) ; Digital elevation model of difference (DOD) ; Drone ; Ecosystem services ; Encroachment ; Environmental changes ; Erosion processes ; Fire ; Flowers & plants ; Grass ; Grasses ; Grasslands ; Hyperspectral ; Indigenous species ; Islands of fertility ; Lidar ; Machine learning ; Nutrient ; Nutrient cycles ; Nutrient dynamics ; Nutrients ; Photogrammetry ; Photography ; Plant species ; Prescribed fire ; Primary production ; Rangeland ; Rangelands ; Remote sensing ; Satellites ; Shrub ; Soil ; Soil dynamics ; Soil erosion ; Soil fertility ; Soil nutrients ; Species classification ; Structure from motion (SFM) ; Terrestrial laser scanning ; Unmanned aerial system (UAS) ; Unmanned aerial vehicle (UAV) ; Unmanned aerial vehicles
É parte de: Remote sensing of environment, 2021-02, Vol.253, p.112223, Article 112223
Descrição: 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. •Rangeland function is influenced by fine-scale patterns of species & soil nutrients.•Range plant-soil-nutrient dynamics require very high spatial & spectral resolution.•UAV multispectral-photogrammetry fusion excels at functional cover classification.•UAV hyperspectral-LiDAR fusion excels at species & soil fertility classification.•LiDAR data detect soil fertility changes from ecological disturbance of fire.
Editor: New York: Elsevier Inc
Idioma: Inglês

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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

New York: Elsevier Inc

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