Next Article in Journal
Population Characteristics of Loess Gully System in the Loess Plateau of China
Previous Article in Journal
Detection of Thermal Changes Related to the 2011 Shinmoedake Volcano Activity, Japan: Spatiotemporal Variation of Singularity of MODIS Data after Discriminating False Changes Due to Cloud
Article

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra

1
Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY 11973, USA
2
Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794, USA
3
College of Natural Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China
4
School of Forest Resources, University of Maine, Orono, ME 04469, USA
5
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
6
Climate Change Science Institute and Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
*
Author to whom correspondence should be addressed.
Equal contribution.
Remote Sens. 2020, 12(16), 2638; https://doi.org/10.3390/rs12162638
Received: 25 June 2020 / Revised: 4 August 2020 / Accepted: 7 August 2020 / Published: 15 August 2020
Changes in vegetation distribution, structure, and function can modify the canopy properties of terrestrial ecosystems, with potential consequences for regional and global climate feedbacks. In the Arctic, climate is warming twice as fast as compared to the global average (known as ‘Arctic amplification’), likely having stronger impacts on arctic tundra vegetation. In order to quantify these changes and assess their impacts on ecosystem structure and function, methods are needed to accurately characterize the canopy properties of tundra vegetation types. However, commonly used ground-based measurements are limited in spatial and temporal coverage, and differentiating low-lying tundra plant species is challenging with coarse-resolution satellite remote sensing. The collection and processing of multi-sensor data from unoccupied aerial systems (UASs) has the potential to fill the gap between ground-based and satellite observations. To address the critical need for such data in the Arctic, we developed a cost-effective multi-sensor UAS (the ‘Osprey’) using off-the-shelf instrumentation. The Osprey simultaneously produces high-resolution optical, thermal, and structural images, as well as collecting point-based hyperspectral measurements, over vegetation canopies. In this paper, we describe the setup and deployment of the Osprey system in the Arctic to a tundra study site located in the Seward Peninsula, Alaska. We present a case study demonstrating the processing and application of Osprey data products for characterizing the key biophysical properties of tundra vegetation canopies. In this study, plant functional types (PFTs) representative of arctic tundra ecosystems were mapped with an overall accuracy of 87.4%. The Osprey image products identified significant differences in canopy-scale greenness, canopy height, and surface temperature among PFTs, with deciduous low to tall shrubs having the lowest canopy temperatures while non-vascular lichens had the warmest. The analysis of our hyperspectral data showed that variation in the fractional cover of deciduous low to tall shrubs was effectively characterized by Osprey reflectance measurements across the range of visible to near-infrared wavelengths. Therefore, the development and deployment of the Osprey UAS, as a state-of-the-art methodology, has the potential to be widely used for characterizing tundra vegetation composition and canopy properties to improve our understanding of ecosystem dynamics in the Arctic, and to address scale issues between ground-based and airborne/satellite observations. View Full-Text
Keywords: Arctic tundra; canopy properties; remote sensing; spectral reflectance; thermal infrared; unoccupied aerial system; vegetation mapping Arctic tundra; canopy properties; remote sensing; spectral reflectance; thermal infrared; unoccupied aerial system; vegetation mapping
Show Figures

Graphical abstract

MDPI and ACS Style

Yang, D.; Meng, R.; Morrison, B.D.; McMahon, A.; Hantson, W.; Hayes, D.J.; Breen, A.L.; Salmon, V.G.; Serbin, S.P. A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra. Remote Sens. 2020, 12, 2638. https://doi.org/10.3390/rs12162638

AMA Style

Yang D, Meng R, Morrison BD, McMahon A, Hantson W, Hayes DJ, Breen AL, Salmon VG, Serbin SP. A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra. Remote Sensing. 2020; 12(16):2638. https://doi.org/10.3390/rs12162638

Chicago/Turabian Style

Yang, Dedi, Ran Meng, Bailey D. Morrison, Andrew McMahon, Wouter Hantson, Daniel J. Hayes, Amy L. Breen, Verity G. Salmon, and Shawn P. Serbin. 2020. "A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra" Remote Sensing 12, no. 16: 2638. https://doi.org/10.3390/rs12162638

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop