
Proceedings Paper
Spectro-spatial relationship between UAV derived high resolution DEM and SWIR hyperspectral data: application to an ombrotrophic peatlandFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
Peatlands cover ~3% of the globe and are key ecosystems for climate regulation. To better understand the potential
effects of climate change in peatlands, a major challenge is to determine the complex relationship between hydrology,
microtopography, vegetation patterns, and gas exchange. Here we study the spectral and spatial relationship of
microtopographic features (e.g. hollows and hummocks) and near-surface water through narrow-band spectral indices
derived from hyperspectral imagery. We used a very high resolution digital elevation model (2.5 cm horizontal, 2.2 cm
vertical resolution) derived from an UAV based Structure from Motion photogrammetry to map hollows and hummocks
in the peatland area. We also created a 2 cm spatial resolution orthophoto mosaic to enhance the visual identification of
these hollows and hummocks. Furthermore, we collected SWIR airborne hyperspectral (880-2450 nm) imagery at 1 m
pixel resolution over four time periods, from April to June 2016 (phenological gradient: vegetation greening). Our results
revealed an increase in the water indices values (NDWI1640 and NDWI2130) and a decrease in the moisture stress index
(MSI) between April and June. In addition, for the same period the NDWI2130 shows a bimodal distribution indicating
potential to quantitatively assess moisture differences between mosses and vascular plants. Our results, using the digital
surface model to extract NDWI2130 values, showed significant differences between hollows and hummocks for each
time period, with higher moisture values for hollows (i.e. moss dominated). However, for June, the water index for
hummocks approximated the values found in hollows. Our study shows the advantages of using fine spatial and spectral
scales to detect temporal trends in near surface water in a peatland.
Paper Details
Date Published: 2 November 2017
PDF: 12 pages
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104210P (2 November 2017); doi: 10.1117/12.2277874
Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)
PDF: 12 pages
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104210P (2 November 2017); doi: 10.1117/12.2277874
Show Author Affiliations
J. Pablo Arroyo-Mora, National Research Council Canada (Canada)
Margaret Kalacska, McGill Univ. (Canada)
Oliver Lucanus, Below Water (Canada)
Margaret Kalacska, McGill Univ. (Canada)
Oliver Lucanus, Below Water (Canada)
Raymond Soffer, National Research Council Canada (Canada)
George Leblanc, National Research Council Canada (Canada)
George Leblanc, National Research Council Canada (Canada)
Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)
© SPIE. Terms of Use
