Videographic Analysis of Eriophorum Vaginatum Spatial Coverage in an Ombotrophic Bog

Abstract

Abstract:The use of Remotely Piloted Aircraft Systems (RPAS) as well as newer automated unmanned aerial vehicles is becoming a standard method in remote sensing studies requiring high spatial resolution (<1 m) and very precise temporal data to capture phenological events. In this study we use a low cost rotorcraft to map Eriophorum vaginatum at Mer Bleue, an ombrotrophic bog located east of Ottawa, ON, Canada. We focus on E. vaginatum because this sedge plays an important role in methane (CH 4 ) gas exchange in peatlands. Using the remote controlled rotorcraft we were able to record, process, and mosaic 11.1 hectares of 4.5 cm spatial resolution imagery extracted from individual frames of video recordings (post georegistration RMSE 4.90 ± 4.95 cm). Our results, based on a supervised classification (96% accuracy) of the red, green, blue image planes, indicate a total tussock cover of 2,417 m 2 . Because the basal area of the plant is more relevant for calculating its contribution to the CH 4 flux, the tussock area was related to the basal area from field data (R 2 = 0.88, p < 0.0001). Our final results indicate a total basal area of 1,786 ± 62.8 m 2 . Based on temporal measurements of CH 4 flux from the peatland as a whole that vary over the growing season, we estimate the E. vaginatum contribution to range from 3.0% to 17.3% of that total. Overall, our low cost approach was an effective non-destructive way to derive E. vaginatum coverage and estimate CH 4 exchange over the growing season. OPEN ACCESSRemote Sens. 2013, 5 6502

Evidence for a nonmonotonic relationship between ecosystem‐scale peatland methane emissions and water table depth

“…groenlandicum communities coincided with periods when the WT fell below 40 cm [ Lai , ]. Although the dominant vegetative cover was (ericaceous) shrubs, CH 4 emissions from sedge communities (~2% cover) [ Kalacska et al ., ] were about 5 times those of the shrub communities [ Lai , ; Moore et al ., ] and thus should contribute to the ecosystem‐scale emissions at Mer Bleue. However, unlike our ecosystem‐scale F CH4 trends, peak autochamber F CH4 in the E .…”

Implementation of a UAV–Hyperspectral Pushbroom Imager for Ecological Monitoring

“…Nevertheless, due to the high cost of implementing a representative and adequate sample (i.e., the number of spectral plots and well-calibrated targets), for instance, due to poor accessibility (e.g., peatlands), field spectroscopy data are still limited to minimal sampling efforts (e.g., [21]). The rapid evolution in the development and implementation of relatively inexpensive and "easy to use" UAV platforms for agriculture, forestry and ecological applications over the last decade [22][23][24][25] have the potential to bridge the gap between in-situ and airborne observations [26]. For instance, the Structure from Motion derived orthomosaics and 3D surfaces at ultra-high ground sampling distances (e.g., 1 cm) [27] to provide extremely detailed biophysical parameters (e.g., vegetation structure) [28], in some cases with higher accuracy than the more expensive Light Detection and Ranging (LiDAR) systems [24].…”

An Object-Based Image Analysis Workflow for Monitoring Shallow-Water Aquatic Vegetation in Multispectral Drone Imagery

“…In recent years, there has been burgeoning use of small drone aircraft systems to conveniently collect timely, very high spatial-resolution (<20 cm) imagery of hard-to-access or -navigate aquatic environments, including wetlands [6][7][8], bogs [9][10][11], lakes [12][13][14], rivers [15][16][17], coasts [18][19][20], and general hydrological and water resource monitoring [21][22][23]. As high-resolution drone imagery tends to be laborious to analyze manually, increasingly sophisticated approaches have been developed and tested to automate such tasks as aquatic vegetation detection and classification, many of them founded on object-based image analysis (OBIA) [24][25][26][27][28].…”