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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 (CH4) 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 m2. Because the basal area of the plant is more relevant for calculating its contribution to the CH4 flux, the tussock area was related to the basal area from field data (R2 = 0.88, p < 0.0001). Our final results indicate a total basal area of 1,786 ± 62.8 m2. Based on temporal measurements of CH4 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 CH4 exchange over the growing season. [ABSTRACT FROM AUTHOR]

Transparent, objective, and repeatable resource assessments should be the goal of companies, investors, and regulators. Different types of resources, however, may require different approaches for their quantification. In particular, coal can be treated both as a solid resource (and thus be mined) as well as a reservoir for gas (which is extracted). In coal mining, investment decisions are made based on a high level of data and establishment of seam continuity and character. The Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (the JORC Code) allows deposits to be characterised based on the level of geological and commercial certainty. Similarly, the guidelines of the Petroleum Resource Management System (PRMS) can be applied to coal seam gas (CSG) deposits to define the uncertainty and chance of commercialisation. Although coal and CSG represent two very different states of resources (i.e., solid vs. gaseous), their categorisation in the JORC Code and PRMS is remarkably similar at a high level. Both classifications have two major divisions: resource vs. reserve. Generally, in either system, resources are considered to have potential for eventual commercial production, but this has not yet been confirmed. Reserves in either system are considered commercial, but uncertainty is still denoted through different subdivisions. Other classification systems that can be applied to CSG also exist, for example the Canadian Oil and Gas Evaluation Handbook (COGEH) and the Chinese Standard (DZ/T 0216-2020) and both have similar high-level divisions to the JORC Code and PRMS. A hypothetical case study of a single area using the JORC Code to classify the coal and PRMS for the gas showed that the two methodologies will have overlapping, though not necessarily aligned, resource and reserve categories. [ABSTRACT FROM AUTHOR]

Peatlands play a fundamental role in climate regulation through their long-term accumulation of atmospheric carbon. Despite their resilience, peatlands are vulnerable to climate change. Remote sensing offers the opportunity to better understand these ecosystems at large spatial scales through time. In this study, we estimated water table depth from a 6-year time sequence of airborne shortwave infrared (SWIR) hyperspectral imagery. We found that the narrowband index NDWI1240 is a strong predictor of water table position. However, we illustrate the importance of considering peatland anisotropy on SWIR imagery from the summer months when the vascular plants are in full foliage, as not all illumination conditions are suitable for retrieving water table position. We also model net ecosystem exchange (NEE) from 10 years of Landsat TM5 imagery and from 4 years of Landsat OLI 8 imagery. Our results show the transferability of the model between imagery from sensors with similar spectral and radiometric properties such as Landsat 8 and Sentinel-2. NEE modeled from airborne hyperspectral imagery more closely correlated to eddy covariance tower measurements than did models based on satellite images. With fine spectral, spatial and radiometric resolutions, new generation satellite imagery and airborne hyperspectral imagery allow for monitoring the response of peatlands to both allogenic and autogenic factors. [ABSTRACT FROM AUTHOR]

Peatlands cover a large area in Canada and globally (12% and 3% of the landmass, respectively). These ecosystems play an important role in climate regulation through the sequestration of carbon dioxide from, and the release of methane to, the atmosphere. Monitoring approaches, required to understand the response of peatlands to climate change at large spatial scales, are challenged by their unique vegetation characteristics, intrinsic hydrological complexity, and rapid changes over short periods of time (e.g., seasonality). In this study, we demonstrate the use of multitemporal, high spatial resolution (1 m2) hyperspectral airborne imagery (Compact Airborne Spectrographic Imager (CASI) and Shortwave Airborne Spectrographic Imager (SASI) sensors) for assessing maximum instantaneous gross photosynthesis (PGmax) in hummocks, and gravimetric water content (GWC) and carbon uptake efficiency in hollows, at the Mer Bleue ombrotrophic bog. We applied empirical models (i.e., in situ data and spectral indices) and we derived spatial and temporal trends for the aforementioned variables. Our findings revealed the distribution of hummocks (51.2%), hollows (12.7%), and tree cover (33.6%), which is the first high spatial resolution map of this nature at Mer Bleue. For hummocks, we found growing season PGmax values between 8 μmol m−2 s−1 and 12 μmol m−2 s−1 were predominant (86.3% of the total area). For hollows, our results revealed, for the first time, the spatial heterogeneity and seasonal trends for gravimetric water content and carbon uptake efficiency for the whole bog. [ABSTRACT FROM AUTHOR]