Groundwater level (GWL) and depth to water (DTW) are related metrics aimed at characterizing groundwater-table positions in peatlands, and two of the most common variables collected by researchers working in these ecosystems. While well-established field techniques exist for measuring GWL and DTW, they are generally difficult to scale. In this study, we present a novel workflow for mapping groundwater using orthophotography and photogrammetric point clouds acquired from unmanned aerial vehicles. Our approach takes advantage of the fact that pockets of surface water are normally abundant in peatlands, which we assume to be reflective of GWL in these porous, gently sloping environments. By first classifying surface water and then extracting a sample of water elevations, we can generate continuous models of GWL through interpolation. Estimates of DTW can then be obtained through additional efforts to characterize terrain. We demonstrate our methodology across a complex, 61-ha treed bog in northern Alberta, Canada. An independent accuracy assessment using 31 temporally coincident water-well measurements revealed accuracies (root mean square error) in the 20-cm range, though errors were concentrated in small upland pockets in the study area, and areas of dense tree covers. Model estimates in the open peatland areas were considerably better.

Abstract:The HEAT (Home Energy Assessment Technologies) pilot project is a FREE Geoweb mapping service, designed to empower the urban energy efficiency movement by allowing residents to visualize the amount and location of waste heat leaving their homes and communities as easily as clicking on their house in Google Maps. HEAT incorporates Geospatial solutions for residential waste heat monitoring using Geographic Object-Based Image Analysis (GEOBIA) and Canadian built Thermal Airborne Broadband Imager technology (TABI-320) to provide users with timely, in-depth, easy to use, location-specific waste-heat information; as well as opportunities to save their money and reduce their green-house-gas emissions. We first report on the HEAT Phase I pilot project which evaluates 368 residences in the Brentwood community of Calgary, Alberta, Canada, and describe the development and implementation of interactive waste heat maps, energy use models, a Hot Spot tool able to view the 6+ hottest locations on each home and a new HEAT Score for inter-city waste heat comparisons. We then describe current challenges, lessons learned and new solutions as we begin Phase II and scale from 368 to 300,000+ OPEN ACCESSRemote Sens. 2011, 3 1381 homes with the newly developed TABI-1800. Specifically, we introduce a new object-based mosaicing strategy, an adaptation of Emissivity Modulation to correct for emissivity differences, a new Thermal Urban Road Normalization (TURN) technique to correct for scene-wide microclimatic variation. We also describe a new Carbon Score and opportunities to update city cadastral errors with automatically defined thermal house objects.

Peatlands are globally significant sources of atmospheric methane (CH 4 ). In the northern hemisphere, extensive geologic exploration activities have occurred to map petroleum deposits. In peatlands, these activities result in soil compaction and wetter conditions, changes that are likely to enhance CH 4 emissions. To date, this effect has not been quantified. Here we map petroleum exploration disturbances on peatlands in Alberta, Canada, where peatlands and oil deposits are widespread. We then estimate induced CH 4 emissions. By our calculations, at least 1900 km 2 of peatland have been affected, increasing CH 4 emissions by 4.4–5.1 kt CH 4 yr −1 above undisturbed conditions. Not currently estimated in Canada’s national reporting of greenhouse gas (GHG) emissions, inclusion would increase current emissions from land use, land use change and forestry by 7–8%. However, uncertainty remains large. Research further investigating effects of petroleum exploration on peatland GHG fluxes will allow appropriate consideration of these emissions in future peatland management.

Peatlands are globally significant stores of soil carbon, where local methane (CH4) emissions are strongly linked to water table position and microtopography. Historically, these factors have been difficult to measure in the field, constraining our capacity to observe local patterns of variability. In this paper, we show how remote sensing surveys conducted from unmanned aerial vehicle (UAV) platforms can be used to map microtopography and depth to water over large areas with good accuracy, paving the way for spatially explicit estimates of CH4 emissions. This approach enabled us to observe—for the first time—the effects of low‐impact seismic lines (LIS; petroleum exploration corridors) on surface morphology and CH4 emissions in a treed‐bog ecosystem in northern Alberta, Canada. Through compaction, LIS lines were found to flatten the observed range in microtopographic elevation by 46 cm and decrease mean depth to water by 15.4 cm, compared to surrounding undisturbed conditions. These alterations are projected to increase CH4 emissions by 20–120% relative to undisturbed areas in our study area, which translates to a total rise of 0.011–0.027 kg CH4 day−1 per linear kilometer of LIS (~2 m wide). The ~16 km of LIS present at our 61 ha study site were predicted to boost CH4 emissions by 20–70 kg between May and September 2016.

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