Hopkinson, Christopher
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- ItemPost-fire vegetation regeneration during abnormally dry years following severe montane fire: southern Alberta, Canada(Elsevier, 2025) Aspinall, Jesse; Chasmer, Laura; Coburn Craig; Hopkinson, ChristopherFire regimes across montane regions of western Canada are changing resulting in longer fire seasons, higher intensity fires, and shortening fire return intervals. The implications of high severity fire and warmer, drier early post-fire conditions on herbaceous understory vegetation regeneration and seedling recruitment in the southern Canadian Rockies are not well known. The overall objective of this study is to quantify trajectories of vegetation recovery (species, structural characteristics, and biomass) during early years of abnormally warm, dry conditions following a high severity fire in two moisture endmember sites Waterton Lakes National Park, Alberta, Canada. Here, we compare the within and between year spatial and temporal variability of vegetation growth and species density and how these change over time and across the broader area as an indicator of ecosystem resilience within these endmember sites. Moderate to extreme drought occurred during the years following fire at Waterton, where 2021 was ranked as the 2nd driest year in 26 years. Despite this, the moist site was characterised by greater herbaceous vegetation recovery with few lodgepole pine seedlings (average biomass = 335 g m−2), while a drier site had greater seedling recruitment over a period of 5 years. Variations in site environmental conditions were more impactful than differences between years (drought) on post-fire vegetation recovery. Use of remotely piloted aircraft system (RPAS) remotely sensed data provided an effective means for quantifying variability in regenerating vegetation height (structure from motion), cover (green chromatic coordinate), and biomass when compared at plot level (R2 = 0.53, 0.53, and 0.30 respectively) using optical photogrammetric methods. The research presented has implications for forest and fuel management in Canada as national parks and forest agencies consider historic use of heterogeneous species patches. High density of lodgepole pine seedling recruitment in mineral soils and under very dry conditions indicate resilience to drought. This will require continued and expanded monitoring as other tree species recruits populate the post-fire environment.
- ItemRemote sensing of wetlands in the prairie pothole region of North America(MDPI, 2021) Montgomery, Joshua; Mahoney, Craig; Brisco, Brian; Boychuk, Lyle; Cobbaert, Danielle; Hopkinson, ChristopherThe Prairie Pothole Region (PPR) of North America is an extremely important habitat for a diverse range of wetland ecosystems that provide a wealth of socio-economic value. This paper describes the ecological characteristics and importance of PPR wetlands and the use of remote sensing for mapping and monitoring applications. While there are comprehensive reviews for wetland remote sensing in recent publications, there is no comprehensive review about the use of remote sensing in the PPR. First, the PPR is described, including the wetland classification systems that have been used, the water regimes that control the surface water and water levels, and the soil and vegetation characteristics of the region. The tools and techniques that have been used in the PPR for analyses of geospatial data for wetland applications are described. Field observations for ground truth data are critical for good validation and accuracy assessment of the many products that are produced. Wetland classification approaches are reviewed, including Decision Trees, Machine Learning, and object versus pixel-based approaches. A comprehensive description of the remote sensing systems and data that have been employed by various studies in the PPR is provided. A wide range of data can be used for various applications, including passive optical data like aerial photographs or satellite-based, Earth-observation data. Both airborne and spaceborne lidar studies are described. A detailed description of Synthetic Aperture RADAR (SAR) data and research are provided. The state of the art is the use of multi-source data to achieve higher accuracies and hybrid approaches. Digital Surface Models are also being incorporated in geospatial analyses to separate forest and shrub and emergent systems based on vegetation height. Remote sensing provides a cost-effective mechanism for mapping and monitoring PPR wetlands, especially with the logistical difficulties and cost of field-based methods. The wetland characteristics of the PPR dictate the need for high resolution in both time and space, which is increasingly possible with the numerous and increasing remote sensing systems available and the trend to open-source data and tools. The fusion of multi-source remote sensing data via state-of-the-art machine learning is recommended for wetland applications in the PPR. The use of such data promotes flexibility for sensor addition, subtraction, or substitution as a function of application needs and potential cost restrictions. This is important in the PPR because of the challenges related to the highly dynamic nature of this unique region.
- ItemDelegate perspectives on transitioning the 41st Canadian Symposium on remote sensing to a virtual event due to the COVID-19 Pandemic(Taylor & Francis, 2022) Hopkinson, Christopher; Coburn, Craig A.The 41st Canadian Symposium on Remote Sensing (CSRS) was a unique event, originally planned to be hosted as an in-person event in Yellowknife, Northwest Territories but ultimately delivered 100% online due to the COVID-19 global pandemic. As the 41st CSRS represented an unprecedented departure from the CRSS-SCT’s long history of annual in-person symposia, this note summarizes the transition from an in-person to an online event. In particular, delegate feedback on some of the challenges encountered, as well as positive and negative perceptions of the event delivery. It is important that a record of these collective experiences is preserved and considered for future symposia, and our experience is shared with the global research community.
- ItemThe Multisource Vegetation Inventory (MVI): a satellite-based forest inventory for the Northwest Territories taiga plains(MDPI, 2022) Castilla, Guillermo; Hall, Ronald J.; Skakun, Rob; Filiatrault, Michelle; Beaudoin, André; Gartrell, Michael; Smith, Lisa; Groenewegen, Kathleen; Hopkinson, Christopher; van der Sluijs, JurjenSustainable forest management requires information on the spatial distribution, composition, and structure of forests. However, jurisdictions with large tracts of noncommercial forest, such as the Northwest Territories (NWT) of Canada, often lack detailed forest information across their land base. The goal of the Multisource Vegetation Inventory (MVI) project was to create a large area forest inventory (FI) map that could support strategic forest management in the NWT using optical, radar, and light detection and ranging (LiDAR) satellite remote sensing anchored on limited field plots and airborne LiDAR data. A new landcover map based on Landsat imagery was the first step to stratify forestland into broad forest types. A modelling chain linking FI plots to airborne and spaceborne LiDAR was then developed to circumvent the scarcity of field data in the region. The developed models allowed the estimation of forest attributes in thousands of surrogate FI plots corresponding to spaceborne LiDAR footprints distributed across the project area. The surrogate plots were used as a reference dataset for estimating each forest attribute in each 30 m forest cell within the project area. The estimation was based on the k-nearest neighbour (k-NN) algorithm, where the selection of the four most similar surrogate FI plots to each cell was based on satellite, topographic, and climatic data. Wall-to-wall 30 m raster maps of broad forest type, stand height, crown closure, stand volume, total volume, aboveground biomass, and stand age were created for a ~400,000 km2 area, validated with independent data, and generalized into a polygon GIS layer resembling a traditional FI map. The MVI project showed that a reasonably accurate FI map for large, remote, predominantly non-inventoried boreal regions can be obtained at a low cost by combining limited field data with remote sensing data from multiple sources.
- Item3D graph-based individual-tree isolation (treeiso) from terrestrial laser scanning point clouds(MDPI, 2022) Xi, Zhouxin; Hopkinson, ChristopherUsing terrestrial laser scanning (TLS) technology, forests can be digitized at the centimeter-level to enable fine-scale forest management. However, there are technical barriers to converting point clouds into individual-tree features or objects aligned with forest inventory standards due to noise, redundancy, and geometric complexity. A practical model treeiso based on the cut-pursuit graph algorithm was proposed to isolate individual-tree points from plot-level TLS scans. The treeiso followed the local-to-global segmentation scheme, which grouped points into small clusters, large segments, and final trees in a hierarchical manner. Seven tree attributes were investigated to understand the underlying determinants of isolation accuracy. Sensitivity analysis based on the PAWN index was performed using 10,000 parameter combinations to understand the treeiso’s parameter importance and model robustness. With sixteen reference TLS plot scans from various species, an average of 86% of all trees were detected. The mean intersection-over-union (mIoU) between isolated trees and reference trees was 0.82, which increased to 0.92 within the detected trees. Sensitivity analysis showed that only three parameters were needed for treeiso optimization, and it was robust against parameter variations. This new treeiso method is operationally simple and addresses the growing need for practical 3D tree segmentation tools.