Nanwakolas Watershed Surveys - Knight Inlet - 2019 - Hakai Airborne Coastal Observatory

Airborne Light Detection and Ranging (LiDAR) data and orthoimagery were collected by Hakai’s Airborne Coastal Observatory (ACO) in the early fall of 2019 for designated Nanwakolas and FLNRORD Coastal Experimental Watersheds in the region of Knight Inlet, BC. These remotely sensed data will be used to support the design and implementation of controlled watershed experiments at spatial scales ranging from fine (plot or stand) to coarse (landscape). Repeat (multi-temporal) aerial remote sensing surveys are required to detect spatiotemporal changes and trends in fine to coarse-scaled ecological and geomorphological phenomena. Airborne LiDAR provides 3-D measurements of forest structure and topography at high spatial resolutions and over relatively large spatial extents, and now routinely used to identify individual tree crowns, vertical canopy profiles, canopy gaps, stand edges, watersheds, sub- basins, channels, and other ecologically relevant landforms. High-spatial-resolution measurements can be further aggregated into coarser-scaled ecological entities (e.g., patches, stands, regions, etc.) using data-driven analytical approaches and methods (e.g., object-based image analysis and clustering). Ground-truth in the form of field visits, air calls, airphoto interpretation, or some combination of all the above are required to place meaningful labels on these new, coarser-scaled spatial entities.

We propose to build several spatial data layers and thematic maps that would support Nanwakolas and FLNRORD Coastal Experimental Watersheds programs. First, several well-established area-based LiDAR canopy height and density metrics related to the vertical and horizontal structure of forest canopies will be extracted at raster cell sizes of 10 and 20 m (100-400m2). Studies demonstrate that these metrics are strongly associated with gradients of microclimates (e.g., light, temperature, moisture, etc.), materials (e.g., phytomass, nutrients, gases, water, etc.), processes (e.g., light capture, photosynthesis, throughfall, evapotranspiration, etc.), organisms (e.g., epiphytes, mammals, birds, insects, microbes, etc.), and timber (e.g., wood volume and mass). LiDAR canopy height and density metrics also change markedly with stand age and may therefore be used to study stand developmental processes and pathways, as well as to predict stand age, at least within ecologically meaningful age classes. Landscape-level variations in forest canopy structure are driven by differences in stand age, species composition, site productivity, climate, and disturbance. We will use data-driven, spatial aggregation techniques to partition continuous, cell-level measurements of canopy height and density into unique structural groups or prototypes that are homogeneous with respect to the variables used to define them.

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Licence: Creative Commons Attribution 4.0
Limitations: Appropriate credit must be given to Hakai Institute and the authors of the dataset.

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Metadata Reference Date(s) March 01, 2022 (Publication)
March 01, 2022 (Revision)
Dataset Reference Date(s) September 29, 2019 (Creation)
December 01, 2019 (Publication)
Frequency of Update As Needed

Responsible Party 1
Name
Geospatial Technology Team
Affiliation
Hakai Institute
Email
data@hakai.org
Role
  • Custodian
  • Distributor
  • Owner
  • Point of Contact
  • Principal Investigator
Responsible Party 2
Name
Airborne Coastal Observatory
Affiliation
Airborne Coastal Observatory - Hakai Institute
Email
data@hakai.org
Role
  • Author
  • Custodian
  • Distributor
  • Originator
  • Owner
  • Point of Contact
  • Principal Investigator
  • Processor
  • Publisher
  • Editor

Field Value
Ocean Variables Other
Scope Dataset
Status On Going
Topic Category oceans
Maintenance Note Generated from https://cioos-siooc.github.io/metadata-entry-form
Spatial Extent { "coordinates": [ [ [ -126.1, 50.54 ], [ -125.3, 50.54 ], [ -125.3, 51.02 ], [ -126.1, 51.02 ], [ -126.1, 50.54 ] ] ], "type": "Polygon" }
North Bounding Latitude 51.02
South Bounding Latitude 50.54
East Bounding Longitude -125.3
West Bounding Longitude -126.1
Temporal Extent
Begin
2019-09-29
End
2019-10-10
Vertical Extent
Min
0.0
Max
1500.0
Default Locale English