Petawawa Research Forest

Petawawa Research Forest is a 97 square kilometres temperate hardwood forest hub site located in Ontario, near the border with Quebec and the city of Pembroke, Ontario.  To gain access to more raw data, please contact Joanne White with the Natural Resources Canada. [Click on any image to magnify]

Forest Monitoring
 

Site Details

Petawawa_Boundary.jpg
Petawawa_DEM30m.jpg
Petawawa_2020BAP.jpg
Best Available Pixel (2020)
Petawawa Hub Site Boundary
Petawawa Digital Elevation Model (DEM) at 30 m resolution

Best Available Pixel (BAP) composites use Landsat scenes to develop cloud-free, surface reflectance pixel-based image composites capable of large-area production. When incorporated in a time series, they generate land cover, land cover change, and forest structural attributes information products in a dynamic, transparent, systematic, repeatable, and spatially exhaustive manner. This figure displays the 2020 BAP composite within the Haliburton hub site in Ontario. The acquisition of all pixels for this BAP composite were within 30 days of the first of August, 2020.

Petawawa_DEM250m.jpg
Petawawa Digital Elevation Model (DEM) at 250 m resolution
 

Climate

PW - Change in Tmin; 2050 + 2090.jpg
PW - Change in Tmax; 2050 + 2090.jpg

Projections for change in minimum temperature for the years 2050 and 2090 relative to the reference period (1981-2010)

Projections for change in maximum temperature for the years 2050 and 2090 relative to the reference period (1981-2010)

PW - Change in PPT; 2050 + 2090.jpg
PW - PPT, Tmax, Tmin - Hist, 2050, 2090.jpg

Projections for change in seasonal precipitation for the years 2050 and 2090 relative to the reference period (1981-2010)

Climate data for historical (1981-2010) and future (2050 and 2090) projections

 

LiDAR Derived Products

PRF_DEM.jpg
PRF_Aspect.jpg
PRF_Slope.jpg
Digital Elevation Model (1m)

Description - An interpolation of last returns classified as 'ground' points using TIN.

Pixel Values - Elevation at a 1 metre resolution.

Forestry Application - The Digital Elevation Model is important for topographical information, including slope, aspect, and radiation

PRF_Radiation.jpg
Radiation (1m)

Description - A technique to visualize a shaded relief, illuminating it with a hypothetical light

Pixel Values - Raster containing a numeric value representing the solar-radiation aspect index. Values range from 0 (land oriented in a northern direction resulting in less solar radiation exposure) and 1 (land oriented with southern slopes)

Forestry Application - Land oriented in northerly (values closer to zero) are typically wetter and cooler compared to land oriented in southerly (values closer to one)

Slope (1m)

Description - Steepness or the degree of incline of a surface based on the DEM model

Pixel Values - Raster containing numeric values representing degrees of incline

Forestry Application - Slope influences tree stability, harvesting solutions, productivity of harvesting and collection means, architecture of the road networks, road characteristics, and solutions related to the reclamation of degraded forested land.

PRF_ZQ20.jpg
20th Height Percentile (20m)

Description - Height at which 20% of LiDAR returns fall below from 2m above the ground

Pixel Values - Height measurement in metres describing the height at which 20% of LiDAR returns fall below

Forestry Application - Assists in determining the height and distribution of the lower section of the canopy

Aspect (1m)

Description - Orientation of slope, measured clockwise in radians based on the DEM model

Pixel Values - Raster containing a numeric value representing the radians of orientation

Forestry Application - Land oriented in northerly are typically wetter and cooler compared to land oriented in southerly

PRF_ZQ95.jpg
95th Height Percentile (20m)

Description - Height at which 95% of LiDAR returns fall below from 2m above the ground

Pixel Values - Height measurement in metres describing the height at which 95% of LiDAR returns fall below

Forestry Application - Assists in determining the height and distribution of the lower section of the canopy

PRF_CHM.jpg
Canopy Height Model (1m)

Description - Based on an interpolation of the height of the top of trees  (using the pitfree algorithm)

Pixel Values - Raster containing a numeric value for the distance between the ground and the top of trees

Forestry Application - Helpful for determining the distribution of canopy coverage

PRF_Zmean.jpg
Mean Height (20m)

Description - Mean height of first returns above 2m from "ground" (last return data)

Pixel Values - Mean height of all point cloud returns greater than 2m above last returns

Forestry Application - Determines the mean height of all objects (trees) that are at least 2m tall

PRF_Zstd.jpg
Mean Standard Deviation (20m)

Description - Standard Deviation of height distributions above 2m

Pixel Values - Standard deviation height of all point cloud returns greater than 2m above last returns

Forestry Application - Determines the standard deviation for the height of all objects (trees) that are at least 2m tall

Entropy (20m)
PRF_Entropy.jpg

Description - Shannon entropy quantifies the diversity and evenness of an elevation distribution of LiDAR points from 2m above the ground

Pixel Values - Entropy results range from 0 to 1. Random data has a Shannon entropy value of 1

Forestry Application - Useful for describing and quantifying species diversity in biological systems.

PRF_Skewness.jpg
Skewness (20m)

Description - A measure of the distribution's symmetry from 2m above the ground

Pixel Values - A normal distribution would produce skewness results of zero. Negative values indicate that data is skewed to the left, and positive values indicate that data is skewed to the right.

Forestry Application - Skewness is often used with kurtosis to separate ground points and object points from a LiDAR point cloud. It has a variety of applications, including optimizing the DEM, segmentation and classification, and road extraction.

PRF_Kurtosis.jpg
Kurtosis (20m)

Description - The size of the tails of a distribution (likelihood that the distribution will produce outliers) from 2m above the ground

Pixel Values - A normal distribution would produce kurtosis results of 3. Distributions with kurtosis less than 3 are platykurtic (fewer and less extreme outliers) and distributions with kurtosis greater than 3 are laptokurtic (produce more outliers)

Forestry Application - Kurtosis is often used with skewness to separate ground points and object points from a LiDAR point cloud. It has a variety of applications, including optimizing the DEM, segmentation and classification, and road extraction.

PRF_cCover2m.jpg
Canopy Cover > 2m (20m)

Description - Canopy cover at a height greater than 2 metres

Pixel Values - Ratio from the sum of first returns > 2 metres divided by the total first returns

Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 2 metres

PRF_LAIe.jpg
LAIe (20m)

Description - A measurement of the gap fraction through the probability of beam penetration of sunlight through the vegetation.

Pixel Values - Ratio of one-sided green leaf area per unit ground surface area

Forestry Application - Important growth index for the status of crop populations

PRF_cCover5m.jpg
Canopy Cover > 5m (20m)

Description - Canopy cover at a height greater than 5 metres

Pixel Values - Ratio from the sum of first returns > 5 metres divided by the total first returns

Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 5 metres

PRF_cCover15m.jpg
Canopy Cover > 15m (20m)

Description - Canopy cover at a height greater than 15 metres

Pixel Values - Ratio from the sum of first returns > 15 metres divided by the total first returns

Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 15 metres

PRF_Rumple.jpg
Rumple (20m)

Description - Crown Surface Roughness from 2m above the ground

Pixel Values - A ratio of canopy outer surface area to ground surface area

Forestry Application - Higher rumple values indicate more vertical and horizontal heterogeneity

 

Vector Products

V-ForestInventory.jpg
V-Water.jpg
V-Infrastructure.jpg
V-Buildings.jpg