20231127
17223800
1.0
FALSE
TreeCanopy2022DiamondHeadresample
002
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_10N
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20231121
14524900
20231121
14524900
150000000
5000
ItemDescription
Esri ArcGIS 13.1.2.41833
Tree Canopy (2021)
To identify the location, extent, height, and deciduous, coniferous, or dead class of every tree within the City of Maple Ridge. Collectively, to identify the canopy cover percentage within the City.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>DHC used the 2022 4-band leaf-on orthoimagery and the December 26, 2021 leaf-off LiDAR as inputs. An object-oriented machine learning classification algorithm generated the canopy using both the imagery and 3D LiDAR data. The resulting canopy was then segmented using an individual tree detection inverse-watershed algorithm. These segments were subsequently classified into coniferous, deciduous, or dead tree classes. Manual editing was conducted by a 3 person crew based on the 2022 orthoimagery and the 2021 LiDAR nDSM (normalized Digital Surface Model) to eliminate artifacts (buildings, poles, cars, etc) from the canopy file. Lastly, tree height and crown area metrics were calculated for each canopy polygon by performing a zonal stats function on the Canopy Height Model (CHM). A height cut-off of 2m was used based on the zonal stats function. </SPAN></P></DIV></DIV></DIV>
Tree Canopy
Trees
Crowns
DHC, City of Maple Ridge
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>There is an overestimation of the number of trees within the City of Maple Ridge due to the over-segmentation of broad-leaf crowns by the algorithm. The individual coniferous tree canopies were detected with higher accuracy compared to deciduous canopies, which are broader and can contain multiple local apexes. </SPAN></P></DIV></DIV></DIV>
Enterprise Geodatabase Feature Class
dataset
EPSG
6.13(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
TreeCanopy2022DiamondHeadresample
Feature Class
0
Shape
Shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
ID
ID
Double
8
38
8
crownArea
crownArea
Double
8
38
8
class
class
String
1073741822
0
0
LIDAR_Year
LIDAR_Year
Integer
4
10
0
ht_mean
ht_mean
Double
8
38
8
ht_stdev
ht_stdev
Double
8
38
8
ht_min
ht_min
Double
8
38
8
ht_max
ht_max
Double
8
38
8
Shape.STArea()
Shape.STArea()
Double
0
0
0
Shape.STLength()
Shape.STLength()
Double
0
0
0
20231121