20240305
15445700
1.0
FGDC CSDGM Metadata
FALSE
RenoCanopy2017_NevadaBoundary
2203353.895590
2359319.400080
14785044.548192
14963898.129266
1
002
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Nevada_West_FIPS_2703_Feet
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20250326
13370400
20250326
13370400
150000000
5000
FGDC
external
54c88b83dfdbaf6b8c5069e5bb6eed7
Shelby Huth
Davey Resource Group
GIS Analyst
295 S. Water Street Suite 300
Kent
OH
44240
shelby.huth@davey.com
US
330-673-5685 ext. 8877
Shelby Huth
True
Shelby Huth
external
a3fd8f2e3edae8d5e519864a7bc53d1
Aaron Taveras
Nevada Division of Forestry - Department of Conservation and Natural Resources
GIS & Data Coordinator
aTaveras@forestry.nv.gov
(775) 684-2518
True
Aaron Taveras
File Geodatabase Raster Dataset
external
62be73387109d2fc59433b0d68ecc86
Tina McKeand
Davey Resource Group
Urban & Community Forestry Specialist
6005 Capistrano Ave, Suite A
Atascadero
Califonia
93422
tina.mckeand@davey.com
US
928-246-7048
8:00 am - 5:00pm PST
Tina McKeand
Tina McKeand
Tina McKeand
Tina McKeand
True
Tina McKeand
RenoCanopy2017_NevadaBoundary
The purpose of this project was to conduct a top down canopy assessment approach. Utilizing the 2017 National Agricultural Imagery Program (NAIP) 60cm imagery and advance remote sensing technology, land cover features were identified by using an object-based image analysis (OBIA) methodology to process and analyze high resolution imagery. This technique allows a more accurate and cost-effective automated feature extraction of land cover classes. The final GIS land cover layer allows Reno, Nevada to conduct additional spatial analyses necessary to identify and map the existing land cover layer for future.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>With the size of the study area measured at approximately </SPAN><SPAN>217.9 square miles, a cost-effective and accurate strategy for assessing the urban forest is the use of remotely sensed and semi-automated classification methods to inventory the current canopy cover and to analyze data for future planting goals.</SPAN></P></DIV></DIV></DIV>
Reno
Washoe County
Nevada
Urban tree canopy (UTC)
Tree Canopy
2017
Nevada Boundary
County Boundary
Boundaries
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>As determined by Reno, Nevada.</SPAN></P></DIV></DIV></DIV>
As determined by Reno, Nevada.
external
62be73387109d2fc59433b0d68ecc86
Tina McKeand
Davey Resource Group
Urban & Community Forestry Specialist
6005 Capistrano Ave, Suite A
Atascadero
Califonia
93422
tina.mckeand@davey.com
US
928-246-7048
8:00 am - 5:00pm PST
Tina McKeand
Tina McKeand
Tina McKeand
Tina McKeand
True
Tina McKeand
Esri ArcGIS 13.2.2.49743
1
-120.082806
-119.521173
39.801535
39.304800
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>As determined by Reno, Nevada.</SPAN></P></DIV></DIV></DIV>
As determined by Reno, Nevada.
These data are believed to be logically consistent, though no formal test were performed. Structural integrity is consistent within the parameters for ESRI ArcGIS 10 Geodatabase format.
Land cover acreage are calculated using the ArcGIS field calculator and percentage of coverage per land cover class are determined by dividing the current acreage for each class by the total area of the City.
Using advanced GIS and remote sensing software, Davey's GIS Analyst utilized a top-down, automated feature extraction approach to process and identify an initial 3-class land cover layer of canopy, impervious surfaces, and all other landcover. ArcGIS 10 and Overwatch's Feature Analyst were used to complete the initial automated feature extraction. Ancillary GIS data, provided by the City, was also utilized to aid in the initial extraction and the quality control process.
Feature extraction provides a much more cost effective way of creating land cover layers than manually digitizing images.
The main QC process was completed at a scale of 1:2000 by GIS Technicians and Specialists in order to ensure that the land cover classification layer was 90% to 95% accurate. During this process, editing was completed using ArcGIS® to identify, clean, and correct any misclassification or topology errors in the final land cover dataset. The use of secondary sources like the Map2Google tool in ArcGIS® and Microsoft's Birds Eye View was also be used to aid in the quality check process. Once the initial intensive QC process was completed, each of the layers were examined by the GIS Analyst to correct any missed misclassifications and also to add any additional features, if necessary.
Multiple QC procedures ensure that Davey will provide the best possible land cover results.
Metadata created.
Random plot locations were generated and verified to ensure that the data met client standards and assured that automated mapping and data analysis performed by GIS specialists accurately reflected the true nature and extent of the land cover. A total of 1,000 points were generated for Reno, Nevada. Each point was examined and a confusion matrix was created to calculate overall accuracy, Kappa coefficient, and a user's and producer's accuracy.
Davey statistically tests all land cover data to ensure the urban tree canopy assessment yields statistically significant results.
After completing the accuracy assessments, the final comprehensive land cover dataset was processed in ArcGIS® using geoprocessing, analysis, and data management tools to measure the existing land cover layer. Additional GIS analysis was completed using current data sources for further investigation and in support of the urban canopy assessment process. Area and percentages of land cover classes were calculated for each type and metadata was created.
To analyze land cover metrics and deliver all data in an organized fashion.
VAT_RenoCanopy2017_NevadaBoundary
Table
1
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Value
Value
Integer
4
0
0
Count
Count
Double
8
0
0
dataset
EPSG
8.2.10(9.3.0.0)
Pixel
54516
47539
3.280791
3.280754
1
1
Upper Left
FALSE
LZ77
1
pixel codes
FGDBR
TRUE
row and column
3.280791
3.280754
20250326