Forest and Land Cover

2008 Study:

High resolution land cover dataset for Toronto with eight land cover classes: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, (7) other paved surfaces and (8) agriculture. This dataset was developed in 2007 as part of an Urban Tree Canopy (UTC) Assessment for Toronto. As such, it represents a "top down" mapping perspective in which tree canopy over hanging other features is assigned to the tree canopy class. At the time of its creation this dataset represents the most detailed and accurate land cover dataset for the area.

Projected coordinate system name: MTM_3Degree

Geographic coordinate system name: GCS_North_American_1927

Urban Forestry performs a complete Forest and Land Cover survey and analysis every 10 years. The next installment of this survey is taking place in 2018.

2018 Study:

High resolution land cover dataset for Toronto with eight land cover classes: (1) tree (2) grass (3) bare (4) water (5) building (6) road (7) other paved surfaces and (8) shrub. This dataset was developed in 2018 as part of the Tree Canopy Study prepared for Toronto. As such, it represents a "top down" mapping perspective in which tree canopy cover hanging over other features is assigned to the tree canopy class. At the time of its creation this dataset represents the most detailed and accurate land cover dataset for the City. Classes 1, 2, 3 and 8 (tree, grass, bare and shrub) were extracted from multispectral satellite imagery, with the assistance of LiDAR information.

Data and Resources

Additional Info

Field Value
Last Updated February 18, 2020, 17:05 (UTC)
Created July 23, 2019, 17:15 (UTC)
Package ID 61642048-56bb-4050-b7c3-f569fcf94527
Package Name forest-and-land-cover
Excerpt High resolution land cover dataset for Toronto with eight land cover classes.
Limitations The following are limitations that were taken into consideration when performing the automated land cover classification: 1. Enterprise geospatial data quality varies in data accuracy, currency and scale a. Ward and Neighbourhood administrative boundaries do not share exact geographic distribution b. Ward and Neighbourhood administrative boundaries have different creation dates 2. Ward and Neighbourhoods administrative boundaries occupy non in-land water areas (i.e. Toronto Harbour) 3. Topographic features are not all collected in the same calendar year, resulting in currency discrepancies 4. Geospatial accuracy differences between classified land cover data and topographic information 5. Image size limitation within the image classification software, resulting in the creation of image grids for analysis 6. The water class in the 2008 analysis included the Toronto Harbour between Toronto Island and the main shoreline. This area of water was removed from the 2018 analysis as it was not determined to be “in-land water”. 7. Absolute accuracy in the extraction of features through automated analysis a. Data similarities between land cover classes • Trees and grass/shrub • Bare and other • Road and other 8. Inability for full automation to provide the desired spatial accuracy   The projection is: Clarke_1866_Transverse_Mercator
Dataset Category Document
Refresh Rate As available
Owner Division Parks, Forestry & Recreation
Owner Email connie.pinto@toronto.ca
Civic Issues Climate change
Formats SHP,DOC,RAR
Topics Environment,Locations and mapping,Transportation,Water
Information URL http://www.toronto.ca/trees/index.htm