Growing Shade is a unique tool that highlights stories and allows users to create custom reports to inform tree canopy enhancement and preservation for the Twin Cities region.
There are additional tools and resources that may be useful for this work. Please consider the list below as a starting point. Additionally, when planning and prioritizing urban forestry work, tools and data cannot substitute for stakeholder engagement to understand community-specific concerns or opportunities. The on-the-ground knowledge of residents and the expertise of local practitioners are valuable sources of information.
Tools
What additional tools and assessments exist to help
prioritize where to plant trees and maintain tree canopy?
•
iTree
tools to quantify the benefits and values of trees, including tools
for individuals such as homeowners concerned with individual or small
amounts of trees
•
American
Forests Tree Equity Score project
•
Hennepin
County, MN Tree Canopy Tree Planting Priority Areas
•
City
of Saint Paul Urban Tree Canopy Assessment 2011
Where can I
lean more about the benefits provided by urban forests and how to build
them?
•
Vibrant
Cities Lab
Where can I learn more about the impact of emerald
ash borer?
•
Minnesota
Department of Agriculture’s Emerald Ash Borer Map
Community Engagement
Why is community engagement essential?
What are the impacts of tree planting on communities?
•
The CREATE
Initiative: Sharing in the Benefits of a Greening City
What
does genuine community engagement look like?
•
Principles
of Authentic Communication (MN Dept of Health)
•
Center
for Whole Communities: Whole Measures
Planting Trees and Native Vegetation
What trees are predicted
to do well in future climate conditions?
•
Climate
Change Vulnerability of Urban Trees: Twin Cities, Minnesota
What the best way to plant a tree?
•
Tree
Trust video
Where can I learn about native plants (trees,
grasses, wildflowers): the benefits, purchasing and planting?
•
Minnesota Native
Plant Society
•
University
of Minnesota Extension
Climate Change
Where can I find more information about climate
change impacts in the Twin Cities?
•
Climate
Vulnerability Assessment by Metropolitan Council for the Twin
Cities
•
Extreme Heat Map Tool by Metropolitan
Council
•
Extreme Heat Story Map by
Metropolitan Council
Human Health
Where can I learn about the impacts of tree on
human health?
•
US
Forest Service Report: Urban Nature for Human Health and Well-being
2018
Connect and Learn
Where can I connect with others working to
grow our tree canopy in the Twin Cities or across Minnesota?
•
Minnesota Shade
Tree Advisory Committee
•
Minnesota
Shade Tree Short Course
•
Stewardship
Mapping and Assessment Project (STEW-MAP): a research tool,
community organizing approach, and partnership mapping platform to
engage and connect stewards of the local environment
How can my
city receive recognition or a certification for our urban forestry
work?
•
Tree
City USA
•
GreenStep
Cities program
What’s Next
What new projects are underway that could support
and inform urban forests in the Twin Cities?
•
Urban
LTER (Long-term Ecological Research) in the Twin Cities
Please refer to a
recorded
webinar or the
text
user guide for help using the tool. Short answers to frequently
asked questions can be found below.
Q. How are the priority layers created?
A. Priority scores are
calculated using equally-weighted variables.
Q. How did you choose the variables for the priority layers?
A. Presets are developed to
provide starting points for various stakeholder groups.
Q. How can I isolate individual variables? Can I visualize the
patterns for a single variable?
A. Click on the “Custom”
priority layer, then select a single variable.
Q. I’m interested in understanding how the tree canopy intersects with
a specific racial or ethnic group rather than all communities of
color.
A. Raw data can be
downloaded from within the “mapping tool” tab if you wish explore
relationships not shown in the report.
Q. Why do different canopy tools show different priority areas?
A. There are several tools,
like the
American
Forests’ Tree Equity Score, that are worth exploring. The Growing
Shade Project was created to specifically address the unique challenges
and opportunities of our region, reflecting priorities that may not be
so readily detailed in a national, more generalized tool. Growing Shade
responds to the specific climate change, conservation, environmental
justice, and public health issues in our region. Also, users can
customize our tool to address their individualized needs, which can be
highly specific (for instance, a user may want to focus on planting
trees in areas to enhance health benefits in children).
Growing Shade’s priority scores range from 0 (lowest priority) to 10 (highest priority). Distance between priority scores can be interpreted on a continuous, linear scale. For instance, the difference between priority scores of 4 and 5 is the same as the difference between priority scores of 5 and 6 (both have a difference of 1).
Q. Why do different canopy tools show different canopy coverage
percents? How did you decide on a goal of 45% tree canopy coverage?
A. We created this tool to
respond to the stakeholder need of providing up-to-date, actionable
data. Therefore, we focus on satellite data to provide current data that
can be used in decision-making. Current data is necessary to manage
impacts from invasive species like emerald ash borer or respond to
emerging climate hazards.
To get current (near real-time) data, Growing Shade leverages Sentinel-2 satellite data. While Sentinel-2 data has excellent temporal resolution, the spatial resolution is 10 meters squared. This is often a bigger area than the canopy from a single tree. When comparing tree canopy detected from Sentinel-2 data with a more spatially accurate (but less temporally accurate) 1 meter squared landcover data set, there was high correlation but Sentinel-2 data detects about a quarter more tree canopy as the 1 meter squared landcover data. Essentially, this means that the methods in Growing Shade detect areas with at least 89% tree canopy coverage. We re-scaled our data using this relationship to improve the clarity of messaging. More information is given in the “methods” tab.
There is not a universal optimal percentage of tree canopy cover for goal setting. Within the 7-county metro area, it is estimated that the natural vegetation had 30.5% of land area covered by forests and another 40.7% was covered by oak woodlands and brushlands. Tree cover in forests can be up to 100% while tree cover in oak woodlands can vary from 10-70% tree cover. Thus, total tree cover across the 7-county region may have been as low as 34.6% (using an estimate of 10% tree cover in oak woodlands) or as high as 59.0% (using an estimate of 70% tree cover in oak woodlands). The average of these values is 46.8% which we have rounded to our goal of 45% tree canopy cover. Note that native tallgrass prairie occurs throughout our region. Native prairie provides many important benefits, and lower tree coverage in areas dominated by tallgrass prairie should not be penalized, nor should prairie be converted into forest.
Q. Why doesn’t the tool show trees where there are trees? Why does the
tool show trees where there are not trees?
A. Calibration revealed that
the tree layer mapped in Growing Shade identifies areas which have at
least 89% tree canopy cover. The tree canopy has been identified from
satellite imagery using a machine learning method rather than collecting
on-the-ground data. More information is given in the “methods” tab.
Q. Is it possible to get the type of information Growing Shade
provides for other areas? Is it possible to get historic data about the
tree canopy from Growing Shade?
A. Right now the focus of
Growing Shade is on current conditions within the 7-county Twin Cities
metro. We do have future updates and new features of this tool planned,
but cannot ensure that any updates will meet specific needs. Please look
to the “resources” tab to see if another product might meet your needs,
and thank you for your interest and understanding.
Growing Shade developed out of a collaboration between the Metropolitan Council, The Nature Conservancy, and Tree Trust. We thank members of the advisory group for initial consultations and thank all individuals who provided feedback during the development phase of this project.
Methods and data sources for the analyses presented within the Growing Shade are detailed below. Please contact us if you have questions or feedback.
Priority variables were sourced from several locations including:
Priority variables were standardized and scaled so that the z-score
was normally distributed on a 0-10 scale (by multiplying the normal
distribution of the z-score for each variable by 10).
Based on user-defined selection of priority variables, standardized scores are averaged to create a single, integrated priority value.
Growing Shade uses and shows a tree canopy layer from 2021. A machine learning method was created in Google Earth Engine and used to detect tree cover from other land cover types using Sentinel-2 satellite imagery. Any areas identified as open water or cultivated cropland were removed.
Next, the tree canopy as identified with Sentinel-2 data was calibrated to the tree canopy identified in 2015 using LiDAR data from 2011 (Twin Cities Metropolitan area 1-meter land cover classification). With 1000 equal-area regions across the 7-county area, a scaling factor of 0.885 was used to bring the Sentinel data in line with on-the-ground tree canopy. This scaling factor is appropriate for our methods of using 10 m x 10 m resolution data, which is often larger than tree canopies. This scaling factor makes our data align very closely with other reports (r^2 = 0.96) while still leveraging the scalability and temporal accuracy of our method.