Bloomington Tree Canopy Summary Report, September 2019

Urban Tree Canopy Assessment Summary Report City of Bloomington, Indiana September 2019 Prepared for: City of Bloomington 501 North Morton Street Bloomington, Indiana 47404 Prepared by: Davey Resource Group, Inc. 5641 West 73rd Street Indianapolis, Indiana 46278 800-828-8312

Acknowledgments Bloomington’s vision to promote and preserve the urban forest and improve the management of public trees was a fundamental inspiration for this project. This vision will ensure canopy continuity, which will reduce stormwater runoff and energy use and improve aesthetic value, air quality, and public health.

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Executive Summary The City of Bloomington’s urban tree canopy is an essential part of the city’s infrastructure. The tree canopy provides more than the traditional values of aesthetics and shade. They provide numerous quantifiable environmental benefits, including stormwater management, watershed protection, water quality improvements, temperature moderation and cooling, reduction of air pollutants, and energy conservation. The amount of tree canopy determines the amount of economic, environmental, and social benefits to a community.

Results of the urban tree canopy assessment will assist the City of Bloomington in managing their urban forest and will help to:

Set Canopy Goals

Trees contribute greatly to the quality of life in the community, and—unlike the other components of the community’s infrastructure—the tree population, with proper care and protection, will continue to increase in value with each passing year.

Revise Policies Associated with Tree Canopy

Over the last 20 years, great advances in quantifying the economic, environmental, and social benefits of the urban forest have been made. These advances have become more available to community and government stakeholders for utilization as planning and managerial tools. The value of trees and green spaces has shifted in communities, thus advances in urban forestry have come forth.

This project provides the City of Bloomington tools that illustrate current baseline land cover percentages, including tree canopy, plantable area, and the ecosystem benefits trees provide.

Promote the Benefits of Trees

Develop Sound Urban Forest Management Strategies

The results of this urban tree canopy assessment will be especially valuable for the reasonable, rational, and defensible planning of the City of Bloomington’s current and future urban forest and green infrastructure.

The City of Bloomington’s Parks and Recreation Department contracted DRG to translate digital imagery showing detailed leaf-on conditions into different land cover classifications. The project area is within the city limits of Bloomington, Indiana and is approximately 23 square miles or 15,000 acres (Figure 1).

The City of Bloomington’s 2018 tree canopy is 38%. Over the last 10 years, Bloomington’s tree canopy has decreased by less than 2%. An estimate of area available to tree planting is 22%. The analysis projects Bloomington’s attainable tree canopy is 61%; this is the sum of the existing tree canopy and plantable area. Within the plantable area, 16% or 532 acres are designated as High or Very High priority areas for tree planting. Priority is based on degradation from storm and flood events and effects of urban heat island.

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Bloomington’s existing tree canopy is a vital asset, providing a value of nearly $55.0 million in ecological and economic benefits. Trees store 720,000 tons of carbon valued at $33.4 million plus annually trees sequester 28,000 tons of carbon, remove 470,000 pounds of air pollutants, and manage 90.6 million gallons of stormwater runoff, all valued at an annually returned benefit of $1.9 million.

At the request of the City of Bloomington, part of the analysis also includes the Indiana University Bloomington campus geographic area. Indiana University’s campus encompasses 1,209 acres; trees cover 244 acres. From the assessment, DRG has determined that Indiana University’s campus can increase its urban tree canopy from 20% to 45%.

City of Bloomington can use the data to set goals with the completion of this tree canopy assessment. Reaching the maximum tree canopy will be a challenge; however, preserving existing tree canopy, establishing realistic canopy goals, and harnessing the maximum amount of ecosystem benefits by planting, maintaining, and caring for trees (particularly large-growing trees) when appropriate are prudent and responsible endeavors.

Figure 1. Aerial imagery of City of Bloomington (2018).

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Table of Contents Acknowledgments ................................................................................................................................... i Executive Summary ............................................................................................................................... ii Assignment ............................................................................................................................................. 1 Land Cover Analysis .............................................................................................................................. 2 Ecological and Economic Services ...................................................................................................... 14 Projected and Preferred Tree Canopy................................................................................................... 18 Prioritized Plantable Area..................................................................................................................... 24 Tree Canopy Change ............................................................................................................................ 26 Tree Canopy Health.............................................................................................................................. 33 Forest Fragmentation ............................................................................................................................ 35 Tree Canopy Calculator........................................................................................................................ 37 Discussion ............................................................................................................................................ 39 Glossary ................................................................................................................................................ 40

Tables 1. Results of Land Cover Classification Analysis for Bloomington, IN (2018) .................................. 2 2. Results of Land Cover Classification Analysis by Neighborhood for Bloomington, Indiana (2018) ............................................................................................................................................... 4 3. Results of Land Cover Classification Analysis by Sub Watershed for Bloomington, IN (2018). ... 8 4. Results of Land Cover Classification Analysis by Zoning Type for Bloomington, Indiana (2018) ............................................................................................................................................. 10 5. Results of Ecosystem Benefits Analysis for the City of Bloomington (2018) .............................. 14 6. Stormwater Pollutant Runoff Benefits Based on 2018 Tree Canopy of 38% ................................ 15 7. Results of Projected Potential Tree Canopy Analysis for Bloomington, IN Neighborhoods (2018) ............................................................................................................................................. 20 8. Results of Prioritized Planting Area Analysis for Bloomington, Indiana (2018). ........................ 24 9. Results of Tree Canopy Change for Bloomington, Indiana per Neighborhood (2008-2018). ..... 29 10. Results of Tree Canopy Change for Bloomington, Indiana per Sub Watershed (2008-2018)..... 31 11. Results of Tree Canopy Change for Bloomington, Indiana per Zoning Type (2008-2018) ......... 32 12. Health of Tree Canopy within the City of Bloomington (2018) .................................................... 33 13. Forest Type of Tree Canopy within the City of Bloomington (2018) ........................................... 35 14. A Sample Planting Strategy to Estimate the Number of Trees and Cost to Increase Tree Canopy by 2% ....................................................................................................................... 38

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Aerial imagery of City of Bloomington (2018) .............................................................................. iii City of Bloomington urban tree canopy assessment results (2018) ................................................. 3 Percentages of tree canopy cover by neighborhood in Bloomington, IN (2018) ............................. 7 Percentages of tree canopy cover based on sub watersheds of Bloomington, IN (2018) ................ 9 The City of Bloomington zoning type descriptions and locations (2018) ..................................... 11 Percentages of tree canopy cover by zoning type in Bloomington, IN (2018) .............................. 12 Percentages of impervious surface cover by zoning type in Bloomington, IN (2018) .................. 13 Stormwater benefits ....................................................................................................................... 15 City of Bloomington population density among neighborhoods (2018) ....................................... 17 Projected tree canopy potential within the City of Bloomington, IN (2018) ................................. 18 Results of the projected potential tree canopy analysis for Bloomington IN sub watersheds (2018) ............................................................................................................................................. 22 12. Results of the projected potential tree canopy analysis for Bloomington, IN zoning type (2018) 23 13. Prioritized planting areas within Bloomington, IN (2018) ............................................................ 25 Davey Resource Group

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Example i-Tree Canopy point locations to derive tree canopy cover change ................................ 26 Change in Bloomington's tree canopy cover over 50 years ........................................................... 27 Tree canopy change from 2008 to 2018 within Bloomington, IN (2018) ..................................... 28 Tree canopy health of the City of Bloomington, IN (2018)........................................................... 34 Forest fragmentation within the City of Bloomington, IN (2018) ................................................. 36

Appendices A. Methodology and Accuracy Assessment B. Indiana University Bloomington Campus Maps

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Assignment The assignment by the City of Bloomington was to provide digital imagery showing detailed leafon conditions that translate into different land cover classifications for individual geographic information system (GIS) layers. Five land cover GIS layers have been provided to the city: tree canopy (trees/forest/shrub); grass/low-lying vegetation (grass/meadow); impervious surfaces; bare soil; and open water. The area and percentage of tree canopy were calculated and are spatially explicit for the following geographic units: census tracts, city-owned parcels, citywide, council districts, Indiana University campus, neighborhood associations, parks, watersheds, and zoning.

The existing and possible UTC was assessed for each geographic unit. Possible tree canopy is the amount of land that is theoretically available for the establishment of tree canopy within the city boundary. This includes all pervious and bare soil surfaces.

The preferred plantable area was determined by identifying reasonable “real world� areas to plant trees. These areas include the pervious surfaces within highways, streets, parks, and residential parcels.

A report of percentages of historical tree canopy cover and other land cover classes, which can be estimated and compared with present tree canopy, is provided. This is a useful analysis to assess changes in and effects of land use modifications over time.

DRG estimated the ecosystem services existing tree canopy provides stormwater runoff reduction, air quality improvement, and carbon sequestration. Also provided was a socio-demographic and economic analysis.

DRG created a customized version of the Urban Tree Resource Analysis and Cost Estimator (UTRACE) tool for the city to model multiple planting scenarios. UTRACE will allow the City of Bloomington to select a desired tree canopy goal percent for neighborhoods. The UTRACE tool will then determine the number of trees feasible for the planting space and the estimated cost of planting those trees.

A Web-Based Story Map using online capabilities combined with GIS data was provided. The story map can be found at: https://gis.davey.com/BloomingtonINTrees/. Using this online mapping technology provides Bloomington with a simplified educational tool that may serve as a useful public relations portal.

In addition to this assessment, DRG has provided GIS data files, a narrative of the classification methodology, metadata, ExcelTM spreadsheet containing land cover metrics and environmental benefits analyses, and slide show of results. Detailed methodologies for each assessment are presented in Appendix A.

Existing Tree Canopy

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Possible Tree Canopy

Preferred Plantable Areas

Prioritized Planting Areas

1

Historical Land Cover Change Assessment

Urban Tree Resource Analysis and Cost Estimator

Ecosystem Benefits Analysis

September 2019

Land Cover Analysis The 2018 National Agricultural Imagery Program (NAIP) leaf-on, multispectral imagery acquired and processed by the United States Department of Agriculture (USDA) was used as the primary source to identify the city’s current land cover (USDA 2018). Land cover data including tree canopy, pervious, impervious, open water, and bare soils were generated for the City of Bloomington. Pervious land cover is a vegetated area that allows rainfall to infiltrate the soil and typically includes parks, golf courses, and residential lawns. Impervious land cover is an area that does not allow rainfall to infiltrate and typically includes buildings, roads, and parking lots. Land cover areas and percentages of tree canopy were calculated and made spatially explicit for the following geographic units: census tracts, city-owned parcels, citywide, council districts, Indiana University campus, neighborhood associations, parks, watersheds, and zoning. This report summarizes the land cover citywide and by neighborhood, watershed, and zoning geographical areas.

Citywide Land Cover The boundary lines of the City of Bloomington cover 15,000 acres or 23 square miles. The 2018 UTC assessment found the city to have a 38% tree canopy coverage or 5,735 tree canopy acres.

Pervious surfaces (grasses and low vegetation) and bare soils cover 27%. All other land cover types (buildings, roads, other impervious, and open water) make up the remaining 35% of the total land area acres. Table 1 presents the results of all land cover classifications for the city limits of Bloomington. Figure 2 illustrates the resulting distribution of land cover for the city limits of Bloomington. Indiana University campus has 20% tree canopy coverage, with 48% as impervious surface coverage (Appendix B).

Table 1. Results of Land Cover Classification Analysis for Bloomington, IN (2018).

Davey Resource Group

Land Cover Classification Tree Canopy

5,735.22

38.24%

Impervious Surfaces

5,063.85

33.76%

Pervious Surfaces

3,640.80

24.27%

Bare Soil

435.22

2.90%

Open Water

124.83

0.83%

Acres

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Figure 2. City of Bloomington urban tree canopy assessment results (2018).

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Neighborhood Land Cover The City of Bloomington is comprised of 62 neighborhoods with tree canopy ranging from less than 1 acre to 342 acres (Table 2).

Evergreen Village has the lowest tree canopy acreage (0.44 acre) and canopy coverage percent (11%). Sunflower Gardens and North Kinser Point also have low tree canopy coverage percentages. Currently, the neighborhoods of Woodlands-Winding Brook, South Griffy, and Bittner Woods have the highest percentages or tree canopy coverage with all greater than 59%. Old Northeast Downtown has the greatest percentage of impervious surface coverage at 72%, thus trees would be beneficial in this neighborhood. Figure 3 presents an illustrated view of the resulting distribution of tree canopy by Bloomington neighborhood.

Table 2. Results of Land Cover Classification Analysis by Neighborhood for Bloomington, Indiana (2018).

Neighborhood

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6th and Ritter Arden Place Arlington Valley Mobile Home Park Ashwood Autumn View Barclay Gardens Bentley Court Bittner Woods Blue Ridge Broadview Bryan Park Bryan Park/Elm Heights Covenanter Covenanter/Eastside Crescent Bend Crestmont Eastern Heights Eastside Elm Heights Fritz Terrace Garden Hill Gentry Estates Grandview Hills

Acres 16.08 26.93

Canopy Acres Percent 6.96 43.28% 12.81 47.57%

Impervious Acres Percent 5.92 36.82% 6.63 24.62%

Pervious Acres Percent 3.20 19.90% 7.41 27.52%

Bare Soil Acres Percent 0.00 0.00% 0.07 0.26%

Water Acres Percent 0.00 0.00% 0.00 0.00%

41.65

18.99

45.59%

15.00

36.01%

7.65

18.37%

0.00

0.00%

0.00

0.00%

25.10 8.32 144.05 8.86 20.73 150.01 220.34 193.36 6.73 221.73 1.22 207.41 37.34 48.17 97.20 342.35 93.80 60.81 71.34 64.76

12.35 2.24 71.22 3.90 14.64 73.41 79.71 72.81 2.56 111.02 0.59 106.00 7.29 17.58 40.40 130.91 36.64 14.51 23.72 25.79

49.20% 26.92% 49.44% 44.02% 70.62% 48.94% 36.18% 37.66% 38.04% 50.07% 48.36% 51.11% 19.52% 36.50% 41.56% 38.24% 39.06% 23.86% 33.25% 39.82%

7.84 3.07 40.16 3.56 3.24 39.99 67.53 76.07 3.08 61.70 0.36 42.74 18.08 13.67 33.30 151.52 31.84 37.50 27.83 17.64

31.24% 36.90% 27.88% 40.18% 15.63% 26.66% 30.65% 39.34% 45.77% 27.83% 29.51% 20.61% 48.42% 28.38% 34.26% 44.26% 33.94% 61.67% 39.01% 27.24%

4.81 2.99 31.49 1.38 2.85 36.30 70.87 43.52 1.09 48.59 0.28 51.57 11.91 16.92 23.49 59.84 25.30 8.78 19.56 21.31

19.16% 35.94% 21.86% 15.58% 13.75% 24.20% 32.16% 22.51% 16.20% 21.91% 22.95% 24.86% 31.90% 35.13% 24.17% 17.48% 26.97% 14.44% 27.42% 32.91%

0.11 0.02 1.17 0.01 0.00 0.32 2.23 0.95 0.00 0.42 0.00 7.06 0.05 0.00 0.00 0.08 0.01 0.01 0.00 0.02

0.44% 0.24% 0.81% 0.11% 0.00% 0.21% 1.01% 0.49% 0.00% 0.19% 0.00% 3.40% 0.13% 0.00% 0.00% 0.02% 0.01% 0.02% 0.00% 0.03%

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.23 0.00

0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.01% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.32% 0.00%

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Neighborhood

Acres

Green Acres Hearthstone Village High Point High Point/Old Northeast Highland Village Hoosier Acres Hyde Park Village Longwood-Devon Maple Heights Matlock Heights McDoel Gardens Moss Creek Village Near West Side North Kinser Point Northwood Estates Old Northeast Downtown Park Ridge Park Ridge East Peppergrass Pigeon Hill Pinestone Prospect Hill Rockport Hills Saint James Woods Sherwood Oaks SoMax South Griffy Southern Pines Spicewood Sunflower Gardens Sunny Slopes Sycamore Knolls Timber Ridge Trail View

137.86 9.17 1.84 29.67 67.08 177.97 11.52 12.43 99.96 131.41 115.52 10.31 116.11 151.02 26.11 164.27 84.91 160.11 40.12 20.75 16.59 148.13 15.38 12.80 234.80 71.05 108.60 33.64 81.58 10.94 26.37 143.91 4.14 7.02

Canopy Acres Percent 51.09 37.06% 1.75 19.08% 0.75 40.76% 7.19 24.23% 15.94 23.76% 67.50 37.93% 4.63 40.19% 5.64 45.37% 27.40 27.41% 68.90 52.43% 28.44 24.62% 3.08 29.87% 42.46 36.57% 23.59 15.62% 6.75 25.85% 29.32 17.85% 30.62 36.06% 59.66 37.26% 16.10 40.13% 10.79 52.00% 6.36 38.34% 40.29 27.20% 3.90 25.36% 2.72 21.25% 101.36 43.17% 32.33 45.50% 66.48 61.22% 9.92 29.49% 46.53 57.04% 1.32 12.07% 9.66 36.63% 70.65 49.09% 1.36 32.85% 2.45 34.90%

Impervious Acres Percent 54.34 39.42% 4.11 44.82% 0.89 48.37% 19.63 66.16% 33.52 49.97% 43.34 24.35% 3.79 32.90% 3.26 26.23% 54.55 54.57% 24.10 18.34% 64.47 55.81% 4.40 42.68% 50.22 43.25% 6.79 4.50% 11.77 45.08% 117.81 71.72% 29.42 34.65% 55.12 34.43% 14.91 37.16% 5.71 27.52% 6.85 41.29% 86.83 58.62% 5.82 37.84% 6.87 53.67% 69.16 29.45% 21.75 30.61% 15.86 14.60% 10.66 31.69% 21.31 26.12% 5.37 49.09% 8.22 31.17% 37.61 26.13% 1.97 47.58% 2.88 41.03%

Pervious Acres Percent 32.43 23.52% 2.89 31.52% 0.21 11.41% 2.86 9.64% 17.62 26.27% 66.94 37.61% 3.09 26.82% 3.44 27.67% 17.60 17.61% 38.28 29.13% 22.48 19.46% 2.15 20.85% 23.12 19.91% 111.82 74.04% 7.58 29.03% 17.14 10.43% 24.75 29.15% 45.26 28.27% 8.96 22.33% 4.25 20.48% 3.26 19.65% 21.00 14.18% 5.35 34.79% 3.19 24.92% 62.64 26.68% 16.95 23.86% 26.19 24.12% 11.76 34.96% 13.38 16.40% 4.09 37.39% 8.23 31.21% 34.96 24.29% 0.64 15.46% 1.69 24.07%

Bare Soil Acres Percent 0.00 0.00% 0.01 0.11% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.05 0.03% 0.00 0.00% 0.09 0.72% 0.41 0.41% 0.13 0.10% 0.14 0.12% 0.04 0.39% 0.31 0.27% 8.81 5.83% 0.00 0.00% 0.00 0.00% 0.12 0.14% 0.07 0.04% 0.15 0.37% 0.00 0.00% 0.12 0.72% 0.02 0.01% 0.31 2.02% 0.02 0.16% 1.14 0.49% 0.02 0.03% 0.08 0.07% 1.29 3.83% 0.36 0.44% 0.16 1.46% 0.25 0.95% 0.69 0.48% 0.17 4.11% 0.00 0.00%

Water Acres Percent 0.00 0.00% 0.40 4.36% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.14 0.08% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.65 6.30% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.50 0.21% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00 0.00%

Davey Resource Group

Neighborhood

Acres

Walnut Creek Waterman West Pointe Woodlands-Winding Brook

15.45 36.81 26.37 10.83

Canopy Acres Percent 8.38 54.24% 18.00 48.90% 7.82 29.65% 6.40

59.10%

Impervious Acres Percent 5.02 32.49% 10.89 29.58% 10.90 41.33% 3.01

27.79%

Pervious Acres Percent 2.05 13.27% 7.91 21.49% 7.65 29.01% 1.36

12.56%

Bare Soil Acres Percent 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.06

0.55%

Water Acres Percent 0.00 0.00% 0.00 0.00% 0.00 0.00% 0.00

0.00%

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Figure 3. Percentages of tree canopy cover by neighborhood in Bloomington, IN (2018).

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Sub Watershed Land Cover Bloomington is located in White River Watershed with most of the city limits present within the Lower East Fork Basin. Sub watersheds within the city limits of Bloomington consist of 14, all listed in Table 3. Sub watersheds range from 0% tree canopy coverage to 76% tree canopy coverage. Richland Creek-Cave Creek, Clear Creek-Lower, and Clear Creek-Sinking Creek sub watersheds have percentages of tree canopy coverage less than 17%. Bloomington’s Clear Creek-West Fork, Bean Blossom-Griffy Creek Upper, and Bean BlossomGriffy Lake sub watersheds have the greatest percent of tree canopy coverage greater than 38%. Clear Creek-Central watershed has the largest acreage of tree canopy with 1,371 acres followed closely by Clear Creek-Jackson Creek with 1,067 acres. Clear Creek-Lower has the greatest percentage of impervious surface coverage at 65%, thus trees would be beneficial in this sub watershed. Figure 4 presents an illustrated view of the resulting distribution of tree canopy by Bloomington sub watershed.

Table 3. Results of Land Cover Classification Analysis by Sub Watershed for Bloomington, IN (2018).

Sub Watersheds Bean Blossom-Cascade Creek

Acres

Canopy Acres

Percent

Impervious Acres

Percent

Pervious Acres

Bare Soil

Water

Percent

Acres

Percent

Acres

Percent

8

1,904.34

653.05

34.29%

701.57

36.84%

529.36

27.80%

19.91

1.05%

0.46

0.02%

Bean Blossom-Griffy Creek

208.27

73.59

35.33%

33.82

16.24%

95.14

45.68%

5.71

2.74%

0.00

0.00%

Bean Blossom-Griffy Creek Upper

1,232.82

626.86

50.85%

203.67

16.52%

217.12

17.61%

179.21

14.54%

5.96

0.48%

Bean Blossom-Griffy Lake

1,075.31

815.73

75.86%

57.35

5.33%

71.39

6.64%

28.78

2.68%

102.05

9.49%

460.89

135.44

29.39%

124.32

26.97%

175.22

38.02%

25.60

5.55%

0.31

0.07%

4,479.85

1,371.27

30.61%

2,015.01

44.98%

1,002.05

22.37%

88.16

1.97%

3.36

0.08%

510.93

163.24

31.95%

177.90

34.82%

163.48

32.00%

3.37

0.66%

2.94

0.58%

3,001.13

1,128.14

37.59%

1,067.17

35.56%

788.18

26.26%

12.17

0.41%

5.47

0.18%

55.90

19.9

35.60%

18.23

32.61%

17.03

30.47%

0.75

1.34%

0.00

0.00%

4.67

0.14

3.00%

3.02

64.67%

0.54

11.56%

0.97

20.77%

0.00

0.00%

210.46

34.16

16.23%

128.44

61.03%

46.51

22.10%

1.36

0.65%

0.00

0.00%

1,710.20

665.07

38.89%

476.57

27.87%

495.52

28.97%

68.77

4.02%

4.27

0.25%

145.08

48.65

33.53%

56.78

39.14%

39.20

27.02%

0.46

0.32%

0.00

0.00%

0.06

0.00

0.00%

0.00

0.00%

0.06

100.00%

0.00

0.00%

0.00

0.00%

Bean Blossom-Stout Creek Clear Creek-Central Clear Creek-East Fork Jackson Clear Creek-Jackson Creek Clear Creek-Leonard Springs Clear Creek-Lower Clear Creek-Sinking Creek Clear Creek-West Fork Lake Monroe-Stephens Creek Richland Creek-Cave Creek

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Figure 4. Percentages of tree canopy cover based on sub watersheds of Bloomington, IN (2018).

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Zoning Type Land Cover Acreage of tree canopy among zoning types in Bloomington range from 8 to 2,009 acres (Table 4). Planned Unit Development, Residential Single-Family, and Institutional zoning types have the greatest tree canopy acreage, totaling 4,578 acres. Interestingly, planned unit development has the largest amount of impervious surface coverage (1,305 acres). The Residential Estate zoning type has the greatest percentage of tree canopy cover at 53%, and only 4% of impervious surface cover. Clear Creek-Lower has the greatest percentage of impervious surface coverage at 65%, thus trees would be beneficial in this sub watershed.

Figure 5 illustrates the City of Bloomington zoning type locations. Medical and Commercial Limited, Downtown and Arterial zoning types have the lowest percentages of tree canopy cover, all below 20% (Figure 6); Medical and Commercial Downtown, Arterial, General and Limited zoning types have the highest percentages of impervious surface coverage all above 60% (Figure 7).

Table 4. Results of Land Cover Classification Analysis by Zoning Type for Bloomington, Indiana (2018) Zoning Type Business Park Commercial Arterial Commercial Downtown Commercial General Commercial Limited Industrial General Institutional

Acres

Canopy Acres

Percent

Impervious Acres

Pervious

Percent

Acres

Percent

Bare Soil Acres

Percent

Water Acres

Percent

283.41

77.64

27.39%

34.49

12.17%

154.66

54.57%

16.31

5.75%

0.31

0.11%

623.46

108.11

17.34%

418.20

67.08%

88.85

14.25%

8.30

1.33%

0.00

0.00%

295.45

23.31

7.89%

245.74

83.17%

20.75

7.02%

5.65

1.91%

0.00

0.00%

255.59

55.09

21.55%

159.16

62.27%

40.90

16.00%

0.45

0.18%

0.00

0.00%

55.81

7.96

14.26%

35.18

63.04%

12.58

22.54%

0.08

0.14%

0.00

0.00%

120.73

29.97

24.82%

63.15

52.31%

22.86

18.93%

4.75

3.93%

0.00

0.00%

4,250.83 2,009.00

47.26%

872.02

20.51%

984.27

23.15% 277.80

6.54%

107.74

2.53%

Manufactured/Mob ile Home Park

93.74

33.21

35.43%

36.17

38.59%

24.07

25.68%

0.30

0.32%

0.00

0.00%

Medical

75.50

11.46

15.18%

55.96

74.12%

8.08

10.70%

0.00

0.00%

0.00

0.00%

33.46% 1,304.53

38.67%

863.63

25.60%

62.4

1.85%

13.88

0.41%

Planned Unit Development

3,373.11 1,128.66

Quarry

111.15

52.10

46.87%

17.29

15.56%

25.26

22.73%

15.63

14.06%

0.87

0.78%

Residential Core

882.88

365.97

41.45%

339.59

38.46%

176.80

20.03%

0.52

0.06%

0.00

0.00%

78.79

52.94

67.19%

4.36

5.53%

21.27

27.00%

0.23

0.29%

0.00

0.00%

684.61

152.39

22.26%

386.22

56.41%

138.27

20.20%

7.17

1.05%

0.56

0.08%

512.49

183.93

35.89%

226.68

44.23%

98.67

19.25%

2.66

0.52%

0.55

0.11%

3,207.06 1,439.92

44.90%

818.50

25.52%

932.31

29.07%

15.43

0.48%

0.91

0.03%

Residential Estate Residential HighDensity Multifamily Residential Multifamily Residential SingleFamily

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September 2019

Figure 5. The City of Bloomington zoning type descriptions and locations (2018).

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September 2019

Figure 6. Percentages of tree canopy cover by zoning type in Bloomington, Indiana (2018).

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September 2019

Figure 7. Percentages of impervious surface cover by zoning type in Bloomington, IN (2018).

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September 2019

Ecological and Economic Services The amount of tree canopy drives the amount of benefits that an urban forest provides. Trees conserve energy, reduce carbon dioxide levels, improve air quality, and mitigate stormwater runoff. In addition, trees provide numerous economical, psychological, and social benefits.

Both i-Tree Canopy and i-Tree Hydro were used to assess and quantify the ecosystem benefits of Bloomington’s canopy. Estimated ecosystem benefits, including carbon storage, carbon sequestration, pollution removal, and stormwater runoff values, were calculated. Air pollutants included in estimates are carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and particulate matter (PM10).

Citywide Ecosystem Services Bloomington’s 5,735 acres of tree canopy has an estimated ecosystem value equal to $35,306,070 and annually provides the community savings-benefit equal to $1,931,905 (Table 5). The tree canopy’s carbon storage capacity is 720,088 tons ($33,374,120) while annually sequestering an additional 28,673 tons ($1,328,918) from the air and annually removing 470,380 pounds ($59,694) of pollutants from the air. By way of public and private trees, the City of Bloomington annually avoids the runoff of 90,556,345 gallons ($543,338) of stormwater.

Table 5. Results of Ecosystem Benefits Analysis for the City of Bloomington (2018) Ecosystem Services Air Quality

Units (pounds) CO

12,340

$642

NO2

36,860

$700

O3

245,800

$24,078

SO2

33,580

$315

PM10

141,800

$33,959

Carbon

Units (tons)

Value ($)

Storage

720,088

$33,374,120

Sequestration

28,673

$1,328,918

Stormwater Avoided Runoff

Davey Resource Group

Value ($)

Units (gallons)

Value ($)

90,556,345

$543,338

Annual Value

$1,931,950

Total Value

$35,306,070

14

September 2019

A Closer Look at Stormwater Benefits Urban trees help manage stormwater runoff depth, time of concentration, peak flow, and volume. With the presence of trees in the urban environment, there is less need for investment in man-made stormwater structures to accommodate peak flows during storm events. i-Tree Hydro, DRG has captured how Bloomington benefits from having urban trees. The model used stormwater data from the 2005 to 2012 to estimate runoff managed by trees and pollutants managed by trees.

The City of Bloomington’s 2018 tree canopy cover is 38%. Bloomington’s trees intercepted an average of 90,556,345 gallons over 8 years. An acre of canopy manages 15,790 gallons annually. Avoided pollutants reaching storm drains is approximately 97,936 pounds annually (Table 6).

Figure 8. Stormwater benefits.

Table 6. Stormwater Pollutant Runoff Benefits Based on 2018 Tree Canopy of 38%.

Pollutant

Mean Concentration

Units (pounds)

Median Mean Median Mean Median

35,973 51,748 7,591 9,307 29,505

Mean Median Mean Median Mean Median Mean Median Mean Median Mean

34,851 171 208 68 85 970 1,142 478 595 74,755 97,936

Suspended Solids Biochemical Oxygen Demand Chemical Oxygen Demand Phosphorus Soluble Organic Pollutants Total Kjeldhal Nitrogen Other Total Pollutant Load

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September 2019

Citywide Aesthetic and Other Benefits Many benefits of tree canopy, such as wildlife habitat, well-being, shading, and beautification, are difficult to quantify into economic terms. When accounting for how these and other intangible services affect people and places, property value is often used as an indicator. To provide some estimation of these intangible services, DRG will calculate and report on property value based on the average value of home prices for the project area. Limitations to this approach include determining actual value of individual trees on a property and extrapolation of residential trees to other land use categories.

The methods applied utilized a study completed in 1988, it was found that single-family residences in Athens, Georgia had a 0.88% increase in the average home sale price for every large front-yard tree on the property. Using this study, DRG utilized sales price increase as an indicator of additional tree benefits. Because home sale can vary widely, DRG used 0.88% as a multiplier to determine the value of a large front yard tree. This value was then converted into annual benefits by dividing the total added value by the estimated leaf surface area of a 30-year-old shade tree.

The total annual benefit associated with property value increases and other tangible and intangible benefits of tree canopy is $19,688,555. The average benefit per acre equals $3,433 per year.

Socio-Demographic and Economic Analyses DRG performed a socio-demographic and economic data analysis for the City of Bloomington.

Data from the 2010 census were aggregated for census tracts to help determine trends and correlations with the existence of tree canopy. Factors included in the analysis: population density, ownership (owner vs renter vs vacant), median income, age group, education, single-family homes, and building age. Land cover data were assessed on the city level, planning areas, and census tracts.

All analyses are included in the urban tree canopy deliverable Excel™ spreadsheets accompanying this report on USB. Figure 8 presents an illustrated view of where Bloomington neighborhoods fall within the city’s density of population distribution. Conclusions made from Figures 9 and 3 will benefit future canopy planning. One goal would be to create new tree canopy where densities of the citizen population are highest and tree canopy coverage is lowest. Equity of the tree canopy utilizing sociodemographic and economic data is often part of developing a master urban forest plan for the community.

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September 2019

Figure 9. City of Bloomington population density among neighborhoods (2018).

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September 2019

Projected and Preferred Tree Canopy Whether the City of Bloomington wants to increase or maintain tree canopy, setting goals will help organize tree planting programs and direct tree preservation. Establishing realistic and achievable tree canopy goals will help capitalize on the economic, environmental, and social benefits trees provide to the community.

Possible tree canopy is the total of all land cover that is pervious and bare soil. While it is theoretically possible that all pervious surfaces and bare soils could represent future tree canopy, considering all land use areas is understandably not practical for implementing actual planting projects nor is it realistic for urban forest planning and management.

Possible plantable area can be refined to provide consideration for current or future planned land use. These areas are called preferred plantable areas. Preferred plantable area is based on a “real world� approach to the identification of reasonable areas to plant trees. Preferred plantable area includes the pervious surfaces within highways corridors, streets, parks, and residential parcels within the City of Bloomington. Excluded from the analysis are land uses, such as agricultural land, cemeteries, golf courses, utility rights-of-way, recreational fields, etc., and referred to as other pervious surfaces.

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September 2019

Citywide Projected and Preferred Tree Canopy 100%

Percent of Projected Tree Canopy (Green 60.62%)

The City of Bloomington’s existing tree canopy is 38%; the possible tree canopy is 27%; and the preferred plantable area is 22%, making the maximum tree canopy attainable under current development conditions at 61% (Figure 10). Reaching the projected tree canopy potential of 61% will require the City of Bloomington to preserve all existing tree canopy while expanding the urban forest in designated preferred plantable areas.

Indiana University campus has 303 acres or 25% of preferred plantable space. Indiana University’s projected maximum tree canopy is 45% (Appendix B).

90% 80%

38.24%

70% 60% 50% 40%

22.38% 4.79%

30% 20%

33.76%

10% 0% Existing Canopy Preferred Plantable Other Pervious Surfaces Impervious Surfaces Open Water

0.83% Citywide Acres 5,735.22 3,357.45 718.57 5,063.85 124.83

Figure 10. Projected tree canopy potential within the City of Bloomington, IN (2018).

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September 2019

Neighborhoods Projected and Preferred Tree Canopy The neighborhoods of Matlock Heights, Bittner Woods, and South Griffy all have maximum tree canopy potential above 80% (Table 7). Neighborhoods with the greatest potential to increase their percentage of tree canopy (preferred plantable area over 30%) include Evergreen, Hoosier Acres, Southern Pines, Eastern Heights, Rockport Hills, North Kinser Point, Sunny Slopes, Broadview, Autumn View, and Grandview Hills. The neighborhoods of Crescent Bend, Elm Heights, Sherwood Oaks, Hoosier Acres, and Broadview have the greatest preferred plantable area all with more than 55 acres of plantable space. High Point, Covenanter/Eastside, Timber Ridge, and Bryan Park/Elm Heights have the least preferred plantable area with less than 1 acre.

Table 7. Results of Projected Potential Tree Canopy Analysis for Bloomington, IN Neighborhoods (2018).

Neighborhood

Acres

6th and Ritter Arden Place Arlington Valley Mobile Home Park Ashwood Autumn View Barclay Gardens Bentley Court Bittner Woods Blue Ridge Broadview Bryan Park Bryan Park/Elm Heights Covenanter Covenanter/Eastside Crescent Bend Crestmont Eastern Heights Eastside Elm Heights Evergreen Village Fritz Terrace Garden Hill Gentry Estates Grandview Hills Green Acres Hearthstone Village High Point High Point/Old Northeast Highland Village Hoosier Acres Hyde Park Village Longwood-Devon

16.08 26.93

6.96 12.81

43.28% 47.57%

3.20 7.48

19.90% 27.78%

2.89 6.94

17.97% 25.77%

Maximum Tree Canopy 61.26% 73.34%

41.65

18.99

45.59%

7.65

18.37%

5.43

13.04%

58.63%

25.10 8.32 144.10 8.86 20.73 150.00 220.30 193.40

12.35 2.24 71.22 3.90 14.64 73.41 79.71 72.81

49.20% 26.92% 49.44% 44.02% 70.62% 48.94% 36.18% 37.66%

4.92 3.01 32.66 1.39 2.85 36.62 73.10 44.47

19.60% 36.18% 22.67% 15.69% 13.75% 24.41% 33.18% 23.00%

4.31 2.56 30.41 1.02 2.62 33.20 67.80 36.10

17.17% 30.77% 21.11% 11.51% 12.64% 22.13% 30.77% 18.67%

66.37% 57.69% 70.55% 55.53% 83.26% 71.07% 66.95% 56.32%

6.73

2.56

38.04%

1.09

16.20%

0.96

14.26%

52.30%

221.70 1.22 207.40 37.34 48.17 97.20 342.40 4.08 93.80 60.81 71.34 64.76 137.90 9.17 1.84

111.02 0.59 106.00 7.29 17.58 40.40 130.91 0.44 36.64 14.51 23.72 25.79 51.09 1.75 0.75

50.07% 48.36% 51.11% 19.52% 36.50% 41.56% 38.24% 10.78% 39.06% 23.86% 33.25% 39.82% 37.06% 19.08% 40.76%

49.01 0.28 58.63 11.96 16.92 23.49 59.92 1.98 25.31 8.79 19.56 21.33 32.43 2.90 0.21

22.10% 22.95% 28.27% 32.03% 35.13% 24.17% 17.50% 48.53% 26.98% 14.45% 27.42% 32.94% 23.52% 31.62% 11.41%

45.51 0.26 55.99 10.34 15.88 22.23 56.39 1.73 22.29 7.75 17.67 19.79 29.70 2.35 0.19

20.52% 21.31% 26.99% 27.69% 32.97% 22.87% 16.47% 42.40% 23.76% 12.74% 24.77% 30.56% 21.54% 25.63% 10.33%

70.59% 69.67% 78.10% 47.21% 69.46% 64.43% 54.71% 53.19% 62.83% 36.61% 58.02% 70.38% 58.60% 44.71% 51.09%

29.67

7.19

24.23%

2.86

9.64%

2.60

8.76%

33.00%

67.08 178.00 11.52 12.43

15.94 67.50 4.63 5.64

23.76% 37.93% 40.19% 45.37%

17.62 66.99 3.09 3.53

26.27% 37.64% 26.82% 28.40%

15.85 62.48 2.80 3.26

23.63% 35.11% 24.31% 26.23%

47.39% 73.03% 64.50% 71.60%

Davey Resource Group

Existing Canopy Acres

Percent

Possible Canopy Acres

20

Percent

Preferred Plantable Acres

Percent

September 2019

Neighborhood

Acres

Maple Heights Matlock Heights McDoel Gardens Moss Creek Village Near West Side North Kinser Point Northwood Estates Old Northeast Downtown Park Ridge Park Ridge East Peppergrass Pigeon Hill Pinestone Prospect Hill Rockport Hills Saint James Woods Sherwood Oaks SoMax South Griffy Southern Pines Spicewood Sunflower Gardens Sunny Slopes Sycamore Knolls Timber Ridge Trail View Walnut Creek Waterman West Pointe Woodlands-Winding Brook

99.96 131.40 115.50 10.31 116.10 151.00 26.11

27.40 68.90 28.44 3.08 42.46 23.59 6.75

27.41% 52.43% 24.62% 29.87% 36.57% 15.62% 25.85%

18.01 38.41 22.62 2.19 23.43 120.63 7.58

18.02% 29.23% 19.58% 21.24% 20.18% 79.88% 29.03%

17.08 37.08 21.77 1.89 18.7 47.22 6.57

17.09% 28.22% 18.85% 18.33% 16.11% 31.27% 25.16%

Maximum Tree Canopy 44.50% 80.65% 43.46% 48.21% 52.67% 46.89% 51.01%

164.30

29.32

17.85%

17.14

10.43%

16.14

9.83%

27.67%

84.91 160.10 40.12 20.75 16.59 148.10 15.38 12.80 234.80 71.05 108.60 33.64 81.58 10.94 26.37 143.90 4.14 7.02 15.45 36.81 26.37

30.62 59.66 16.10 10.79 6.36 40.29 3.90 2.72 101.36 32.33 66.48 9.92 46.53 1.32 9.66 70.65 1.36 2.45 8.38 18.00 7.82

36.06% 37.26% 40.13% 52.00% 38.34% 27.20% 25.36% 21.25% 43.17% 45.50% 61.22% 29.49% 57.04% 12.07% 36.63% 49.09% 32.85% 34.90% 54.24% 48.90% 29.65%

24.87 45.33 9.11 4.25 3.38 21.02 5.66 3.21 63.78 16.97 26.27 13.05 13.74 4.25 8.48 35.65 0.81 1.69 2.05 7.91 7.65

29.29% 28.31% 22.71% 20.48% 20.37% 14.19% 36.80% 25.08% 27.16% 23.88% 24.19% 38.79% 16.84% 38.85% 32.16% 24.77% 19.57% 24.07% 13.27% 21.49% 29.01%

23.34 37.66 8.12 4.02 2.90 19.81 5.07 2.81 58.16 15.42 25.46 11.51 11.74 2.96 8.12 31.80 0.46 1.69 1.55 7.48 6.55

27.49% 23.52% 20.24% 19.37% 17.48% 13.37% 32.96% 21.95% 24.77% 21.70% 23.44% 34.22% 14.39% 27.06% 30.79% 22.10% 11.11% 24.07% 10.03% 20.32% 24.84%

63.55% 60.78% 60.37% 71.37% 55.82% 40.57% 58.32% 43.20% 67.94% 67.21% 84.66% 63.70% 71.43% 39.12% 67.43% 71.19% 43.96% 58.97% 64.27% 69.22% 54.49%

10.83

6.40

59.10%

1.42

13.11%

1.12

10.34%

69.44%

Davey Resource Group

Existing Canopy Acres

Percent

Possible Canopy Acres

21

Percent

Preferred Plantable Acres

Percent

September 2019

Sub Watershed Projected and Preferred Tree Canopy Bloomington’s sub watersheds for where there is preferred plantable area range from 0 acre to 908 acres and their projected maximum tree canopy range from 35% to 100% (Figure 11). Richland Creek-Cave Creek, Bean Blossom-Griffy Lake, and Bean Blosom-Griffy Creek Upper all have maximum tree canopy potential greater than 80%. Comparing available acreage for tree planting, sub watersheds with more than 400 acres available include Clear Creek-Central, Clear Creek Jackson Creek, and Clear Creek-West Fork; and sub watersheds with less than 20 acres available include Richland Creek-Cave Creek, Clear Comparatively Creek-Lower, and Clear Creek-Leonard Springs. Bean Blossom-Griffy Lake is among the sub watersheds with the greatest potential for tree canopy cover, but it is one of the sub watersheds with the smallest area for tree planting potential by acreage. Bean Blossom-Griffy Creek Upper is among the sub watersheds with the greatest potential for tree canopy cover, and it is one of the sub watersheds with the largest area for tree planting potential by acreage. Planting trees in Bean-Blossom-Griffy Creek Upper will have a better impact on increased tree canopy and preserving trees in Bean Blossom-Griffy Lake will have a better impact on maintaining tree canopy.

Zoning Type Projected and Preferred Tree Canopy Residential Estate, Quarry, and Institutional zoning types have the greatest potential for tree canopy cover with about 70% or more potential. Not far behind are Residential Core, Planned Unit Development, Manufactured/Mobile Home Park, and Business Park all with near 60% potential tree canopy cover (Figure 12). Institutional, Residential Single-Family, and Planned Unit Development have more than 700 acres available for tree planting. Medical, Commercial Limited, and Manufactured/Mobile Home Park zoning types have less than 20 acres of available tree planting. Tree planting will have a great impact on expanding tree canopy while preserving and caring for existing trees in Institutional, Residential Single-Family, and Planned Unit Development zoning types. Residential Estate, Manufactured/Mobile Home Park, Residential Core, Residential Single-Family, Quarry, and Institutional zoning types will have a great impact on maintaining tree canopy cover.

Davey Resource Group

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September 2019

Richland Creek-Cave Creek

100.00%

Lake Monroe-Stephens Creek

33.53%

Clear Creek-West Fork

39.14%

38.89%

Clear Creek-Sinking Creek

38.89%

27.87%

24.81%

37.59%

Clear Creek-East Fork Jackson

10%

20%

16.24%

20.32% 30%

50%

60%

Clear CreekClear CreekClear CreekLeonard East Fork Jackson Creek Springs Jackson 163.24 1,128.14 19.90 140.33 678.77 13.87 177.90 1067.17 18.23 26.52 121.58 3.90 2.94 5.47 0.00

70%

2.43%

18.38%

36.84%

40%

Bean BlossomBean Blossom- Bean Blossom- Clear CreekBean Blossom- Bean BlossomGriffy Creek Griffy Lake Stout Creek Central Cascade Creek Griffy Creek Upper Existing Canopy Acres 653.05 73.59 626.86 815.73 135.44 1,371.27 Preferred Plantable Acres 387.04 62.57 366.42 90.18 140.95 908.38 Impervious Surfaces Acres 701.57 33.82 203.67 57.35 124.32 2015.01 Other Pervious Surfaces Acres 162.22 38.29 29.91 10.00 59.87 181.83 Open Water Acres 0.46 0.00 5.96 102.05 0.31 3.36

9.49%

16.52%

30.04%

34.29% 0%

5.33%

29.72%

35.33%

Bean Blossom-Cascade Creek

12.99% 8.39%

50.85%

Bean Blossom-Griffy Creek

4.06%

26.97%

75.86%

Bean Blossom-Griffy Creek Upper

5.19%

44.98% 30.58%

Bean Blossom-Griffy Lake

4.05%

34.82%

20.28%

29.39%

6.98%

35.56%

27.47%

30.61%

Bean Blossom-Stout Creek

32.61%

22.62%

31.95%

Clear Creek-Central

2.58%

64.67%

35.60%

Clear Creek-Jackson Creek

4.30%

61.03%

32.33%

Clear Creek-Leonard Springs

3.72%

28.69% 20.16%

Clear Creek-Lower 3.00%

Sub Watersheds

23.61%

8.52% 80%

90%

Clear CreekLower

Clear CreekSinking Creek

Clear CreekWest Fork

0.14 1.51 3.02 0.00 0.00

34.16 42.42 128.44 5.44 0.00

665.07 490.7 476.57 73.59 4.27

Lake MonroeStephens Creek 48.65 34.25 56.78 5.40 0.00

100% Richland Creek-Cave Creek 0.00 0.06 0.00 0.00 0.00

Figure 11. Results of the projected potential tree canopy analysis for Bloomington, IN sub watersheds (2018).

Davey Resource Group

22

September 2019

Residential Single Family Residential Multifamily Residential High-Density Multifamily Residential Estate

74.12%

9.91%

15.18%

Manufactured/Mobile Home Park

Commercial Limited Commercial General Commercial Downtown Commercial Arterial

83.17%

8.04%

7.89%

Business Park 77.64 95.90 34.49 75.07 0.31

10%

20%

30%

Commercial Commercial Commercial Commercial Arterial Downtown General Limited 108.11 87.02 418.20 10.13 0.00

23.31 23.75 245.74 2.65 0.00

55.09 38.07 159.16 3.27 0.00

7.96 11.65 35.18 1.02 0.00

40%

Industrial General

Institutional

29.97 25.80 63.15 1.81 0.00

2,009.00 947.40 872.02 314.67 107.74

26.49%

12.17%

33.84%

27.39% 0%

0.00 1.62%

67.08%

13.96%

17.34%

Business Park

1.28%

62.27%

14.89%

21.55%

1.83%

63.04%

20.87%

14.26%

2.53%

52.31%

21.37%

24.82%

7.40%

20.51%

22.29%

47.26%

Industrial General

5.62%

38.59%

20.36%

35.43%

Institutional

4.03%

38.67%

23.42%

33.46%

Medical

15.56%

36.55%

46.87%

Planned Unit Development Zoning Type

38.46%

18.88%

41.45%

Quarry

5.53%

26.40%

67.19%

Residential Core

Existing Canopy Acres Preferred Plantable Acres Impervious Surfaces Acres Other Pervious Surfaces Acres Open Water Acres

3.41%

56.41%

17.84%

22.26%

2.81%

44.23%

16.97%

35.89%

3.70%

25.52%

25.85%

44.90%

50% Manufacture d/Mobile Home Park 33.21 19.09 36.17 5.27 0.00

60%

70%

Medical

Planned Unit Development

Quarry

Residential Core

11.46 7.48 55.96 0.60 0.00

1,128.66 790.03 1304.53 136.01 13.88

52.10 40.62 17.29 0.27 0.87

365.97 166.66 339.59 10.66 0.00

80%

90%

100%

Residential Residential Residential Residential High-Density Multifamily Single Family Estate Multifamily 52.94 152.39 183.93 1,439.92 20.80 122.12 86.95 829.15 4.36 386.22 226.68 818.50 0.69 23.32 14.38 118.58 0.00 0.56 0.55 0.91

Figure 12. Results of the projected potential tree canopy analysis for Bloomington, IN zoning type (2018).

Davey Resource Group

23

September 2019

Prioritized Plantable Area DRG conducted a prioritized planting analysis to determine where the most preferred lands to plant are within Bloomington’s city limits. To prioritize planting areas, DRG assessed several environmental features, including existing tree canopy percent, proximity to hardscape, urban heat island index, floodplain proximity, soil permeability, soil erosion factor (K-factor), and slope.

Planting trees in areas of very high and high priority can reduce the risk of urban heat island effects, degradation from storm and flood events, as well as reducing soil loss and increasing urban forest connectivity.

Citywide Prioritized Plantable Area The plantable area analysis found 3,338 acres of public and private land with the potential for 61,702 plantable areas in Bloomington (Table 8). To be categorized for purpose or returned benefit, plantable Very High, High, Moderate, Low, and Very Low Levels further define areas. Very High and High plantable areas total 532 acres and an estimated 24,670 tree planting sites. Figure 13 presents an illustrated view of the resulting distribution of prioritized plantable tree area in Bloomington.

Table 8. Results of Prioritized Planting Area Analysis for Bloomington, Indiana (2018).

Priority Rank

Davey Resource Group

Number of Locations

Prioritized Plantable Area (Acres)

Very High

12,335

175.95

High

12,335

356.31

Moderate

12,258

416.91

Low

12,433

454.64

Very Low

12,341

1,934.49

Total

61,702

3,338.30

24

September 2019

Figure 13. Prioritized planting areas within Bloomington, IN (2018).

Davey Resource Group

25

September 2019

Tree Canopy Change A historical look at how tree canopy cover has changed for the City of Bloomington’s 2018 geographic area was performed using images from 1992, 1998, 2008, and 2018. To assess change in tree canopy cover for 2008, DRG isolated the tree canopy in land cover assessment and reran the land cover assessment for tree canopy only using the land cover methodology and the 2008 National Agricultural Imagery Program (NAIP) leaf-on, multispectral imagery acquired and processed by the United States Department of Agriculture (USDA 2008). Additionally, DRG utilized i-Tree Canopy to assess change in tree canopy cover for 2016 to 1998 and 1992. The i-Tree Canopy created a Google® Earth KML file of the random point locations within Bloomington’s 2018 city limits, and DRG photo interpreted the images to develop estimates of tree canopy (Figure 14).

1998

2016 Figure 14. Example i-Tree Canopy point locations to derive tree canopy cover change.

Davey Resource Group

26

September 2019

Citywide Tree Canopy Change From the year 2008 to the year 2018 (10 years), Bloomington’s tree canopy cover decreased by less than 2% or 243 acres. Using the city limits of 2018, the i-Tree Canopy analysis estimates a decrease of 54% tree canopy (approximately 8,034 acres). Figure 15 presents an illustration of tree canopy change for 1998, 2008, and 2018, and projects what canopy could be in 30 years under existing policies, planning, programs, and conditions. Similarly, Indiana University also had a reduction in canopy coverage. The tree canopy within Indiana University campus decreased by 7% over the last 10 years. Figure 16 presents an illustrated view of the resulting changes in tree canopy from 2008 to 2018 in Bloomington.

42%

40%

39%

40% 38%

38%

38%

37% 36%

37%

37%

35%

34%

33%

32%

30%

1998

2008

2018

2028

2038

2048

City of Bloomington Tree Canopy Change City of Bloomington Tree Canopy Projected Change over 10 Years (1.6%) City of Bloomington Tree Canopy Projected Change over 20 Years (0.6%)

Figure 15. Change in Bloomington’s tree canopy cover over 50 years.

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September 2019

Figure 16. Tree canopy change from 2008 to 2018 within Bloomington, IN (2018).

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September 2019

Neighborhood Tree Canopy Change The average change in tree canopy cover among the 65 neighborhoods of Bloomington is -3% (147 acres). The 2018 tree canopy results show neighborhoods Woodlands-Winding Brook, South Griffy, and Bittner Woods having the highest percentages of tree canopy cover for their geographical area (Table 9). Over the last 10 years, Woodlands-Winding Brook has lost 2% of their tree canopy, South Griffy has lost 4% of their tree canopy, and Bittner Woods has lost 9% of their tree canopy. Autumn View, Southern Pines, Northwood Estates, and Highland Village neighborhoods have all gained more than 10% tree canopy cover in the last 10 years within their geographical areas. Trail View, Longwood-Devon, and Eastern Heights neighborhoods have all lost more than 20% tree canopy cover in the last 10 years within their geographical areas.

Table 9. Results of Tree Canopy Change for Bloomington, Indiana per Neighborhood (2008-2018).

Neighborhood 6th and Ritter Arden Place Arlington Valley Mobile Home Park Ashwood Autumn View Barclay Gardens Bentley Court Bittner Woods Blue Ridge Broadview Bryan Park Bryan Park/Elm Heights Covenanter Covenanter/Eastside Crescent Bend Crestmont Eastern Heights Eastside Elm Heights Evergreen Village Fritz Terrace Garden Hill Gentry Estates Grandview Hills Green Acres Hearthstone Village High Point High Point/Old Northeast Highland Village

Davey Resource Group

Acres 16.08 26.93 41.65

Acres 2018 6.96 12.81 18.99

Percent 2018 43.28% 47.57% 45.59%

25.10 8.32 144.05 8.86 20.73 150.01 220.34 193.36 6.73 221.73 1.22 207.41 37.34 48.17 97.20 342.35 4.08 93.80 60.81 71.34 64.76 137.86 9.17 1.84 29.67 0.58

12.35 2.24 71.22 3.90 14.64 73.41 79.71 72.81 2.56 111.02 0.59 106.00 7.29 17.58 40.40 130.91 0.44 36.64 14.51 23.72 25.79 51.09 1.75 0.75 7.19 0.01

49.20% 26.92% 49.44% 44.02% 70.62% 48.94% 36.18% 37.66% 38.04% 50.07% 48.36% 51.11% 19.52% 36.50% 41.56% 38.24% 10.78% 39.06% 23.86% 33.25% 39.82% 37.06% 19.08% 40.76% 24.23% 1.72%

29

Tree Canopy Acres 2008 6.01 17.05 24.48 10.76 0.73 73.18 3.51 16.58 78.09 86.09 77.26 3.34 130.99 0.81 104.23 7.18 27.42 54.28 164.80 0.64 38.65 18.32 23.21 30.27 70.22 1.92 0.79 10.41 0.00

Percent 2008 37.38% 63.31% 58.78%

Percent Change 5.91% -15.74% -13.18%

42.87% 8.77% 50.80% 39.62% 79.98% 52.06% 39.07% 39.96% 49.63% 59.08% 66.39% 50.25% 19.23% 56.92% 55.84% 48.14% 15.69% 41.20% 30.13% 32.53% 46.74% 50.94% 20.94% 42.93% 35.09% 0.00%

6.33% 18.15% -1.36% 4.40% -9.36% -3.12% -2.90% -2.30% -11.59% -9.01% -18.03% 0.85% 0.29% -20.43% -14.28% -9.90% -4.90% -2.14% -6.27% 0.71% -6.92% -13.88% -1.85% -2.17% -10.85% 1.72%

September 2019

Neighborhood

Acres

Highland Village Highland Village Hoosier Acres Hyde Park Village Longwood-Devon Maple Heights Matlock Heights McDoel Gardens Moss Creek Village Near West Side North Kinser Point North Kinser Point Northwood Estates Old Northeast Downtown Park Ridge Park Ridge East Peppergrass Pigeon Hill Pinestone Prospect Hill Rockport Hills Saint James Woods Sherwood Oaks SoMax South Griffy Southern Pines Spicewood Sunflower Gardens Sunny Slopes Sycamore Knolls Timber Ridge Trail View Walnut Creek Waterman West Pointe Woodlands-Winding Brook

66.34 0.16 177.97 11.52 12.43 99.96 131.41 115.52 10.31 116.11 0.12 150.90 26.11 164.27 84.91 160.11 40.12 20.75 16.59 148.13 15.38 12.80 234.80 71.05 108.60 33.64 81.58 10.94 26.37 143.91 4.14 7.02 15.45 36.81 26.37 10.83

Davey Resource Group

Acres 2018 15.90 0.04 67.50 4.63 5.64 27.40 68.90 28.44 3.08 42.46 0.00 23.59 6.75 29.32 30.62 59.66 16.10 10.79 6.36 40.29 3.90 2.72 101.36 32.33 66.48 9.92 46.53 1.32 9.66 70.65 1.36 2.45 8.38 18.00 7.82 6.40

Percent 2018 23.97% 25.00% 37.93% 40.19% 45.37% 27.41% 52.43% 24.62% 29.87% 36.57% 0.00% 15.63% 25.85% 17.85% 36.06% 37.26% 40.13% 52.00% 38.34% 27.20% 25.36% 21.25% 43.17% 45.50% 61.22% 29.49% 57.04% 12.07% 36.63% 49.09% 32.85% 34.90% 54.24% 48.90% 29.65% 59.10%

30

Tree Canopy Acres 2008 11.59 0.02 81.05 5.03 8.71 35.65 67.71 33.68 2.36 46.16 0.00 17.12 3.85 41.59 39.29 88.91 12.92 11.56 6.20 43.35 2.51 2.48 95.32 41.92 70.84 5.16 54.41 0.68 13.08 81.67 1.43 7.03 7.36 19.93 6.52 6.65

Percent 2008 17.47% 12.50% 45.54% 43.66% 70.07% 35.66% 51.53% 29.16% 22.89% 39.76% 0.00% 11.35% 14.75% 25.32% 46.27% 55.53% 32.20% 55.71% 37.37% 29.26% 16.32% 19.38% 40.60% 59.00% 65.23% 15.34% 66.70% 6.22% 49.60% 56.75% 34.54% 100.14% 47.64% 54.14% 24.73% 61.40%

Percent Change 6.50% 12.50% -7.61% -3.47% -24.70% -8.25% 0.91% -4.54% 6.98% -3.19% 0.00% 4.29% 11.11% -7.47% -10.21% -18.27% 7.93% -3.71% 0.96% -2.07% 9.04% 1.88% 2.57% -13.50% -4.01% 14.15% -9.66% 5.85% -12.97% -7.66% -1.69% -65.24% 6.60% -5.24% 4.93% -2.31%

September 2019

Sub Watershed Tree Canopy Change The 2018 tree canopy results show sub watersheds Bean Blossom-Griffy Lake, Bean BlossomGriffy Creek Upper, and Clear Creek-West Fork having the highest percentages of tree canopy cover for the geographical area (Table 10). Over the last 10 years, Bean Blossom-Griffy Lake has lost less than 1% tree canopy, Bean Blossom-Griffy Creek Upper has lost 7% of tree canopy, and Clear Creek-West Fork has gained 3% of tree canopy. Sub watersheds Clear Creek-East Fork Jackson, Clear Creek-Sinking Creek, and Bean Blossom-Stout Creek have all gained more than 3% tree canopy cover in the last 10 years within their geographical areas. Sub watersheds Lake Monroe-Stephens Creek, Bean Blossom-Griffy Creek Upper, Clear Creek-Jackson Creek, and Clear Creek-Central have all lost more than 2% tree canopy cover in the last 10 years within their geographical areas.

Table 10. Results of Tree Canopy Change for Bloomington, Indiana per Sub Watershed (2008-2018) Sub Watershed

Acres

Bean Blossom-Griffy Creek Bean Blossom-Griffy Creek Upper Bean Blossom-Griffy Lake Bean Blossom-Stout Creek Clear Creek-Central Clear Creek-East Fork Jackson Clear Creek-Jackson Creek Clear Creek-Leonard Springs Clear Creek-Lower Clear Creek-Sinking Creek Clear Creek-West Fork Lake Monroe-Stephens Creek Richland Creek-Cave Creek

208.27 1,232.82 1,075.31 460.89 4,479.85 510.93 3,001.13 55.90 4.67 210.46 1,710.20 145.08 0.06

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Acres 2018 73.59 626.86 815.73 135.44 1,371.27 163.24 1,128.14 19.90 0.14 34.16 665.07 48.65 0.00

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Percent 2018 35.34% 50.85% 75.86% 29.39% 30.61% 31.95% 37.59% 35.59% 3.04% 16.23% 38.89% 33.53% 0.00%

Tree Canopy Acres Percent 2008 2008 68.13 32.71% 709.36 57.54% 817.93 76.06% 121.48 26.36% 1,488.25 33.22% 139.97 27.39% 1,207.99 40.25% 18.73 33.51% 0.08 1.69% 25.79 12.25% 619.24 36.21% 65.24 44.97% 0.00 0.00%

Percent Change 2.62% -6.69% -0.20% 3.03% -2.61% 4.56% -2.66% 2.08% 1.35% 3.97% 2.68% -11.44% 0.00%

September 2019

Zoning Type Tree Canopy Change The 2018 tree canopy results show zoning types Residential Estate, Institutional, and Quarry having the highest percentages of tree canopy cover for the geographical area (Table 11). Over the last 10 years, Residential Estate has gained 4% tree canopy, Institutional has lost 3% of tree canopy, and Quarry has gained 12% of tree canopy. Zoning types Quarry, Residential Estate, Business Park, and Planned Unit Development have all gained more than 2% tree canopy cover in the last 10 years within their geographical areas. Zoning types Residential Core, Manufactured/Mobile Home Park, and Residential Single-Family have all lost about 5% or more tree canopy cover in the last 10 years within their geographical areas.

Table 11. Results of Tree Canopy Change for Bloomington, Indiana per Zoning Type (2008-2018)

283.41 623.46 295.45 255.59 55.81 120.73 4,250.83 93.74

Acres 2018 77.64 108.11 23.31 55.09 7.96 29.97 2,009.00 33.21

Tree Canopy Percent Acres Percent 2018 2008 2008 27.39% 68.38 24.13% 17.34% 98.1 15.73% 7.89% 32.27 10.92% 21.55% 56.95 22.28% 14.26% 9.58 17.17% 24.82% 27.60 22.86% 47.26% 2,129.77 50.10% 35.43% 39.26 41.88%

Percent Change 3.27% 1.61% -3.03% -0.73% -2.90% 1.96% -2.84% -6.45%

75.50 3,373.11 111.15 882.88 78.79 684.61

11.46 1,128.66 52.10 365.97 52.94 152.39

15.18% 33.46% 46.87% 41.45% 67.19% 22.26%

13.23 1,029.84 38.28 436.83 49.46 162.50

17.52% 30.53% 34.44% 49.48% 62.77% 23.74%

-2.34% 2.93% 12.43% -8.03% 4.42% -1.48%

512.49 3,207.06

183.93 1,439.92

35.89% 44.90%

189.40 1,591.81

36.96% 49.63%

-1.07% -4.74%

Zoning Type

Acres

Business Park Commercial Arterial Commercial Downtown Commercial General Commercial Limited Industrial General Institutional Manufactured/Mobile Home Park Medical Planned Unit Development Quarry Residential Core Residential Estate Residential High-Density Multi-family Residential Multi-family Residential Single-Family

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September 2019

Tree Canopy Health DRG performed an assessment of tree canopy health for the City of Bloomington. Visible and near infra-red bands were analyzed from the 2018 NAIP imagery to evaluate the condition of Bloomington’s tree canopy. The Normalized Difference Vegetation Index (NVDI) was used as an indicator to assess tree health. In general, Bloomington’s tree canopy is Fair to Good or healthy, with 35% of the canopy in Fair health and 32% of the canopy in Good health (Table 12).

Figure 17 presents an illustrated view of the resulting 2018 assessment of tree canopy health in Bloomington.

Table 12. Health of Tree Canopy within the City of Bloomington (2018) Health Rating Shadow/Not Classified Dead/Dying Poor Fair Good Very Good Total

Davey Resource Group

Acres 89.77 294.63 1,081.48 2,006.69 1,840.40 422.79 5,735.77

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Percentage 1.57% 5.14% 18.86% 34.99% 32.09% 7.37% 100.00%

September 2019

Figure 17. Tree canopy health of the City of Bloomington, IN (2018).

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September 2019

Forest Fragmentation The overall health of the urban ecosystem depends highly on the ability of the trees, plants, wildlife, insects, and humans to interact collectively as a whole. However, a key factor in declining urban health is urban build-up and sprawl, which can lead to the removal of trees and decreased canopy across a community. Often this effect causes canopies to be fragmented and leads to the degradation of ecosystem health, which in turn leads to a decline in habitat quality and canopy connectivity. This decline results in changes and imbalance to microclimates and increases the risk and susceptibility to invasive species.

DRG mapped these forested patches and cores to help Bloomington identify areas where trees may be more susceptible to invasive species and where forest connectivity planning may improve the ecosystem (Figure 18). Table 13 presents the results of each forest type classification. Edge Canopy is the exterior perimeter of a forest degraded by "edge effects." Core Canopy is a forest not degraded by "edge effects.� Patch Canopy is small isolated fragments of forest completely degraded by "edge effects." Perforated Canopy is the edge of an interior gap in a forest degraded by "edge effects.�

Table 13. Forest Type of Tree Canopy within the City of Bloomington (2018).

Forest Type

Percentage

Patch Canopy

3,161.47

55.12%

Edge Canopy

1,621.48

28.27%

Perforated Canopy

395.44

6.89%

Small Core Canopy

169.43

2.95%

Medium Core Canopy

388.16

6.77%

5,735.97

100.00%

Total

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35

September 2019

Figure 18. Forest fragmentation within the City of Bloomington, IN (2018).

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September 2019

Tree Canopy Calculator Acreage within the City of Bloomington identified as plantable area was analyzed to determine approximate tree counts and costs needed to populate these areas with trees. The Urban Tree Resource Analysis and Cost Estimator (UTRACE) tool, developed by DRG, utilizes the land cover assessment data to estimate the number of trees required and costs to increase and maintain the newly planted tree canopy.

UTRACE can model multiple possible tree planting scenarios to attain a desired tree canopy goal.

The number of trees and their costs are estimated based on the change in tree canopy selected and the size and number of trees to be planted. User-defined inputs, such as mature size distribution and crown size diameter of the trees to be planted, allow Bloomington to model various scenarios for differing geographic boundaries, including the number and crown size diameter of the trees to be planted.

Utilizing baseline tree canopy and plantable space information presented in this report, this tool generated possible planting scenarios to attain the desired canopy goal. Bloomington has two UTRACE tools for the geographies zoning and census tracts. Using the zoning UTRACE, an example analysis considered the following: • •

• •

Assumed a mortality rate of 10%; Used tree size distributions of 10% at 15-feet crown diameter (small-growing trees), 25% at 30-feet crown diameter (medium-growing trees), and 65% at 40-feet crown diameter (large-growing trees); Maintained tree canopy at 2% across all zoning types; and, Estimated tree costs at $300 for a small-growing tree, $400 for a medium-growing tree, and $500 for a large-growing tree.

Table 14 shows a scenario for estimated costs and trees required to increase canopy by 2% for the entire city by planting trees in the assessed plantable areas. The canopy increase is equally dispersed throughout each of the 16 zoning types. To increase the 2018 tree canopy by 2%, it is estimated that 10,841 trees need to be planted at a cost of $4,770,016. UTRACE can be customized and is fully adjustable to allow the city to plan and consider other planting strategies. The UTRACE application was provided along with this report on USB.

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September 2019

Table 14. A Sample Planting Strategy to Estimate the Number of Trees and Cost to Increase Tree Canopy by 2%.

Existing Zoning

Land (Acres)

Additional Plantable Areas

Tree Canopy (Acres)

Tree Canopy (%)

Planting (Acres)

Planting (%)

Modeled Change (%)

Projected UTC Tree Canopy (Acres)

Tree Canopy (%)

Acreage Change

Estimated Number of Trees and Costs Number Estimated Costs of ($) Trees

Business Park

283

78

27%

96

34%

2.00%

83

29%

5.7

282

$

112,760.95

Commercial Arterial

623

108

17%

87

14%

2.00%

121

19%

12.5

620

$

248,060.11

Commercial Downtown

295

23

8%

24

8%

2.00%

29

10%

5.9

294

$

117,551.23

Commercial General

256

55

22%

38

15%

2.00%

60

24%

5.1

254

$

101,695.00

Commercial Limited

56

8

14%

12

21%

2.00%

9

16%

1.1

56

$

22,203.56

Industrial General

121

30

25%

26

21%

2.00%

32

27%

2.4

120

$

48,036.26

4,251

2,009

47%

947

22%

2.00%

2,094

49%

85.0

4,228

$

1,691,308.83

Manufactured/Mobile Home Park

94

33

35%

19

20%

2.00%

35

37%

1.9

93

$

37,298.97

Medical

75

11

15%

8

10%

2.00%

13

17%

1.5

75

$

30,038.43

Institutional

Planned Unit Development

3,373

1,129

33%

789

23%

2.00%

1,196

35%

67.5

3,355

$

1,342,083.52

Quarry

111

52

47%

41

36%

2.00%

54

49%

2.2

111

$

44,222.98

Residential Core

883

366

41%

166

19%

2.00%

384

43%

17.7

878

$

351,276.66

Residential Estate

79

53

67%

21

26%

2.00%

55

69%

1.6

78

$

31,350.48

Residential High-Density Multi-family

685

152

22%

122

18%

2.00%

166

24%

13.7

681

$

272,390.91

Residential Multi-family

512

184

36%

87

17%

2.00%

194

38%

10.2

510

$

203,907.81

Residential Single-Family

291

132

45%

74

25%

2.00%

138

47%

5.8

290

$

115,830.02

11,989

4,424

37%

2,555

21%

2.00%

4,663

39%

240

11,925

$

4,770,016

Total

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Se pte m b er 2019

Discussion The management of trees in an urban forest can be challenging. The City of Bloomington has to balance the recommendations of tree experts, the needs of residents, the pressures of local economics and politics, the concerns for public safety and liability issues, the physical aspects of trees, the forces of nature and severe weather events, and the desires for all of these issues to be resolved. The City of Bloomington must carefully consider each specific issue and balance these pressures with a knowledgeable understanding of their current urban tree canopy. If balance is achieved, Bloomington’s beauty will flourish and the health of its trees and residents will sustain.

Bloomington’s existing tree canopy covers 38% of the city’s total land area and provides an annual benefit valued at $1.9 million in tangible environmental benefits. During the last 10 years, Bloomington has seen nearly a 2% decrease of tree canopy cover. The plantable space assessment found 22% of the city’s total land area is available for trees. Areas designated as Very High and High priority planting areas should also be addressed first. Maximum tree canopy for Bloomington is 61%. If not planned, trees will be lost due to development, natural mortality, insects and diseases, and climate change. Further analyzing, establishing, planning, and setting out to achieve a tree canopy goal from a public and private perspective is the only way Bloomington will slow the loss of trees and tree canopy.

Many communities have set tree canopy goals, standards, or policies. The City of Bloomington should consider setting a tree canopy goal that is attainable in a set period. The goal should be citywide and objectives can be land use or neighborhood based. The results of this report must be considered to ensure goals are obtainable. Utilize the results of the urban tree canopy assessment and the provided tools to prioritize areas throughout the community to plant trees. Maintain existing healthy public trees and strive to preserve public and private tree canopy. Tree maintenance and preservation creates a sustainable urban forest. Increase public outreach efforts about the urban forest and the benefits it provides to the community. This bolsters support of trees and an understanding of the importance for tree planting, maintenance, and preservation. Today, the City of Bloomington and city partners need to make initiatives to help promote and sustain the urban tree canopy for the community and future generations to come.

Planting

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Maintenance

Preservation

39

Increased Tree Canopy

September 2019

Glossary bare soil land cover: The land cover areas mapped as bare soil typically include vacant lots, construction areas, and baseball fields. canopy: Branches and foliage which make up a tree’s crown. canopy cover: As seen from above, it is the area of land surface that is covered by tree canopy. canopy spread: A data field that estimates the width of a tree’s canopy in five-foot increments. existing UTC: The amount of UTC present within the city boundary. geographic information systems (GIS): A technology that is used to view and analyze data from a geographic perspective. The technology is a piece of an organization's overall information system framework. GIS links location to information (such as people to addresses, buildings to parcels, or streets within a network) and layers that information to give you a better understanding of how it all interrelates. greenspace: A land use planning and conservation term used to describe protected areas of undeveloped landscapes. impervious land cover: The area that does not allow rainfall to infiltrate the soil and typically includes buildings, parking lots, and roads. i-Tree Canopy: The i-Tree Canopy tool allows users to easily photo-interpret Google aerial images of their area to produce statistical estimates of tree and other cover types along with calculations of the uncertainty of their estimates. A simple, quick, and inexpensive means for cities and forest managers to accurately estimate their tree and other cover types. i-Tree Hydro: The i-tree Hydro tool is a desktop application that stimulates the effects of changes in urban tree cover and impervious surfaces on the hydrological cycle, including hourly stream flows, and water quality. land cover: Physical features on the earth mapped from satellite or aerial imagery such as bare soils, canopy, impervious, pervious, or water. nitrogen dioxide (NO2): Nitrogen dioxide is a compound typically created during the combustion processes and is a major contributor to smog formation and acid deposition. open water land cover: The land cover areas mapped as water typically include lakes, oceans, rivers, and streams. ozone (O3): A strong-smelling, pale blue, reactive toxic chemical gas with molecules of three oxygen atoms. It is a product of the photochemical process involving the Sun’s energy. Ozone exists in the upper layer of the atmosphere as well as at the Earth’s surface. Ozone at the Earth’s surface can cause numerous adverse human health effects. It is a major component of smog. particulate matter (PM10): A major class of air pollutants consisting of tiny solid or liquid particles of soot, dust, smoke, fumes, and mists. pervious land cover: The vegetative area that allows rainfall to infiltrate the soil and typically includes parks, golf courses, and residential areas. possible UTC: The amount of land that is theoretically available for the establishment of tree canopy within the city boundary. This includes all pervious and bare soil surfaces.

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September 2019

preferred plantable area: The amount of land that is realistically available for the establishment of tree canopy within the city boundary. This includes all pervious and bare soil surfaces with specified land uses. projected UTC: This the sum of existing UTC and the preferred plantable area. right-of-way (ROW): A strip of land generally owned by a public entity over which facilities, such as highways, railroads, or power lines, are built. street tree: A street tree is defined as a tree within the right-of-way. species: Fundamental category of taxonomic classification, ranking below a genus or subgenus and consisting of related organisms capable of interbreeding. sulfur dioxide (SO2): A strong-smelling, colorless gas that is formed by the combustion of fossil fuels. Sulfur oxides contribute to the problem of acid rain. tree: A tree is defined as a perennial woody plant that may grow more than 20 feet tall.

Characteristically, it has one main stem, although many species may grow as multi-stemmed forms. tree benefit: An economic, environmental, or social improvement that benefited the community and resulted mainly from the presence of a tree. The benefit received has real or intrinsic value associated with it. urban forest: All of the trees within a municipality or a community. This can include the trees along streets or rights-of-way, parks and greenspaces, and forests. urban tree canopy assessment (UTC): A study performed of land cover classes to gain an understanding of the tree canopy coverage, particularly as it relates to the amount of tree canopy that currently exists and the amount of tree canopy that could exist. Typically performed using aerial photographs, GIS data, or LIDAR.

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Appendix A Methodology and Accuracy Assessment Davey Resource Group Classification Methodology DRG utilized an object-based image analysis (OBIA) semi-automated feature extraction method to process and analyze current high-resolution color infrared (CIR) aerial imagery and remotelysensed data to identify tree canopy cover and land cover classifications. The use of imagery analysis is cost-effective and provides a highly accurate approach to assessing your community's existing tree canopy coverage. This supports responsible tree management, facilitates community forestry goal setting, and improves urban resource planning for healthier and more sustainable urban environments.

Advanced image analysis methods were used to classify, or separate, the land cover layers from the overall imagery. The semi-automated extraction process was completed using Feature Analyst, an extension of ArcGISÂŽ. Feature Analyst uses an object-oriented approach to cluster together objects with similar spectral (i.e., color) and spatial/contextual (e.g., texture, size, shape, pattern, and spatial association) characteristics. The land cover results of the extraction process was postprocessed and clipped to each project boundary prior to the manual editing process in order to create smaller, manageable, and more efficient file sizes. Secondary source data, high-resolution aerial imagery provided by each UTC city, and custom ArcGISÂŽ tools were used to aid in the final manual editing, quality checking, and quality assurance processes (QA/QC). The manual QA/QC process was implemented to identify, define, and correct any misclassifications or omission errors in the final land cover layer.

Classification Workflow 1) Prepare imagery for feature extraction (resampling, rectification, etc.), if needed.

2) Gather training set data for all desired land cover classes (canopy, impervious, grass, bare soil, shadows). Water samples are not always needed since hydrologic data are available for most areas. Training data for impervious features were not collected because the city maintained a completed impervious layer.

3) Extract canopy layer only; this decreases the amount of shadow removal from large tree canopy shadows. Fill small holes and smooth to remove rigid edges.

4) Edit and finalize canopy layer at 1:2,000 scale. A point file is created to digitize-in small individual trees that will be missed during the extraction. These points are buffered to represent the tree canopy. This process is done to speed up editing time and improve accuracy by including smaller individual trees.

5) Extract remaining land cover classes using the canopy layer as a mask; this keeps canopy shadows that occur within groups of canopy while decreasing the amount of shadow along edges.

6) Edit the impervious layer to reflect actual impervious features, such as roads, buildings, parking lots, etc. to update features.

7) Using canopy and actual impervious surfaces as a mask; input the bare soils training data and extract them from the imagery. Quickly edit the layer to remove or add any features. DRG tries to delete dry vegetation areas that are associated with lawns, grass/meadows, and agricultural fields.

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September 2019

8) Assemble any hydrological datasets, if provided. Add or remove any water features to create the hydrology class. Perform a feature extraction if no water feature datasets exist.

9) Use geoprocessing tools to clean, repair, and clip all edited land cover layers to remove any self-intersections or topology errors that sometimes occur during editing.

10) Input canopy, impervious, bare soil, and hydrology layers into DRG’s Five-Class Land Cover Model to complete the classification. This model generates the pervious (grass/low-lying vegetation) class by taking all other areas not previously classified and combining them.

Land Cover Classification Code Values Land Cover Classification

Code Value

Tree Canopy

1

Impervious

2

Pervious (Grass/Vegetation)

3

Bare Soil

4

Open Water

5

11) Thoroughly inspect final land cover dataset for any classification errors and correct as needed.

12) Perform accuracy assessment. Repeat Step 11, if needed.

Automated Feature Extraction Files The automated feature extraction (AFE) files allow other users to run the extraction process by replicating the methodology. Since Feature Analyst does not contain all geoprocessing operations that DRG utilizes, the AFE only accounts for part of the extraction process. Using Feature Analyst, DRG created the training set data, ran the extraction, and then smoothed the features to alleviate the blocky appearance. To complete the actual extraction process, DRG uses additional geoprocessing tools within ArcGISÂŽ. From the AFE file results, the following steps are taken to prepare the extracted data for manual editing.

1) DRG fills all holes in the canopy that are less than 30 square meters. This eliminates small gaps that were created during the extraction process while still allowing for natural canopy gaps.

2) DRG deletes all features that are less than 9 square meters for canopy (50 square meters for impervious surfaces). This process reduces the amount of small features that could result in incorrect classifications and also helps computer performance.

3) The Repair Geometry, Dissolve, and Multipart to Singlepart (in that order) geoprocessing tools are run to complete the extraction process.

4) The Multipart to Singlepart shapefile is given to GIS personnel for manual editing to add, remove, or reshape features.

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Accuracy Assessment Protocol Determining the accuracy of spatial data is of high importance to DRG and our clients. To achieve to best possible result, DRG manually edits and conducts thorough QA/QC checks on all urban tree canopy and land cover layers. A QA/QC process will be completed using ArcGIS® to identify, clean, and correct any misclassification or topology errors in the final land cover dataset. The initial land cover layer extractions will be edited at a 1:2,000 quality control scale in the urban areas and at a 1:2,500 scale for rural areas utilizing the most current high-resolution aerial imagery to aid in the quality control process.

To test for accuracy, random plot locations are generated throughout the city area of interest and verified to ensure that the data meet the client standards. Each point will be compared with the most current NAIP high-resolution imagery (reference image) to determine the accuracy of the final land cover layer. Points will be classified as either correct or incorrect and recorded in a classification matrix. Accuracy will be assessed using four metrics: overall accuracy, kappa, quantity disagreement, and allocation disagreement. These metrics are calculated using a custom Excel® spreadsheet.

Land Cover Accuracy The following describes DRG’s accuracy assessment techniques and outlines procedural steps used to conduct the assessment.

1. Random Point Generation—Using ArcGIS, 1,000 random assessment points are generated.

2. Point Determination—Each point is carefully assessed by the GIS analyst for likeness with the aerial photography. To record findings, two new fields, CODE and TRUTH, are added to the accuracy assessment point shapefile. CODE is a numeric value (1–5) assigned to each land cover class (Table 1) and TRUTH is the actual land cover class as identified according to the reference image. If CODE and TRUTH are the same, then the point is counted as a correct classification. Likewise, if the CODE and TRUTH are not the same, then the point is classified as incorrect. In most cases, distinguishing if a point is correct or incorrect is straightforward. Points will rarely be misclassified by an egregious classification or editing error. Often incorrect points occur where one feature stops and the other begins.

3. Classification Matrix—During the accuracy assessment, if a point is considered incorrect, it is given the correct classification in the TRUTH column. Points are first assessed on the NAIP imagery for their correctness using a “blind” assessment—meaning that the analyst does not know the actual classification (the GIS analyst is strictly going off the NAIP imagery to determine cover class). Any incorrect classifications found during the “blind” assessment are scrutinized further using sub-meter imagery provided by the client to determine if the point was incorrectly classified due to the fuzziness of the NAIP imagery or an actual misclassification. After all random points are assessed and recorded; a classification (or confusion) matrix is created. The classification matrix for this project is presented in Table 2. The table allows for assessment of user’s/producer’s accuracy, overall accuracy, omission/commission errors, kappa statistics, allocation/quantity disagreement, and confidence intervals.

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Classification Matrix Tree Canopy

Impervious Surfaces

Grass & LowLying Vegetation

Bare Soils

Open Water

ROW Total

Producer's Accuracy

Errors of Omission

369

4

22

0

1

396

93.18%

6.82%

Impervious

0

316

19

2

0

337

93.77%

6.23%

Grass/Vegetation

6

8

212

2

0

228

92.98%

7.02%

Bare Soils

0

0

0

25

0

25

100.00%

0.00%

Water

0

0

0

0

14

14

100.00%

0.00%

375

328

253

29

15

1000

User's Accuracy

98.40%

96.34%

83.79%

86.21%

93.33%

Overall Accuracy

93.60%

Errors of Commission

1.60%

3.66%

16.21%

13.79%

6.67%

Kappa Coefficent

0.9062

Classes

Reference Data

Tree Canopy

Column Total

Following are descriptions of each statistic as well as the results from some of the accuracy assessment tests.

Overall Accuracy – Percentage of correctly classified pixels; for example, the sum of the diagonals divided by the total points ((369+316+212+25+14)/1000 = 93.60%).

User’s Accuracy – Probability that a pixel classified on the map actually represents that category on the ground (correct land cover classifications divided by the column total [369/375 = 98.40%]).

Producer’s Accuracy – Probability of a reference pixel being correctly classified (correct land cover classifications divided by the row total [369/396 = 93.18%]).

Kappa Coefficient – A statistical metric used to assess the accuracy of classification data. It has been generally accepted as a better determinant of accuracy partly because it accounts for random chance agreement. A value of 0.80 or greater is regarded as “very good” agreement between the land cover classification and reference image.

Errors of Commission – A pixel reports the presence of a feature (such as trees) that, in reality, is absent (no trees are actually present). This is termed as a false positive. In the matrix below, we can determine that 1.60% of the area classified as canopy is most likely not canopy.

Errors of Omission – A pixel reports the absence of a feature (such as trees) when, in reality, they are actually there. In the matrix below, we can conclude that 6.82% of all canopy classified is actually classified as another land cover class.

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Allocation Disagreement – The amount of difference between the reference image and the classified land cover map that is due to less than optimal match in the spatial allocation (or position) of the classes.

Quantity Disagreement – The amount of difference between the reference image and the classified land cover map that is due to less than perfect match in the proportions (or area) of the classes.

Confidence Intervals – A confidence interval is a type of interval estimate of a population parameter and is used to indicate the reliability of an estimate. Confidence intervals consist of a range of values (interval) that act as good estimates of the unknown population parameter based on the observed probability of successes and failures. Since all assessments have innate error, defining a lower and upper bound estimate is essential.

Need Title Confidence Intervals Class

Acreage

Percentage

Lower Bound

Upper Bound

Tree Canopy

5,735.2

38.2%

37.8%

38.6%

5,063.8

33.8%

33.4%

34.1%

Overall Accuracy =

93.60%

3,640.8

24.3%

23.9%

24.6%

Kappa Coefficient =

0.9062

435.2

2.9%

2.8%

3.0%

Allocation Disagreement =

5%

124.8

0.8%

0.8%

0.9%

Quantity Disagreement =

1%

14,999.9

100.00%

Impervious Surfaces Grass & LowLying Vegetation Bare Soils Open Water Total

Statistical Metrics Summary

Accuracy Assessment Class

99.0%

Producer's Accuracy 93.2%

Lower Bound 91.9%

95.3%

97.4%

93.8%

92.5%

95.1%

83.8%

81.5%

86.1%

93.0%

91.3%

94.7%

86.2% 93.3%

79.8% 86.9%

92.6% 99.8%

100.0% 100.0%

100.0% 100.0%

100.0% 100.0%

User's Accuracy

Lower Bound

Upper Bound

98.4%

97.8%

96.3%

Tree Canopy Impervious Surfaces Grass & LowLying Vegetation Bare Soils Open Water

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Upper Bound 94.4%

September 2019

Ecosystem Services Methodology How Tree Canopy Benefits Are Calculated Air Quality The i-Tree Canopy v6.1 Model was used to quantify the value of ecosystem services for air quality. i-Tree Canopy was designed to give users the ability to estimate tree canopy and other land cover types within any selected geography. The model uses the estimated canopy percentage and reports air pollutant removal rates and monetary values for carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and particulate matter (PM) (Hirabayashi 2014).

Within the i-Tree Canopy application, the U.S. EPA’s BenMAP Model estimates the incidence of adverse health effects and monetary values resulting from changes in air pollutants (Hirabayashi 2014; US EPA 2012). Different pollutant removal values were used for urban and rural areas. In i-Tree Canopy, the air pollutant amount annually removed by trees and the associated monetary value can be calculated with tree cover in areas of interest using BenMAP multipliers for each county in the United States.

To calculate ecosystem services for the study area, canopy percentage metrics from UTC land cover data performed during the assessment were transferred to i-Tree Canopy. Those canopy percentages were matched by placing random points within the i-Tree Canopy application. Benefit values were reported for each of the five listed air pollutants.

Carbon Storage and Sequestration The i-Tree Canopy v6.1 Model was used to quantify the value of ecosystem services for carbon storage and sequestration. i-Tree Canopy was designed to give users the ability to estimate tree canopy and other land cover types within any selected geography. The model uses the estimated canopy percentage and reports carbon storage and sequestration rates and monetary values.

Methods on deriving storage and sequestration can be found in Nowak et al. 2013.

To calculate ecosystem services for the study area, canopy percentage metrics from UTC land cover data performed during the assessment were transferred to i-Tree Canopy. Those canopy percentages were matched by placing random points within the i-Tree Canopy application. Benefit values were reported for carbon storage and sequestration.

Stormwater The i-Tree Hydro v5.0 Model was used to quantify the value of ecosystem services for stormwater runoff. i-Tree Hydro was designed for users interested in analysis of vegetation and impervious cover effects on urban hydrology. This most recent version (v5.0) allows users to report hydrologic data on the city level rather than just a watershed scale giving users more flexibility. For more information about the model, please consult the i-Tree Hydro v5.0 manual (http://www.itreetools.org).

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To calculate ecosystem services for the study area, land cover percentages derived for the project area and all municipalities that were included in the project area were used as inputs into the model.

Precipitation data from 2005–2012 was modeled within the i-Tree Hydro to best represent the average conditions over an eight-year time period. Model simulations were run under a Base Case as well as an Alternate Case. The Alterative Case set tree canopy equal to 0% and assumed that impervious and vegetation cover would increase based on the removal of tree canopy. Impervious surface was increased 5% based on a percentage of the amount of impervious surface under tree canopy and the rest was added to the vegetation cover class. This process was completed to assess the runoff reduction volume associated with tree canopy since i-Tree Hydro does not directly report the volume of runoff reduced by tree canopy. The volume (in cubic meters) was converted to gallons to retrieve the overall volume of runoff avoided by having the current tree canopy.

Through model simulation, it was determined that tree canopy decreases the runoff volume in the project area by 90,556,345 gallons per year using precipitation data from 2005–2012. This equates to approximately 15,790 gallons per acre of tree canopy (90,556,345 gals/15,790 acres).

To place a monetary value on storm water reduction, the cost to treat a gallon of storm/waste water was taken from McPherson et al 1999. This value was $0.006 per gallon. Tree canopy was estimated to contribute roughly $543,338 to avoided runoff annually to the project area.

References Hirabayashi, S. 2014. i-Tree Canopy Air Pollutant Removal and Monetary Value Model Descriptions. http://www.itreetools.org/canopy/resources/iTree_Canopy_Methodology.pdf [Accessed 11 February 2019] i-Tree Canopy v6.1. i-Tree Software http://www.itreetools.org/canopy

Suite.

[Accessed

11

February

2019]

i-Tree Hydro v6.0. i-Tree Software http://www.itreetools.org/hydro/index.php

Suite.

[Accessed

11

February

2019]

McPherson, E.G.; Simpson, J.R.; Peper, P.J.; Xiao, Q. 1999. Tree Guidelines for San Joaquin Valley Communities. U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, Center for Urban Forest Research.

U.S. Environmental Protection Agency (US EPA). 2012. Environmental Benefits Mapping and Analysis Program (BenMAP). http://www.epa.gov/air/benmap [Accessed 11 February 2019] U.S. Forest Service. 2012. STRATUM Climate Zones. [Accessed 11 February 2019] http://www.fs.fed.us/psw/programs/uesd/uep/stratum.shtml

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Prioritized Planting – Planting Location Methodology The planting location polygons were created by taking all grass/open space and bare ground areas and combining them into one dataset. Non-feasible planting areas such as agricultural fields, recreational fields, major utility corridors, airports, etc. were removed from consideration. This layer was reviewed and approved by the City of Bloomington before the analysis proceeded. The remaining planting space was consolidated into a single feature and, then, exploded back out to multipart features creating separate, distinct polygons for each location. Using zonal statistics, the priority grid raster was used to calculate an average value for each planting location polygon. The averages were binned into five (5) classes with the higher numbers indicating higher priority for planting. These classes ranged from Very Low to Very High.

How Sites Were Prioritized To identify and prioritize planting potential, DRG assessed a number of environmental features, including proximity to hardscape, proximity to canopy, floodplain proximity, soil permeability, slope, soil erosion factor (K-factor), and urban heat island index. Each factor was assessed using data from various sources and analyzed using separate grid maps. Values between zero and four (with zero having the lowest priority) were assigned to each grid assessed. The grids were overlain and the values were averaged to determine the priority levels at an area on the map. A priority ranging from Very Low to Very High was assigned to areas on the map based on the calculated average of all grid maps.

Once the process of identifying priority was completed, the development of planting strategies was the next task. All potential planting sites were not treated equal as some sites were considered to be more suitable than others. Through prioritization, sites were ranked based on a number of factors pertaining to storm water reduction and a relative urban heat island index. While available planting sites may ultimately be planted over the next several decades, the trees that are planted in the next several years, should be planned for areas in most need, and where they will provide the most benefits and return on investment.

Priority Ranking Variables Dataset Proximity to Hardscape Urban Heat Island Index Floodplain Proximity Soil Permeability Slope Soil Erosion (K-factor) Proximity to Canopy

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Source Urban Tree Canopy Assessment Urban Tree Canopy Assessment National Hydrologic Dataset Natural Resource Conservation Service National Elevation Dataset Natural Resource Conservation Service Urban Tree Canopy Assessment

Weight 0.25 0.20 0.15 0.15 0.10 0.10 0.05

September 2019

Appendix B Indiana University Bloomington Campus Maps

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September 2019

Indiana University Bloomington Campus Land Cover Classification

Land Cover Classes Tree Canopy

Impervious Surfaces

ÂŻ 0

0.125

0.25

Bare Soil

Grass/Low-Lying Vegetation 0.5 Miles

Open Water

University Boundary

Indiana University Bloomington Campus Canopy Change 2008-2018

Canopy Year

ÂŻ 0

0.125

0.25

Consistant Canopy

Canopy Cover 2008 0.5 Miles

Canopy Cover 2018

University Boundary

Indiana University Bloomington Campus Priority Planting Levels

Priority Planting levels Very Low Low

ÂŻ 0

0.125

0.25

Moderate High 0.5 Miles

Very High

University Boundary

Indiana University Bloomington Campus Tree Health Index

Tree Health levels Shadow/Not Classified Dead/Dying Poor

¯ 0

0.125

0.25

Fair

Good 0.5 Miles

Very Good

University Boundary