PLAN-IT GEO LLC
AN ASSESSMENT OF URBAN TREE CANOPY IN HORN LAKE, SOUTHAVEN, & OLIVE BRANCH, MISSISSIPPI
Plan-It G eo LLC | 5690 Webster Street, Arvada, Col orado, 80002 | www.planitgeo.com
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Horn Lake, Southaven, & Olive Branch, Mississippi Urban Tree Canopy Assessment Completed September 2013 Prepared By
Acknowledgements Funding for this project was provided by the USDA Forest Service through the grant “Canopy in the Mid-South� to the Mississippi Forestry Commission.
Core partners included the Mississippi Forestry Commission, Urban Forestry South, The study area, City of Olive Branch Parks & Recreation, City of Horn Lake Public Works, and the City of Southaven. In addition, thanks go to Todd Matthews, Jim Hancock, Will McNeer, Sam Russell, Spencer Shields, Renee Havens, Debbie Bounds, and Tom Bledsoe for their assistance at many stages of this project. Prepared For Mississippi Forestry Commission The City of Horn Lake, Mississippi The City of Southaven, Mississippi The City of Olive Branch, Mississippi
An Urban Tree Canopy Study is just one of many elements needed to inform management and planning initiatives for urban forests. Complete and sustainable urban forestry programs involve a shared vision for the desired quality of life and level of service that tree canopies can provide the urban environment.
CONTENTS Contents ............................................................ v Executive Summary............................................. 1 Urban Forest Assessment Approach
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Urban Tree Canopy In the study area
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Recommendations and Summary
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Project Background............................................. 3 Major Findings.................................................... 5 Project Fundamentals ......................................... 6 Mapping Land Cover and Urban Tree Canopy 6 Urban Forests Ecosystem Benefits
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Terminology
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Assessment Results and Products ...................... 11 Land Cover In the Study Area
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Tree Canopy Assessment by Zoning
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Drainage Basins and Tree Canopy
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Tree Canopy in Traffic Analysis Zones
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Goal Setting
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Summary .......................................................... 23 Appendix .......................................................... 25
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HORN LAKE, SOUTHAVEN, & OLIVE BRANCH, MISSISSIPPI URBAN TREE CANOPY ASSESSMENT 2013
EXECUTIVE SUMMARY Mississippi’s urban forest is comprised of trees, gardens, green spaces and other natural areas. This urban forest provides numerous benefits by making environments cleaner, safer, and more livable, therefore contributing directly to public health and reducing the costs associated with many required services. To manage, monitor and enhance the quality and stream of benefits received from its urban forests, the Mississippi Forestry Commission has initiated this study assessing the extent of Urban Tree Canopy (UTC) across three participating communities within DeSoto County; Horn Lake, Southaven, and Olive Branch. This report presents results for current land cover and UTC distribution and offers data analysis, custom maps, suggested goals and recommendations for setting and achieving UTC goals throughout these communities.
URBAN FOREST ASSESSMENT APPROACH Natural resource managers use top-down (remote sensing) and bottom-up (field-based) approaches to measure land cover, trees and other green infrastructure, and associated ecosystem services. Terms and methods for UTC assessment are presented in this report. Additionally, steps used to identify potential planting sites and UTC goals are described and explained. See Project Fundamentals section on pages 6-8.
URBAN TREE CANOPY IN HORN LAKE, SOUTHAVEN, &OLIVE BRANCH
Total Impervious: 21%
Unsuitable UTC: 2%
UTC: This study encompasses 60,965 acres defined by the participating 37% cities of DeSoto County, Mississippi; Horn Lake, Southaven, and Olive Branch. Based on land area (after excluding water) of 59,474 Possible Planting acres, the study area cities have 21,722 acres (37%) of existing tree Areas: 41% canopy, 24,168 acres (41%) of Vegetated Possible Planting Area, or PPA Vegetation, which is defined as non-canopy vegetation where tree planting is possible. Additionally, 2,641 acres (4%) of Figure 1: Distribution of UTC Metrics in the study the study area is likely unsuitable for tree planting (i.e. area
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water bodies, roads). The land cover data was used to assess similar metrics for the areas drainage basins, traffic analysis zones, and zoning classes. See Results section on pages 11-19.
UTC GOALS To support and facilitate future tree planting and canopy preservation policies, attainable UTC goals must be developed. Results determined that 25% of all parcels have more than 42% UTC; an attainable goal within the study area. Of the 43,709 parcels across the participating cities in DeSoto County, more than 10,928 have already achieved the goal. Based upon this method, individual goals were determined across each zoning class. See Goal Setting on page 19 for details.
45% 45%
36% 35%
34% 34%
Horn Lake
Southaven
Olive Branch
Participating The study area Communities
21,722
41%
Number of acres covered by tree canopy in the project study area
Vegetated possible plantable space throughout DeSoto citys
59,474 Total land acres within The study area Area of Interest
37% Average tree canopy cover throughout DeSoto citys
RECOMMENDATIONS AND SUMMARY Understanding how and where trees are concentrated and distributed across the study area is essential for maintaining a healthy and sustainable urban forest. This study provides the most up-to-date analysis to foster this overarching goal. DeSoto County’s urban forest is vibrant and already provides substantial benefits that can be quantified, monetized, and forecasted. Enhancing green infrastructure depends on strategic canopy increases, ongoing care and maintenance, and education on the benefits of UTC. This ensures that trees appreciate over time and that their contributions toward addressing issues and improving community health are maximized. This study provides hard data for planning and decisionmaking. See Recommendations and Summary on pages 21-23.
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PROJECT BACKGROUND The citiesof Horn Lake, Southaven, and Olive Branch, located in Northwestern Mississippi, border Southern Tennessee, and cover approximately 95 square miles. As part of the Memphis Metropolitan Planning Area (MPO) for transportation planning, The study area has an obligation to relate to current planning objectives within Memphis & Shelby County (Tennessee). The EPA has found the Memphis MPO to be “non-attainment�, or an area of the country where air pollution levels persistently exceed the national ambient air quality standards. Each assessment boundary has unique management objectives and regulatory constraints. The project background introduces:
The study area, funding sources and partners The key data analyzed for the assessment and how the information is used The benefits of managing, protecting and enhancing this resource
Project Boundary
The study area Figure 2: The study area cities participating in the UTC assessment. Using GIS and remote sensing technologies, Plan-It Geo conducted UTC Assessments for the cities of Horn Lake, Olive Branch, Southaven, and Jackson Mississippi totaling 184 square miles. Funded by the US Forest Service, The Mississippi Forestry Commission Contracted Plan-It Geo to conduct this Urban Tree Canopy Assessment. This project is part of a Canopy in the Mid-South study, which comprised 16 cities throughout Mississippi, Arkansas, and Tennessee. The project included assessments in Jackson, Horn Lake, Southaven, and Olive Branch, Mississippi, and this report will address the participating study
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area cities. The information will measure existing canopy cover, strengthen local/state partnerships, build awareness of urban forest benefits, provide a baseline of information for increasing environmental services, and allow the study area and State of Mississippi to establish canopy goals and strategies.
Using geographic information systems (GIS) and remote sensing technologies, land cover classes mapped and assessed for the study area include;
Urban Tree Canopy: Tree cover, when viewed and mapped from above Vegetation: Irrigated and non-irrigated vegetation Impervious: Surfaces: roads, buildings, sidewalks, parking areas and other impervious surfaces Soil: Dry vegetation/ bare soil Water: All water bodies, including lakes, rivers, and streams The land cover data are used to examine the area and percent cover for existing tree canopy, possible planting area (in vegetated grass areas), and areas unsuitable for planting (buildings, roads, water, and sports fields). Within the three participating cities in DeSoto County; Southaven, Olive Branch, and Horn Lake, these metrics were calculated for four (4) assessment boundaries: (1) City Limits, (2) Drainage Basins, (3) Parcels, (4) and Traffic Analysis Zones (Table 1 on page 9).
What the UTC assessment provides: This project provides maps and statistical quantification of existing urban tree canopy, possible planting areas and other land cover classes across the study area, and target areas where tree planting can most positively impact the County.
Why the UTC assessment is necessary: This assessment provides the County with an up-to-date urban forest inventory; one of several components necessary for an effective urban forest management plan.
How will the participating cities use this UTC assessment: The information from this assessment will help community planners and The Mississippi Department of Environmental Quality (MDEQ) work closely together to monitor compliance with Environmental Protection Agency (EPA) standards. Additionally, this data will help determine where an increase in tree canopy can improve air quality throughout the study area and compare existing canopy results with the rest of the Memphis MPO.
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MAJOR FINDINGS THE STUDY AREA’S TREE CANOPY: The study area has 37% (21,722 acres) urban tree canopy, and 21% (12,207 acres) of total impervious surfaces. The vegetated possible planting area (PPA Vegetation) for the study area is 24,168 acres, which accounts for nearly 41% of the total land area.
CANOPY BY DRAINAGE BASINS: Camp Creek 4 drainage basin in Olive Branch has the highest percent UTC at 67% (174 acres), while the lowest percent UTC was 8% (82 acres) in Nonconnah Creek 4. PPA Vegetation in drainage basins ranged from a high of 75% (35 acres) to a low of 28% (2 acres) while percent total impervious ranged from a high of 35% (1,505) in Rocky Creek, to a low of 2% (4 acres) in Camp Creek 4.
CANOPY BY TRAFFIC ANALYSIS ZONES (TAZS): UTC in traffic analysis zones ranged from 6% (73 acres) to 68% (488 acres). PPA in traffic analysis zones ranged from 19% (45 acres) to 69% (260 acres).
ZONING / LAND USE: Agricultural Residential zoning has the highest UTC% throughout the study area at 54% (11,377 acres), while Planned Commercial zoning type has the lowest UTC at 8% (48 acres). Planned Unit Development zoning has the highest PPA Vegetation at 50% (5,379 acres), and Street Rights-of-Way zoning has the lowest PPA Vegetation at 27% (1,653 acres). While Street ROW accounts for 10% of DeSoto’s land area, only 3% of Street ROW is covered by tree canopy.
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PROJECT FUNDAMENTALS This section includes: Mapping Land Cover & Urban Tree Canopy Urban Forest Ecosystem Benefits UTC Terminology Assessment Boundaries
How Are UTC Results Used?
To set and implement canopy cover goals To prioritize areas for tree planting and preservation To analyze and visualize tree planting opportunities To work with multiple, diverse partners to achieve and maintain goals
The “top-down” UTC assessment conducted for the study area provides an accurate evaluation of canopy cover within the desired boundary. The following section describes the data and methods used for land cover classification, the terminology for defining and assessing Urban Tree Canopy (UTC) and Possible Planting Areas (PPA), and the boundaries (geographic units of scale) that were assessed.
MAPPING LAND COVER AND URBAN TREE CANOPY Aerial photography (2012 National Agricultural Imagery Program) at 1-meter pixel resolution was used as the basis for this UTC assessment. Object-based image classification results were combined with GIS data provided by the cities and the County to produce a five (5) class land cover layer. Numerous GIS layers from the county and state were used to map the following five land cover classes in the study area: (1) tree canopy, (2) other low-lying vegetation, (3) impervious surfaces, (4) bare soil/dry vegetation, and (5) water. Roads were included in the analysis and added to eliminate areas that are unsuitable for planting. A building point layer was not included in the analysis (a polygon building layer is required to include in image classification). Once finalized, the land cover data was the input to assessing boundaries to provide UTC metrics at multiple scales.
Figure 3: Accurate land cover mapping is the foundation of a UTC assessment.
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URBAN FORESTS ECOSYSTEM BENEFITS Urban forests are an integral part of the character for many residents and policy makers in the study area. The benefits of trees are referred to as “ecosystem services”, and describe the ways that urban forests impact people’s environment. The information below outlines and justifies the many reasons to promote, establish, manage, and maintain a robust, “working” urban forest in the study area.
A Better Place to Live, Work, and Play: Environmental Air Quality – trees absorb, trap, offset and hold air pollutants such as particulate matter, ozone, sulfur dioxide, carbon monoxide, and CO2. Water Quality and Stormwater Runoff Mitigation – trees infiltrate, evapotranspire, and intercept stormwater while also increasing soil permeability and ground water recharge. Erosion control – tree roots hold soil together along stream banks and steep slopes. Increased wildlife habitat – increases biodiversity in urban areas
Economic Property value –residential homes with healthy trees add property value (up to 15%). Energy conservation – trees lower energy demand through summer shade and winter wind block, additionally offsetting carbon emissions at the power plant. Stormwater facilities – trees and forests reduce the need for or size of costly gray infrastructure .
Social Public health – trees help reduce asthma rates and reduce UV-B exposure by about 50% Crime and domestic violence – urban forests help build stronger communities. Nature and trees provide settings in which relationships grow stronger and violence is reduced. Noise pollution – Trees reduce noise pollution by acting as a buffer and absorbing up to 50% of urban noise (U.S. Department of Energy study).
Resources to Manage Tree Inventory and Monetize Urban Forest Benefits: i-Tree Tools: Software suite from the USDA Forest Service that delivers urban forestry benefits and analysis assessment tools. http://www.itreetools.org/
The UF Cloud: With tools such as Canopy Tracker, Simulate Canopy, Prioritize, and Update Metrics, Plan-It Geo’s Urban Forest Cloud applications allow users to design and print maps of tree planting plans. This can increase volunteerism, community outreach, and the many environmental services and benefits urban trees provide. For more information, visit: http://www.planitgeo.com/.
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TERMINOLOGY Land cover classes were grouped into UTC Types for the assessment. UTC types categorize the landscape so that metrics can be summarized across spatial scales consistently for different applications. These terms are the calculations used in the project, and the following page illustrates the boundaries the calculations were used for. They also target land uses, neighborhoods, natural areas, or individual properties for tree planting activities and policies.
UTC Types assessed in this Report: Existing UTC comprises forests and individual trees viewed and mapped from above. Possible Planting Areas - Vegetation is the total area of grass and open space where tree canopy does not exist and it is biophysically possible to plant trees.
Total Impervious is the total area of hardscape surfaces (e.g. roads, buildings, parking lots etc.) that contribute urban heat islands and stormwater runoff (Note: due to overhanging tree canopy onto roads, sidewalks, and buildings, the total impervious acreage is reported lower than physical values). Unsuitable UTC - - the combination of soil, roads, water and other areas where it is not feasible to plant trees. Building area is typically included, however, it was not available when requested.
UTC types were mapped across GIS boundaries, described below. From the city to the parcel-level, the area and percent of these UTC types was calculated for map-making and Excel summaries.
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UTC ASSESSMENT BOUNDARIES Assessment boundaries provide geographic units linked to where we live, work and play. Metrics for UTC Types were assessed for the GIS boundaries in Table 1. These summaries provide data for resource managers and planners at different spatial scales. This resulted in summaries, maps, tools, and other products that will be used for targeted outreach campaigns. Table 1: Four (4) assessment boundaries examined in The study area Assessment Boundary
Study Area Boundaries
Drainage Basins
Traffic Analysis Zones
# of Types or Features
Description
3
City boundaries of Horn Lake, Olive Branch, and Southaven
42
Areas that gather surface water and drain it to a particular body of water.
89
A unit for inventorying demographic data and land use.
Map
Zoning Categories:
Parcels / Zoning
43,709 / 8
Agricultural Residential, Commercial, Industrial, Multi-Family Residential, Planned Commercial, Planned Unit Development, Single Family Residential, ROW
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ASSESSMENT RESULTS AND PRODUCTS The boundaries assessed in the study area’s UTC study are governed, owned, managed, and used in different ways by diverse constituents in the community. Therefore the UTC data and analysis results are presented for multiple scales and purposes to inform planners, managers and citizens alike. The following sections present canopy cover and planting potential at various scales and describe how the cities can use the data to develop better ways to manage this important resource.
Tree Canopy in The study area This study provides a snapshot of land cover in the study area. Based on 2012 aerial imagery, tree canopy covers 21,721 acres (37%) of land area (excluding water) in the study area, specifically 45% in Horn Lake, 34% in Olive Branch, and 35% in Southaven (see Figure 5). The predominate land cover types are vegetation (grass and open space) at 24,641 acres and impervious surfaces (roads, buildings, parking lots, driveways, patios, and other paved surfaces) at 12,207 acres (see Figure 6). Result sections each present four key components: Ways urban forests benefit DeSoto communities
Figure 4: Urban tree canopy across Horn Lake, Southaven, and Olive Branch
UTC results of each assessed geographic boundary Local applications using the UTC GIS data to target planting opportunities that maximize benefits Related resources the County and communities can implement
We all Impact UTC: Within The study area, the fate of urban forests relies upon City planners, council members, business owners, and residents alike. Sustainable community efforts must be met by all parties of the study area in order for the County’s urban forest to thrive. Local involvement includes: Establishing, strengthening, and enforcing tree planting ordinances across all zoning types. Community outreach to educate residents of the economic, environmental, social, and public health benefits of private property trees. Preserving or offsetting existing tree canopy in areas at risk to forest loss based on current zoning (i.e. from development pressures). Involvement from the City council members in development of urban forest management plans. Urban Tree Canopy Assessment in Horn Lake, Southaven, & Olive Branch, Mississippi
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LAND COVER IN THE STUDY AREA
34% UTC
45% UTC
35% UTC
Figure 5: 5-class land cover map in The study area
1% 2% (1,222 Ac) (904 Ac) 20% (12,207 Ac)
36% (21,721 Ac)
41% (24,641 Ac) Figure 7:
Figure 6: Distributions of 5 land cover classes across the study area
Inset Map of 5-Class Land Cover Data, Southaven, MS.
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TREE CANOPY ASSESSMENT BY ZONING Zoning and Management Planning Various policies, regulations, ordinances, and city codes influence tree canopy in the study area. To provide data that advances urban forest management, the zoning categories were assessed for tree canopy and possible planting areas. Results can be queried and symbolized using GIS to drill down and identify specific planting opportunities in zoning types. One of the many ways to target areas in need of tree canopy is provided on the following page.
Figure 8: Zoning districts in Olive Branch
In this section, results are presented for existing tree canopy and planting potential for seven (7) zoning categories and the Street Rights-of-Way, as well as applying the data to identify strategic areas for trees and residential energy conservation.
Tree Canopy by Zoning While nearly 35% of the study area’s total land area is comprised of Agricultural Residential zoning, this assessment revealed that over half of all tree canopy fell within this zoning class (11,377 acres). Planned unit development has 31% (3,348 acres) UTC, and 50% (5,379 acres) PPA Vegetation. As new development projects advance, tree planting and preservation should be a priority in this zone. Street rights-of-way accounts for nearly 10% of the study area’s total land area, yet only contributes 3% to the County’s overall tree canopy. For full results of tree canopy by zoning, see page 28 in the Appendix.
Figure 9: Distribution of UTC in the study area by zoning classes.
Applying UTC Zoning Data to Specific Types of Tree Benefits The zoning results may be used in numerous ways to determine the benefits trees provide across a specific zoning type. The example on the following page illustrates the energy conservation benefits of strategically placed trees in residential zones, and how to focus on residential areas with low tree canopy. Only residential parcels with less than 15% UTC are shown. The i-Tree Design software (U.S. Forest Service) is demonstrated to calculate the direct savings trees will provide a homeowner. This use of the data can be replicated in commercial and industrial zones to mitigate urban heat islands and reduce energy consumption while also providing stormwater management benefits.
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Trees and Energy Efficiency Benefits: Properly placed trees can save homeowners up to 20% on their energy bills. Shading reduces the amount of heat absorbed and stored by buildings. Trees slow winds, which reduces the amount of heat lost from a home, especially where conductivity is high. Trees cool the air through evapotranspiration. Trees in parking lots mitigate urban heat islands, reducing ambient air temperature.
Figure 10: Olive Branch Residential Zoning < 15% UTC
The image to the rights depicts a home in Olive Branch with little to no tree canopy. A “What If” scenario was developed using iTree Design to calculate projected benefits of strategically placed trees. Studies suggest that placing trees facing east and west walls keeps buildings cooler in the summer and allows sunlight to strike the southern side of a building in winter, lessening heating costs. The sum annual savings of planting three (3) deciduous trees on this property would total $232.50, an energy savings of $33.80 (294 kWh) annually. Public outreach and education of these benefits may be an incentive for residents to plant on private properties.
Residential < 15% UTC
Related Resources: Energy-Saving Trees is a research-based tool from the Arbor Day Foundation intended to help homeowners and utility companies save energy and money by strategically planting trees. Encouraging electric utilities in the study area to partner with the Arbor Day Foundation to conserve energy and save money while encouraging tree planting. For more information, visit: http://energysavingtrees.arborday.org/ #Home Figure 11: Screenshot of i-Tree Design application
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DRAINAGE BASINS AND TREE CANOPY Stormwater Management and Water Quality Benefits of Trees Trees infiltrate, evapotranspire, and intercept stormwater, saving communities within the study area money on costly stormwater infrastructure, while also increasing soil permeability and groundwater recharge. Urban trees also control erosion by holding soil together along stream banks and steep slopes, stabilizing soils and reducing sedimentation issues in water bodies. By targeting tree plantings in drainage basins with low canopy cover and high planting area, polluted stormwater runoff may be additionally reduced and water quality improved. As members of the Memphis Metropolitan Planning Area (MPO) for transportation and planning, Horn Lake, Southaven, and Olive Branch chose to evaluate UTC within drainage basins in order to compare similar geographies with the rest of the Memphis MPO. Assessing UTC within a natural, environmental geography such as drainage basins will assist all parties in cultivating a plan to further develop and connect green spaces throughout the region.
Tree Canopy by Drainage Basins Tree canopy in the study area drainage basins ranged from 8% to 67%, while impervious surface cover ranged from 2% to 40%. The County and cities should target watersheds and determine priority planting areas. An example â&#x20AC;&#x153;drill-downâ&#x20AC;? approach on the following page shows using drainages, zoning, and parcel data. For complete results of UTC metrics in drainage basins, see pages 37-39 in Appendix.
Figure 12: The study area percent UTC by drainage basins.
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Figure 13: Left: Percent imperviousness in Horn Lake by drainage basin. Below: A GIS-based “drill-down” approach highlighting potential forest restoration areas for stormwater management.
Surrounded by little tree canopy and considerable impervious surface, this lake is susceptible to polluted surface water flows, flooding, and impaired water quality. Traditional stormwater Best Management Practices (BMPs) such as bioswales and rain gardens should incorporate large stature trees and forested tracts as buffers to protect source waters and sensitive habitat. Figure 14 (Right): Impact of Hydrologic cycle due to development.
http://www.jacksonms.gov/government/publicworks/s wmp
Related Resources The EPA has declared ‘Tree and Canopy programs’ be included as part of Stormwater Best Management Practice using Smart Growth techniques. http://water.epa.gov/polwaste/green/upload/stormwater2streettrees.pdf The International Society of Arboriculture (ISA) has published “Guidelines for Developing and Evaluation Tree Ordinances”, which outlines various types of tree ordinances, and how to develop an effective forest management strategy. For more information, and the full document, visit: http://www.isa-arbor.com/education/resources/educ_TreeOrdinanceGuidelines.pdf The Urban Watershed Manual Part 1: Methods for Increasing Forest Cover in a Watershed, developed by the US Forest Service outlined techniques for maintaining and increasing current canopy within drainage basins. A table of goals and techniques is provided in the Appendix on page 38. To read more, visit: http://nemonet.uconn.edu/images/resources/FREMO/completepart1forestrymanual.pdf
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TREE CANOPY IN TRAFFIC ANALYSIS ZONES Transportation Planning & Air Quality A Traffic Analysis Zone (TAZ) is the unit of geography most commonly used in transportation planning models. As part of the Memphis Metropolitan Planning Area (MPO) for transportation planning, the study area Traffic Analysis Zones are assessed to monitor air quality within the study area. These cities have placed an emphasis on promoting better air quality within its cities. To support the County in transportation planning and environmental compliance, tree canopy and planting potential was assessed for TAZ’s.
Tree Canopy and Air Quality The results from this assessment showed that UTC in TAZ’s ranged from 6% to 68% throughout the study area. Total impervious surface cover ranged from 3% to 53%. Air quality benefits of urban trees can be attributed to three main effects: Lower air temperatures resulting from shade and latent heat absorption, which reduces ozone formation and smog. Trees reduce evaporative emissions from vehicles by cooling. Air is “cleaned” through the direct removal of a variety of pollutants. Indirectly, shade from trees reduces the amount of energy used for cooling, therefore limiting pollutants emitted from power plants. By measuring tree canopy within traffic analysis zones, city planners may target tree planting in traffic zones with low tree canopy, and high PPA, to help enhance the areas air quality. The image on the following page illustrates planting areas within 150 ft. of roads where trees may reduce emissions. For complete UTC Results by Traffic Analysis Zones, see page 35 in the Appendix.
Figure 15: Percent UTC by TAZ
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Figure 16 (Top Right): Percent imperviousness by TAZ’s in Southaven. Figure 17 (Above and Right): Strategic tree planting using the UTC data sets to improve air quality in grassy areas near roads and a large parking lot lacking in tree canopy.
Related Resources In a 2004 guidance document, the EPA stated that strategic tree planting can be incorporated in a State Implementation Plan (SIP) to help meet air quality standards set by the EPA (Nowak n.d.). For more information, visit: http://www.nrs.fs.fed.us/units/urban/localresources/downloads/Emerging_Measures_Summary.pdf An i-Tree Eco project was conducted in 2009 to assess the role of the County’s urban forest in removing air pollutants and sequestering carbon. Countywide, the findings revealed these annual benefits: Pollution removal = 3,500 tons/year valued at $17M/year Carbon removal = 167 K tons/year valued at $3.5M/year
Did you know? Trees in street proximity absorb 9 times more pollutants than more distant trees, converting harmful gasses back into oxygen and other useful and natural gasses. Dumbaugh, Journal of the American Planning Association, Vol. 71, No. 3, Summer 2005
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GOAL SETTING
Study Area UTC Goal: 42%
To assist decision makers in utilizing results from this assessment, suggested canopy goals were evaluated and are presented below. Goals should be implemented through landscape ordinances, tree preservation policies, comprehensive plans, and education/outreach. Localities are encouraged to develop their own UTC goals using Plan-It Geo’s Canopy Calculator. See page 36 in the Appendix. To determine appropriate and attainable tree canopy goals for the study area, percent UTC was ranked from lowest to highest at the parcel level, and analyzed. Of the 43,709 zoning districts, 32,781 (75%) have less than 42% UTC. Since 25% of all zoning areas within the study area have over 42% UTC, this was used to set the goal (75th Percentile Rule, Poracsky, J. and M. Lackner (2004). Using the Canopy Calculator, this goal would mean 3,251 acres of tree canopy from 151,800 new trees planted across the three cities. Using the same technique across zoning classes, study area goals are:
Agricultural Residential: Increase canopy to 60% (1,139 new acres of canopy) Commercial: Increase canopy to 30% (260 new acres of canopy) Industrial: Increase canopy to 28% (293 new acres of canopy) Multi-Family Residential: Increase canopy to 20% (10 new acres of canopy) Planned Commercial: Increase canopy to 18% (52 new acres of canopy) Planned Unit Development: Increase canopy to 36% (586 acres of new canopy) Single Family Residential: Increase canopy to 42% (586 acres of new canopy) Street Rights-of-Way: Increase canopy to 15% (325 new acres of canopy)
Aspects of Increasing UTC: Recent research by the USFS (Nowak 2012) suggests that a large percentage of tree canopy gains can occur through natural regeneration. In order to effectively increase UTC in the study area, cities must incorporate 1) greater tree planting, 2) preservation of existing trees, and 3) establishing areas suitable for forest regeneration. Areas suitable for regeneration include: Areas next to large patches of tree canopy Areas within a riparian buffer (i.e. conservation of lands along creeks and in the 100-year flood plain) Where soils will experience flooding Vacant or abandoned properties
Figure 18: Percent UTC increase by city and by zoning class needed to reach suggested goals.
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RECOMMENDATIONS Management of Horn Lake, Southaven, and Olive Branch’s urban forests requires planners to balance allocation of limited resources (time and money) and make choices that provide the best outcomes based on the environmental, social, and economic needs of all community members. To help support these decisions, below are recommendations that follow the organization of this report, describing ways to use the resources provided through this assessment and techniques to use over time that will lead to the enhancement of the County’s urban forest.
LAND COVER ANALYSIS Disseminate the GIS land cover data broadly to diverse partners for use in forestry/natural resources planning and other applications while the information is current. Continue to work with diverse partners to integrate the land cover data into decision-making and implementation planning. Re-assess canopy cover 8 to 10-year intervals, using LiDAR data if available, aiming for 95% overall accuracy.
ENERGY CONSERVATION Foster public and private tree planting in priority areas within each community, and determine if tree planting in new development is achieving desired outcomes. Encourage utility companies to become partners with the Arbor Day Foundation, and adopt the “Energy Saving Trees” program to save energy and money for the entire County, while encouraging tree planting. The data from this assessment highlighted 6,700 residential parcels under 10% tree canopy. Implementing a targeted residential tree planting campaign within these parcels will reduce peak energy consumption. The County should encourage residents to utilize free online tools such as i-Tree Design to determine proper placement of trees around their homes.
STORMWATER MANAGEMENT Utilize geospatial and UTC data in watershed planning to prioritize tree planting and restoration projects for protecting local and regional water quality. Encourage the use of trees and forests as a Best Management Practice (BMP) in Green Infrastructure and Low Impact Development stormwater mitigation strategies, where appropriate.
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Develop a public/private incentive program to plant and maintain large trees in and around parking lots. This will reduce the flow of contaminated runoff into surface waters, while also reducing the urban heat island effect. Conduct an i-Tree Hydro ecosystems benefits analysis using the land cover data to determine the stormwater impact of trees and forests under various future management scenarios. Target planting resources along riparian corridors and areas with high impervious surface cover to help prevent flooding and erosion and promote groundwater recharge.
AIR QUALITY ENHANCEMENT – USE THE DATA TO: Prioritize tree planting in Traffic Analysis Zones with low UTC and high impervious surface cover. Increase canopy in Street Rights-of-Way from 10% to the suggested goal of 15%, reducing evaporative emissions from vehicles by cooling the air. Focus tree planting within parking lots to mitigate urban heat islands, and reduce temperatures. Compare tree canopy within neighboring counties and the rest of the Memphis MPO. Work closely with these groups to reach air quality attainment levels set forth by the EPA. Evaluate the effectiveness of current street tree and parking lot tree ordinances where air pollutant concentrations are often highest and the benefits of trees can be maximized. Minimize the use of heavy carbon-emitting machinery in tree maintenance practices.
GOAL SETTING Reassess or draft tree related ordinances and update the city and county comprehensive plans with canopy cover goals, using the goals suggested in this report and Plan-It Geo’s Canopy Calculator tool as a starting point. Across the study area, the overall study area goal of 42% would require expanding the tree canopy by 3,251 acres. Specifically: o Expanding canopy in Agricultural Residential land to 60%. o Expanding canopy by roughly 586 acres in both single family residential and planned unit development (PUD) lots, resulting in an overall tree canopy cover of 42% and 36%, respectively. o Expanding canopy in both commercial and industrial zones by 5% each; to 30% and 28%, respectively. Utilize web-mapping applications such as Plan-It Geo’s Urban Forest Cloud to prioritize areas for tree planting, grow-out (simulate) canopy growth, and track/monitor/update urban tree canopy data sets. Doing so provides an accessible and visual platform for implementing goals and conducting outreach. Develop a partnership and implementation plan involving planning and engineering departments, developers, and citizen input to lay out a vision for canopy cover and related forestry goals in the County.
Urban Tree Canopy Assessment in Horn Lake, Southaven, & Olive Branch, Mississippi
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SUMMARY Urban forests are dynamic resources that are constantly changing through natural and human processes. Managing urban forests effectively over time requires an understanding of where trees are presently, where they can be planted equitably to maximize benefits, and how to overcome regulatory and physical restrictions that impede goals. This 2013 UTC assessment provides participating study area cities with an accurate and dependable tree inventory benchmark for Horl Lake, Southaven, and Olive Branch, and a customized analysis and report tailored to assist in the area’s near and long-term vision of urban natural resource management. City officials may use the information from this report, and compare tree canopy with the rest of the Memphis Metropolitan Planning Area (MPO) for transportation and planning, and assist the Memphis MPO in overcoming the EPA’S “non-attainment” status. Highlights from this study: Data from this study indicates that 36% of the land area is covered by tree canopy, with nearly 41% of the County’s land area available for possible planting (aka, PPA Vegetation). The study area’s 36 Drainage Basins ranged from 8% UTC (82 acres in Nonconah Creek 4) to 67% UTC (174 acres in Camp Creek 4). PPA Vegetation in drainage basins ranged from a high of 75% (35 acres) to a low of 28% (2 acres) while percent total impervious ranged from a high of 35% (1,505) in Rocky Creek, to a low of 2% (4 acres) in Camp Creek 4. Tree canopy in Traffic Analysis Zones ranged from a low of 5% to a high of 68% throughout the study area. Total impervious surfaces ranged from 3% to 53% within TAZ’s. Agricultural Residential zoning has the highest UTC% throughout the study area at 54% (11,377 acres), while Planned Commercial zoning type has the lowest UTC at 8% (48 acres) Planned Unit Development zoning has the highest PPA Vegetation at 50% (5,379 acres), and Street Rights-of-Way zoning has the lowest PPA Vegetation at 27% (1,653 acres) 25% or 10,928 out of 43,709 parcels are above 42% UTC, which is an attainable UTC goal for the study area to strive for.
The Future of Canopy in The study area A detailed an accurate baseline of land cover has been thoroughly analyzed and presented in this report. An ongoing challenge will be to balance new development with the protection and conservation of environmental values related to forest cover such as energy conservation, air quality, and climate adaptation related to carbon storage and stormwater mitigation. The social, environmental, and economic benefits of urban tree canopy are an incentive to continue in this direction.
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APPENDIX Additional details on the study areaâ&#x20AC;&#x2122;s 2013 urban tree canopy assessment are provided including supporting information on:
A1: Glossary of Terms A2: Complete Zoning, Drainage Basin, and TAZ Results A3: Urban Forest Self Evaluation; Criteria & Indicators A4: Canopy Calculator A5: USFS Table for Increasing Forest Cover within Watersheds A6: Land Cover Classification Accuracy Assessment
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A1: GLOSSARY OF TERMS Air Quality – The quantity of particulates and other pollutants present in a volume of air relative to necessary compounds such as oxygen. Trees improve air quality by absorbing and trapping air pollutants such as particulate matter, ozone, sulfur dioxide, carbon monoxide, and CO2 and by decreasing volatility by lowering air temperatures. Carbon Sequestration – The rate that carbon is removed from the atmosphere by trees. Carbon is considered a very important element because of its recognized influence on climate regulation as a greenhouse gas. Carbon Storage – Cumulative amount of carbon stored in the stems, branches and roots of trees over time. Ecosystem Services – Direct and indirect benefits provided by natural systems. The most common ecosystem services associated with urban trees and forests are air quality improvement, carbon sequestration and storage, energy conservation, and storm water mitigation. Energy conservation – The amount of energy saved due to the presence of trees. Summer cooling through shade, and by wind blocking in the winter reduces total energy used. Geographic Information Systems – Computer mapping systems used to understand how resources are distributed across the Earth’s surface. Impervious Land Cover – Hardscape surfaces that do not allow rainfall to infiltrate the soil (Buildings, roads, parking lots). i-Tree Design– As part of the i-Tree suite developed by the USDA Forest Service, this tool calculates benefits of trees on a property PPA Vegetation – (Possible Planting Area) associated with vegetation and open space. These are areas where tree planting is possible. Urban Heat Island Effect – refers to developed areas that are hotter than surrounding rural areas due to the abundance of man-made materials which absorb the sun’s energy much more than trees or other plants, and in turn warm the air around them (Center for Environmental Studies, Brown University, “Trees and the Urban Heat Island Effect”, 2010). UTC – (Urban Tree Canopy) is defined as the layer of leaves and stems of trees that cover the ground when viewed from above. Stormwater Runoff Mitigation and Water Quality – Important ecosystem services related to precipitation events, hydrologic cycles, and urban forests. Trees reduce stormwater runoff and improve water quality by intercepting rainfall, increasing soil permeability, and evapotranspiration.
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A2: COMPLETE UTC RESULTS FOR ZONING, DRAINAGE BASINS, & TAZâ&#x20AC;&#x2122;S The following maps and tables on pages 28-35 provide more comprehensive results from this UTC assessment
Zoning Results for the study area Zoning
Total Acres
% of Total Land Area
UTC Acres
UTC %
% of Total UTC
PPA (Veg) Acres
PPA (Veg) %
% of Total PPA
Total Imp. Acres
Total Imp. %
Uns. UTC Acres
Uns. UTC %
Agricultural Residential
21,437
35%
11,377
54.3%
52.4%
8,310
39.6%
34.4%
1,331
6.3%
717
1.2%
Commercial
4,661
8%
1,157
25.1%
5.3%
1,809
39.2%
7.5%
2,028
44.0%
121
0.2%
Industrial
5,696
9%
1,293
22.9%
6.0%
2,115
37.5%
8.8%
2,151
38.1%
675
1.1%
187
0%
27
14.5%
0.1%
63
34.3%
0.3%
120
65.4%
4
0.0%
589
1%
48
8.4%
0.2%
190
32.8%
0.8%
414
71.5%
29
0.0%
PUD Single Family Res.
11,059
18%
3,348
31.2%
15.4%
5,379
50.1%
22.3%
2,368
22.1%
494
0.8%
10,921
18%
3,853
36.3%
17.7%
4,650
43.8%
19.2%
2,583
24.3%
413
0.7%
Street ROW
6,145
10%
620
10.1%
2.9%
1,653
26.9%
6.8%
3,684
60.0%
188
0.3%
TOTALS
60,695
100%
21,722
37%
100.0%
24,168
41%
100.0%
14,679
25%
2,641
4%
Multi-Family Res. Planned Commercial
Goals by Zoning Classes Zoning Agricultural Residential Commercial
Total % Acres Needed Total Goal UTC Goal to Reach Goal Acres
Southaven Existing UTC %
Southaven Goals
Olive Branch Existing UTC %
Olive Branch Goals
Horn Lake Existing UTC %
Horn Lake Goals
60%
1,139
12,515
51%
56%
54%
59%
63%
68%
30%
260
1,417
23%
27%
29%
35%
20%
26%
Industrial
28%
293
1,586
37%
42%
17%
22%
41%
46%
Multi Family Res.
20%
10
37
15%
20%
0%
0%
14%
20%
Planned Comm.
18%
52
100
8%
12%
0%
0%
10%
17%
PUD
36%
586
3,934
27%
34%
30%
37%
47%
53%
Single Family Res.
42%
586
4,439
39%
44%
35%
40%
35%
42%
Street ROW
15%
325
945
9%
13%
11%
14%
11%
16%
TOTALS
42%
3251
24,973
35%
41%
34%
39%
45%
51%
Urban Tree Canopy Assessment in Horn Lake, Southaven, & Olive Branch, Mississippi
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Zoning Results for Horn Lake Zoning Agricultural Residential Commercial Industrial Multi Family Res. Planned Com. PUD Single Family Res. Street ROW TOTALS
Total Acres
Total Land Acres
% of Total Land Area
UTC Acres
UTC %
% of Total UTC
PPA (Veg.) Acres
PPA (Veg.) %
4,205
4,115
40%
2,600
63.2%
56.2%
1,340
32.6%
566 617 87 86 1,850 2,090 975 10,476
565 608 85 79 1,765 2,030 976 10,223
6% 6% 1% 1% 17% 20% 10% 100%
115 248 12 8 823 707 109 4,623
20.4% 40.8% 14.1% 10.4% 46.6% 34.8% 11.2% 45%
2.5% 5.4% 0.3% 0.2% 17.8% 15.3% 2.4% 100.0%
199 219 31 36 759 917 270 3,772
35.3% 36.1% 36.4% 45.8% 43.0% 45.2% 27.7% 37%
Total Imp. Acres
Total Imp. %
158 240 128 42 34 176 400 593 1,771
3.8% 42.4% 21.1% 49.2% 43.4% 10.0% 19.7% 60.8% 17%
Uns. UTC Uns. UTC Acres % 106
1.0%
12 21 2 8 91 66 4 310
0.1% 0.2% 0.0% 0.1% 0.9% 0.6% 0.0% 3%
Figure 19: Zoning Classes in Horn Lake.
Urban Tree Canopy Assessment in Horn Lake, Southaven, & Olive Branch, Mississippi
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Zoning Results for Southaven Zoning Agricultural Residential Commercial Industrial Multi Family Res. Planned Comm. PUD Single Family Res. Street ROW TOTALS
Total Acres
Total Land Acres
% of Total Land Area
UTC Acres
UTC %
% of Total UTC
PPA PPA Total Imp. Total Imp. Uns. UTC Uns. UTC (Veg.) (Veg.) % Acres % Acres % Acres
9,843
9,675
37%
4,904
50.7%
53%
4,107
42%
2,132 920 100 503 6,008 4,425 2,648 26,580
2,094 916 98 500 5,884 4,284 2,648 26,101
8% 4% 0% 2% 23% 16% 10% 100%
473 335 15 40 1,601 1,657 233.0 9,259.3
22.6% 36.6% 14.9% 8.0% 27.2% 38.7% 8.8% 35%
5% 4% 0% 0% 17% 18% 3% 100.0%
760 356 32 154 3,003 1,734 758 10,904
36% 39% 33% 31% 51% 40% 29% 42%
548 822 190 51 287 1,159 854 1,641 5,553
6% 39% 21% 52% 57% 20% 20% 62% 21%
285
1.1%
76 39 2 22 245 181 17 866
0.3% 0.1% 0.0% 0.1% 0.9% 0.7% 0.1% 3%
Figure 20: Zoning Classes in Southaven.
Urban Tree Canopy Assessment in Horn Lake, Southaven, & Olive Branch, Mississippi
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Zoning Results for Olive Branch Zoning Agricultural Residential Commercial Industrial PUD Single Fam. Res. Street ROW TOTALS
Total Acres
Total % Total Land Land Area Acres
UTC Acres
UTC %
% of Total UTC
PPA (Veg.) Acres
7,389
7,170
31%
3,872.2
54%
49%
2,863
40%
1,963 4,159 3,201 4,405 2,522 23,639
1,956 4,114 3,084 4,306 2,522 23,151
8% 18% 13% 19% 11% 100%
568.6 708.8 923.6 1,488.7 278.0 7,839.4
29% 17% 30% 35% 11% 34%
7% 9% 12% 19% 4% 100.0%
849 1,540 1,617 1,998 625 9,492
43% 37% 52% 46% 25% 41%
PPA (Veg.) Total Imp. Total Uns. UTC % Acres Imp. % Acres 327 33 615 158 166 1,298 4,883
5% 2% 15% 5% 4% 51% 21%
Uns. UTC %
327
1.4%
33 615 158 166 167 1,465
0.1% 2.7% 0.7% 0.7% 0.7% 6%
Figure 21: Zoning Classes in Olive Branch.
Urban Tree Canopy Assessment in Horn Lake, Southaven, & Olive Branch, Mississippi
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Drainage Basin Results
UTC Acres
UTC %
Percent of Total UTC in The study area
Drainage Basin
City
Total Acres
Land Acres (Excludes Water)
Bean Patch Creek
Southaven
1,851
1,823
726
39.8%
3%
Camp Creek 1
Olive Branch
1,928
1,864
382
20.5%
2%
Cemp Creek 2
Olive Branch
3,315
3,208
1,107
34.5%
5%
Camp Creek 3
Olive Branch
1,254
1,246
316
25.3%
1%
Camp Creek 4
Olive Branch
262
260
174
67.0%
1%
Camp Creek 5
Olive Branch
387
358
153
42.7%
1%
Camp Creek 6
Olive Branch
47
47
0
0.4%
0%
Camp Creek 7
Olive Branch
236
232
114
49.2%
1%
Coldwater River 1
Olive Branch
33
32
7
22.3%
0%
Coldwater River 2
Olive Branch
386
385
102
26.4%
0%
Cowpen Creek
Horn Lake
2,868
2,810
1,159
41.2%
5%
Horn Lake Creek 1
Southaven
875
842
424
50.4%
2%
Horn Lake Creek 2
Southaven
533
513
163
31.8%
1%
Horn Lake Creek 3
Southaven
4,212
4,173
1,438
34.5%
7%
Horn Lake Creek 4
Horn Lake
1,377
1,309
782
59.7%
4%
Horn Lake Creek 5
Southaven
790
786
265
33.7%
1%
Horn Lake Creek 6
Southaven
3,628
3,559
1,099
30.9%
5%
Horn Lake Creek 7
Southaven
1,288
1,247
575
46.1%
3%
Horn Lake Creek 8
Southaven
3,532
3,479
1,549
44.5%
7%
Horn Lake Creek 9
Southaven
100
100
50
49.8%
0%
Horn Lake Creek 10
Southaven
2,142
2,098
830
39.6%
4%
Hurricane Creek 1
Southaven
1,973
1,959
606
31.0%
3%
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Land Acres (Excludes Water)
UTC Acres
UTC %
Percent of Total UTC in The study area
Drainage Basin
City
Total Acres
Hurricane Creek 2
Southaven
16
16
5
31.0%
0%
Hurricane Creek 3
Southaven
1,685
1,670
797
47.7%
4%
Hurricane Creek 4
Southaven
237
233
148
63.6%
1%
Hurricane Creek 5
Southaven
243
241
110
45.6%
1%
Johnson Creek
Horn Lake
2,253
2,174
1,121
51.6%
5%
Lick Creek
Olive Branch
5,120
5,064
2,097
41.4%
10%
Nolehole Creek
Olive Branch
5,846
5,714
2,071
36.2%
10%
Nonconnah Creek 1
Olive Branch
7
7
0
6.2%
0%
Nonconnah Creek 2
Olive Branch
4,468
4,395
1,609
36.6%
7%
Nonconnah Creek 3
Southaven
50
50
18
36.1%
0%
Nonconnah Creek 4
Olive Branch
1,009
1,004
82
8.2%
0%
Nonconnah Creek 5
Olive Branch
1,614
1,590
549
34.6%
3%
Nonconnah Creek 6
Olive Branch
729
718
56
7.8%
0%
Rocky Creek
Southaven
4,399
4,267
1,034
24.2%
5%
60,694
59,472
21,721
36.5%
20%
TOTALS
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Figure 22: Percent PPA Vegetation by drainage basins
Figure 23: Percent total impervious by drainage basins
Urban Tree Canopy Assessment in Horn Lake, Southaven, & Olive Branch, Mississippi
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Traffic Analysis Zones (TAZ) Results
Figure 24: Percent UTC by traffic analysis zones
Figure 25: Percent PPA Vegetation by traffic analysis zones
Figure 26: Percent total impervious by traffic analysis zones
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A3: URBAN FOREST SELF EVALUATION; CRITERIA & INDICATORS The table below illustrates Criteria and Indicators (Clark 1997) to self-evaluate various components necessary for an effective and sustainable urban forest model. This is a useful tool in guiding the process of developing an urban forest management plan.
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A4: CANOPY CALCULATOR To assist in UTC goal setting, Plan-It Geoâ&#x20AC;&#x2122;s Canopy Calculator (MS Excel) tool is provided as an advanced but easy-to-use tool for the study area. The study area, as well as individual cities may quickly and easily enter various canopy or planting goals and see the impact on future tree canopy cover and tree planting scenarios.
Figure 27: Screenshots of the study areaâ&#x20AC;&#x2122;s UTC Calculator
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A5: USFS TABLE FOR INCREASING FOREST COVER WITHIN WATERSHEDS Recommendations for maintaining and increasing forest cover, taken from the US Forest Serviceâ&#x20AC;&#x2122;s Urban Watershed Forestry Manual, Part 1: Methods for Increasing Forest Cover in a Watershed.
Figure 28: Goals, objectives and techniques to increase forest cover within watersheds.
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A6: LAND COVER CLASSIFICATION ACCURACY ASSESSMENT Mississippi Land Cover Classifications This report describes the methods used and generated results in mapping land cover types across the City of Jackson and County of Desoto, Mississippi. National Agricultural Residential Inventory Program (NAIP) aerial photography from 2012 and GIS data were combined to map five land cover classes: (1) Tree Canopy, (2) Impervious Surface, (3) Green Vegetation, (4). Soil and Dry Vegetation, and (5) Water. Object-based image analysis (OBIA) was used to map trees, other vegetation, impervious surfaces and soil/dry vegetation areas. Impervious surfaces were augmented with existing buildings (provided by MS) and by buffering existing road centerlines. Water was mapped using features provided in addition to manual digitizing at 1:1,000 scale.
Figure 29: This graphic depicts various imagery used in land cover classification.
Figure 30: The breakdown of a 5-class land cover to a 7-class land cover and the conversion into UTC Metrics.
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Accuracy Assessment Classification accuracy serves two main purposes: First, accuracy assessments provide information to technicians producing the classification about where processes need to be improved and where they are effective. Secondly, measures of accuracy provide information about how to use the classification and how well land cover classes are expected to estimate actual land cover on the ground. Even with high resolution imagery, very small differences in classification methodology and quality can have a large impact on overall map area estimations. The classification accuracy error matrix illustrated in Table 1 contains confidence intervals that report the high and low values that could be expected for any comparison between the classification data and what actual, on the ground land cover was in 2012. One thousand (1,000) sample points were randomly distributed across the study area and assigned a random numeric value. Sorting from lowest random value to highest, each sample point was referenced using the NAIP imagery and assigned one of the five land cover classes (Reference ID) mentioned above. Random values ensure sample points are geographically distributed across the entire study area. An automated script is then used to assign values from the classification (Evaluation ID). Misclassified points (where reference ID does not equal evaluation ID) and corresponding land cover are inspected for necessary corrections. The procedure was repeated until an acceptable accuracy percent and classification quality are achieved.
Figure 31: Error Matrix Interpretation Statistical relationships between the reference pixels (representing the true conditions on the ground) and the intersecting classified pixels are used to understand how closely the entire classified map represents the Mississippi landscape. The sample error matrix represents the intersection of reference
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pixels manually identified by a human observer (columns) and classification category of pixels in the classified image (rows). The white boxes along the diagonals of the matrix represent agreement between the two pixel maps. Off-diagonal values represent the number pixels manually referenced to the column class that were classified as another category in the classification image. Overall accuracy is computed by dividing the total number of correct pixels by the total number of pixels reported in the matrix (397+218+283+21+17 = 936 / 997 = 95%), and the matrix can be used to calculate per class accuracy percentages. For example, 418 points were manually identified in the reference map as Tree Canopy, but only 397 of those pixels were classified as Tree Canopy in the classification map, with 8 pixels misclassified as Vegetation, and 13 as Impervious. This relationship is called the “Producer’s Accuracy” and is calculated by dividing the agreement pixel total (diagonal) by the reference pixel total (column total). Therefore, the Producer’s Accuracy for Tree Canopy is calculated as: (397 / 418 = 0.95), meaning that we can expect that 95% of all tree canopy in the MS study area were classified as Tree Canopy in the classification map. Conversely, the “User’s Accuracy” is calculated by dividing the number agreement pixel total by the total number of classified pixels in the row category. For example, 397 classification pixels intersecting reference pixels were classified as Tree Canopy, but 2 pixels were identified as Vegetation, 13 as Impervious and 2 as Soil/Dry veg. in the reference map. Therefore, the User’s Accuracy for Tree Canopy is calculated as: (397 /414 = 0.96), meaning that pixels classified as Tree Canopy the classification were actual tree canopy in the CONLR. It is important to recognize the Producer’s and User’s accuracy percent values are based on a sample of the true ground cover, represented by the reference pixels at each sample point.
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REFERENCES Clark, N. Matheny, G. Cross, V. Wake. "A Model of Urban Forest Sustainability." Journal of Arboriculture, 1997: 23: 17-30. Nowak, David J. Strategic Tree Planting as an EPA encouraged Pollutant REduction Strategy: How Urban Trees can Obtain Credit in State Implementation Plans. Syracuse, NY: Northern Reserach Station, n.d. Porasky, J and M. Lackner. 2004. Urban Forest Canopy Cover in Portland, Oregon, 1972-2002: Final Report. Available online @: http://web.pdx.edu/~poracskj/Cart%20Center/psucc200404047.pdf. Accessed 07 March 2013.
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