Microenvironment Analysis of a University Campus: GIS Design Considerations for Process Repeatability

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Microenvironment Analysis of a University

Campus: GIS Design Considerations for Process

Repeatability

Brian N. Hilton & Richard J. Burkhard

To cite this article: Brian N. Hilton & Richard J. Burkhard (2009) Microenvironment Analysis of a University Campus: GIS Design Considerations for Process Repeatability, Journal of Maps, 5:1, 219-231, DOI: 10.4113/jom.2009.1089

To link to this article: http://dx.doi.org/10.4113/jom.2009.1089

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Microenvironment Analysis of a University Campus: GIS

Design Considerations for Process Repeatability

BRIAN N. HILTON1 _{and RICHARD J. BURKHARD}2

1_{School of Information Systems and Technology, Claremont Graduate University, 130 East Ninth Street, Claremont, CA, 91711,} USA;[email protected].

2_{Department of MIS, College of Business, San Jose State University, One Washington Square, San Jose, CA, 95192, USA.}

Abstract

A GIS-based microenvironment analysis of the campuses of the Claremont Colleges was conducted to assess the environmental impact of the campus footprint and to implement new ideas and approaches for advancing environmental sustainability. The project used concepts from information systems design science to provide a framework for assembling a GIS analysis engine to produce map images and data to explore economic, environmental, energy savings, and social outcomes of planting and preserving appropriate tree species. The framework assisted investigation of increasing the tree canopy coverage at various levels, as well as stakeholder preferences for tree types and aesthetic outcomes. In addition, the study’s methods, outcomes, and limitations may be of interest to local and regional planning and sustainability administrators.

(Received 21st_{July 2009; Revised 30}th_{November 2009; Accepted 2}nd_{December 2009)}

ISSN 1744-5647

219

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1. Introduction

The objective of this project was to create an Information Systems (IS) design science fra-mework for conducting a microenvironment analysis of the Claremont Colleges Cam-puses, and to apply the resulting GIS-based analysis engine to analysis of a comprehen-sive and integrated tree planting strategy to meet a set of environmental, economic, and aesthetic goals.

Four steps were required to meet this objective:

1. Conduct a microenvironment analysis of the Claremont Colleges Campuses enu-merating the benefits of the existing ecosystem and expected benefits of increasing the tree canopy coverage to 35%;

2. Develop a Geographic Information System-based methodology to identify poten-tial tree planting locations to meet a 35% tree canopy goal based on the location of the existing tree canopy, buildings, urban heat island microclimate, and estimates of land surface temperatures;

3. Investigate potential tree planting types based on input from three sources: Tree species identified in the “Tree Guidelines for Inland Empire Communities” of the U.S. Forest Service; A campus-stakeholder tree and landscape aesthetic pre-ferences survey; Guidance from university and community stakeholders;

4. Analyze sustainable land use practices, make recommendations for implementing a tree canopy goal as part of a Claremont Colleges sustainable land use policy, and identify sources of funding and/or partnerships to conduct a tree planting initiative.

Steps 1 and 2 are those that describe the techniques and data utilized for this project and are described in detail in sections 3.1 - 3.2. Steps 3 and 4 are beyond the scope of this article. The following section presents background information regarding the GIS-based microenvironment analysis and the IS design science framework.

2. Background

The microenvironment analysis for this project addressed the environmental, economic and aesthetic benefits of increasing trees within a specified microenvironment area for the Claremont Colleges campuses, located in northeast Los Angeles County, California

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(latitude: 34.102157, longitude: -117.712326). Trees provide direct benefits in the form of reduced stormwater runoff, improved air and water quality, and increased carbon se-questration. In addition, trees provide indirect benefits, such as reducing local ambient air temperatures through evapotranspiration, which in turn affects air-conditioning use and carbon emissions from energy production. Trees provide communities with many valuable services that can be measured in terms of quantifiable benefits (McPherson et al.,2001) that may include:

• Saving Energy - trees provide building shade and mitigate the heat island effect, which in turn reduces air conditioning use, electricity costs, and air pollution from the generation of electricity (Heisler,1986;McPherson and Rowntree,1993; Simp-son,2002);

• Reducing Atmospheric Carbon Dioxide - trees absorb carbon dioxide and reduce atmospheric CO2;

• Improving Air Quality - trees absorb and filter air pollution, filter surface water and prevent erosion (McPherson et al.,2005);

• Reducing Stormwater Runoff - trees reduce the infrastructure needed to manage stormwater and reduce the need for landscape irrigation (Dwyer and Miller,1999);

• Aesthetic and Other Benefits - while more difficult to quantify, these include im-proved scenic values and imim-proved human health and well being.

Recent examples of this type of analysis, though on a larger scale, include New York City (Peper et al., 2007) and Los Angeles (McPherson et al., 2007) as well as two local area studies conducted by the University of Southern California (Longcore et al.,2001). Such approaches also provide a baseline of an area’s urban forest resources, which can be used to help manage and preserve these resources and to clarify the benefits of increa-sing the existing tree canopy coverage. The magnitude of these benefits is dependent upon the urban forest structure - e.g. tree size, proximity and orientation to buildings, and tree type (drought-resistance, emission of gases, etc.). Consequently, the selection of appropriate tree species and potential locations are a critical component of any tree-planting program.

Tree distributions in urban areas can be analyzed using a combination of spatial data in vector and raster forms, and GIS software. GIS are often applied as an analytic frame-work for combining image and other data to investigate or solve problems and perform appropriate sensitivity analyses.

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2.1 IS Design Theory Framework as a Flexible Method for

Develo-ping GIS for Microenvironment Analysis

A key objective of this research was to develop an approach to microenvironment ana-lysis that was understandable to a variety of stakeholders and would accommodate the wide ranging objectives and orientations of stakeholders, including those in social sciences such as economics and sociology, natural sciences such as meteorology and ecology, and related disciplines such as geography and urban planning. In addition, the approach should be repeatable and extensible to other GIS projects. The IS De-sign Theory Framework approach provides a flexible and understandable alternative to more cumbersome IS methods for GIS development, such as joint application de-velopment (Dennis and Wixom, 2007) or object-oriented spatial systems development (Pick,2008), and is similar to GIS Application Design and Development and GIS System Design (Marble,2009).

In IS design theories, GIS can be seen as providing high-level, conceptual views of na-tural systems, accompanied by coordinated categories of quantitative data. The most familiar of these are GIS map layers, which form the core of the GIS design artifact. In this view, the GIS exemplifies computer systems that are designed to emulate hu-man thought or imagination processes (Vaishnavi and Kuechler, 2007). Using testable views of microenvironment impact considerations is a straightforward way to integrate theory-based design approaches into GIS for this class of application (Hilton et al.,2007). In addition, a successful IS design framework can create a system tool-kit for application elsewhere (Walls et al.,2004).

2.2 IS Design Elements for GIS for Microenvironment Analysis

The IS design for this project follows an established approach developed by Walls and others (Walls et al., 1992) and has been applied extensively over the last decade (e.g.

Hevner et al.,2004;Vaishnavi and Kuechler,2007). In this approach, the meta-requirements are the high-level goals addressed by the system of the type being designed. Next, the meta-design for the design product, or artifact, is introduced as the plan to enable the system to meet meta-requirements. Kernel theories are conceptual ideas drawn from the physical, social, or management sciences that guide the design. This element al-lows integration of broad and inherently disparate objectives into the design. The final elements of the design product plan are testable design product propositions about the satisfaction of meta-requirements by the meta-design. Carried to the GIS implemen-tation phase, design theories require design product elements that can be rigorously evaluated. Table 1 defines these elements as they are implemented in the GIS for mi-croenvironment analysis.

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Design Element Implementation in GIS for Microenvironment Analysis

Meta-requirements Ability to address specific environmental management objectives, including:

1. Energy savings

2. Reduction of net CO2release

3. Reduction of particulate pollution 4. Reduction of storm water runoff

Ability to address human aesthetic and experiential factors, including: 1. Enhancement of aesthetic factors in outdoor environment

2. Reduction of summertime temperatures in outdoor recreational environments

Meta-design The meta-design for the GIS includes a GIS content and analysis management system that can:

1. Combine GIS, image and custom-generated datasets from disparate sources

2. Provide a basis for quantitative analysis of effects of alternative scenarios on micro-ecology

3. Provide means for analysis of energy savings or loss

4. Provide ways to assist non-analysts in visualizing alternative aesthetic outcomes

Kernel Theories The kernel theories for the GIS include: 1. GIS systems analysis and design 2. Sustainable Energy Architecture 3. Conservation Planning Theory 4. Ecological Aesthetics

Testable design product propositions

The general proposition is that a GIS-based system that integrates the kernel ideas will improve the product’s ability to meet the

meta-requirements described above. Specifically, the system will: 1. Enable visualization of microenvironment impacts from a variety of imaging perspectives, including those not normally associated with traditional GIS

2. Enable sensitivity analysis of microenvironment impact of planning decisions

3. Provide appropriate information to non-specialists interested in aesthetic impacts of planning decisions

Table 1. IS Design Elements and their Implementation in GIS for Microenvironment Analysis

3. Microenvironment Analysis of the Claremont Colleges

Campuses

A baseline analysis was needed to understand the existing ecosystem and the possible benefits of increasing the tree canopy coverage to 35% as suggested for suburban re-sidential zones in the Southwest United States (American Forests, 2003). CITYgreen

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(American Forests,2004), a GIS software extension for ArcGIS, was utilized in the mi-croenvironment analysis to assess the effect of trees on carbon storage, air and water quality, storm water management, and to calculate the following environmental im-pacts:

• Nitrogen Dioxide (NO2) removal (lbs/year) • Sulfur Dioxide (SO2) removal (lbs/year) • Ozone (O3) removal (lbs/year)

• Carbon Monoxide (CO) removal (lbs/year)

• Particulate Matter less than 10 microns (PM10) removal (lbs/year)

• Carbon storage (total tons)

• Carbon sequestration (tons/year)

• Runoff reduction (%)

• Peak runoff flow reduction (%)

• Total avoided runoff storage (cubic ft)

To conduct the microenvironment analysis, the geographic distribution of buildings, trees, turf and other permeable surfaces, as well as impermeable surfaces such as as-phalt must be obtained. For this project, many of these data sources, in the form of aerial imagery and architectural drawings, were obtained from existing University and other private sources and were analyzed for their suitability on the basis of geographic extent, date of image, detail, and field accuracy.

Several additional computer aided design (CAD) drawings were obtained that pro-vide additional categories of information for the Claremont Colleges Campuses. These CAD drawings were geo-referenced against the California State Plane V coordinates and converted into several GIS shapefiles, a widely used vector data storage format for storing the location, shape, and attributes of geographic features. The resultant shape-files define several characteristics of the Claremont Colleges main campuses:

1. Buildings;

2. Hardscape Areas, such as asphalt and concrete;

3. Landscape Areas, including turf, ground cover, and decomposed granite areas.

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These locations were then ground-truthed (systematically checked for accuracy in the field using pabased maps derived from the CAD drawings) by a team of eight per-sons who were assigned to review for accuracy. Any inaccuracies were noted, and the corresponding shapefiles were edited to more closely represent actual features and locations. In addition, the locations of the tree canopy were digitized in a GIS using newly acquired (existing aerial imagery was not reflective of the current landscape) sa-tellite imagery (Quick Bird imagery with 0.60-meter panchromatic and 2.4-meter multi-spectral resolution - acquisition date: 03/25/2007) as a base map reference and exported as the Tree Canopy shapefile. Several GIS data management functions were utilized to manipulate these data sets and to create the various data sets required to perform the analysis.

Four supplementary CITYgreen analyses were performed to simulate the effects of an increase/decrease of the existing tree canopy due to tree growth or tree removal. Selec-ted results of these analyses are presenSelec-ted in summary form in Table 2.

Baseline

Total Tree Canopy: 75.5 acres (25.2 ha) (23.6%)

Total Air Pollution Removal; 15,482 Lbs. (7,037 kg) removed/year Total Carbon Tons Sequestered (Annually); 25.30 Tons (22,952 kg) removed/year

5% Increase in Tree Canopy

Total Tree Canopy: 79.6 acres (26.6 ha) (24.9%)

Total Tree Canopy; 83.7 acres (27.9 ha) (26.1%)

5% Decrease in Tree Canopy

10% Decrease in Tree Canopy

Table 2. Claremont Colleges Campuses Analysis Summary

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4. GIS-based Methodology to Identify Potential Tree

Plan-ting Locations

The goal of this step was to develop a GIS-based methodology to identify potential tree planting locations (where to plant) to meet the 35% tree canopy goal based on the location of the existing buildings, hardscape, landscape, and tree canopy. In addition to increasing the tree canopy, two related goals were also investigated - reducing building energy use and urban heat island mitigation.

4.1 Tree Canopy Objectives

The first analysis performed was to determine the effect of increasing the existing tree canopy coverage to the suggested 35% coverage. The first step in this analysis was to identify existing areas that would be appropriate for tree planting given existing site conditions across the campuses and to modify the “Tree Canopy” data set to include additional tree canopy coverage. This operation necessitated a trade-off between Land-scape areas and Tree Canopy. This step identified the majority of locations suitable for tree planting. The next step in this analysis was to re-run the CITYgreen analysis with the new Tree Canopy data set. Table 3 contains the results of the analysis.

Total Tree Canopy, 90.0 acres (36.4 ha) (28.1%)

Total Air Pollution Removal, 18,460 Lbs. (8,373 kg) removed/year Total Carbon Tons Sequestered (Annually), 30.16 Tons (27,361 kg) removed/year

Table 3. Claremont Colleges Campuses Analysis Summary

The results of the analysis indicate that an ambitious tree-planting program would only increase the Tree Canopy coverage to 28.1%, not the suggested 35%. This is due prima-rily to existing site constraints - buildings, parking areas, hardscape - that are not easily modified. While this would be a 20% increase over the existing Tree Canopy coverage, it falls short of the suggested goal.

4.2 Reducing Building Energy Use

Tree shading reduces building cooling requirements by reducing direct and reflected so-lar radiation. However, estimates of the size of this effect, and how it is influenced by the

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tree plantings, are challenging due to the complexity of the variability of solar, atmos-pheric and building characteristics (Simpson, 2002). The inability to calculate energy savings for structures larger than one or two stories pose challenges in quantifying es-timates (Longcore et al., 2004). However, in this study, the majority of the buildings in the area under evaluation are under three stories. Nevertheless, the effect of trees on energy use with respect to tree positions, distances to buildings, and the ability for trees to shade windows and air conditioners provides the fundamentals of this type of analy-sis (Heisler,1986;McPherson and Rowntree,1993;Simpson and McPherson,1996;Scott and Betters,2000).

A review of these findings (Simpson, 2002) indicates that tree orientation, distances to buildings, and tree canopy size all affect the cooling and heating loads of buildings. In particular, large trees, along the east and west azimuth (slightly less so for those along the south), and located within a tree-to-building distance of 15 to 50 feet, have a maximum effect on energy use. Plantings having these qualities will reduce the summer cooling load.

The second analysis performed created common buffer zones around the buildings. These buffer areas, with a tree-to-building distance of 15 to 50 feet, helped to identify the existing tree canopy that has a high value related to energy saving. This analysis also helps to identify those areas that would be suitable for future tree planning initiatives.

4.3 Urban Heat Island Mitigation

Urban Heat Island (UHI) is the term used to describe the temperature difference bet-ween an urban area and its rural environment. Many cities and suburbs in the United States have air temperatures up to 10◦F (5.6◦C) warmer than the surrounding natural land cover (U.S. Environmental Protection Agency,2007). Heat islands occur when ve-getation is replaced with surfaces such as asphalt, concrete, and buildings, which reflect or absorb and reradiate more solar energy than grass and trees.

It has been noted that “remote sensing of urban heat islands has traditionally used the Normalized Difference Vegetation Index (NDVI) as the indicator of vegetation abun-dance to estimate the land surface temperature vegetation relationship” (?). The NDVI is a standardized index that contrasts the characteristics of two bands from multi-spectral raster imagery - the chlorophyll pigment absorptions in the red (R) band, and the high reflectivity of plant materials in the near infrared (NIR) band (ESRI Inc., 2008). The differential reflection in the R and NIR bands identifies areas of vegetation using the spectral reflectivity of solar radiation in remotely-sensed images.

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The formula for the NDVI is: (NIR - R) / (NIR + R)

The third analysis performed utilized the NDVI process to create a single-band da-taset where, in this case, blue/green colors represent areas of high vegetation while brown/yellow represent areas of low vegetation. The blue/green colors can also be said to indicate areas of cooler temperatures while brown/yellow indicate areas of hi-gher temperatures.

This analysis also helped to identify areas that can be targeted with methods to reduce heat island effects in addition to identifying areas for strategic planting of trees (Solecki et al.,2005). These approaches may also help to reduce energy use in nearby buildings.

5. Conclusions

The objective of this project was to conduct a microenvironment analysis of the Cla-remont Colleges Campuses and devise a comprehensive and integrated tree planting strategy to meet a tree canopy goal of 35%. Although the Claremont Campuses re-present a medium-size university in scale and population, several of the observations of the study may be applicable to larger campuses, as well as larger entities such as towns, cities, and regions.

The 120-year-old campus has traditionally tried to maintain its tree coverage for both its aesthetic as well as practical value, which is seen as important in the relatively arid en-vironment of eastern Los Angeles County. Increasing interest in tree coverage in many areas of the world may lead to more studies of this type in local geographic areas. As this study suggests, many factors must be considered in a GIS analysis in pursuit of a truly effective tree coverage initiative.

Results from analysis indicate that the current tree canopy coverage for the Claremont Colleges Campuses is 23.6%. When compared to similar urban settings, this value would fall near the median for suburban areas, and when compared to American Fo-rests suggested 35% coverage for this region, there is evidently much room for improve-ment. These deficiencies strengthen the argument in favor of increasing the tree canopy. Results from analysis indicate that an ambitious tree-planting program would only in-crease the Tree Canopy coverage to a maximum of 28.1%, not the suggested 35%. Exis-ting site conditions - buildings, parking areas, landscape, and hardscape - limit the abi-lity to substantially increase the tree canopy. Hence, any effort to increase the tree ca-nopy would require broad changes in current land use polices, in particular as it relates to open grassy areas and parking lots.

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Results from analysis indicate that the NDVI process to create a single-band dataset was very useful in identifying areas suitable for heat island reduction strategies, such as the use of reflective surfaces on buildings and hardscape, and the strategic planting of trees. Again, any future tree-planting program should consider including these factors when selecting locations for trees.

The IS design science framework approach offered several advantages that expand the usefulness of the GIS design developed in this project. First, it enforced systematic in-clusion of “hard” and “soft” factors into the design. The hard, traditionally engineering-associated factors included the quantitative analysis approaches based on environmen-tal science and engineering. In addition, many GIS image manipulation elements are derived from computer science. The soft factors included the systems analysis metho-dologies and important aesthetic considerations of stakeholders that can be further in-tegrated with iterative application of the model. Perhaps most importantly, the design framework allowed a unique formalization of the system used in this study, allowing a tool-kit approach that allows repeatability advocated by theorists in IS design science (Walls et al.,2004). Future use of the model is planned for other environmental settings.

Software

This project used ESRI ArcGIS 9.3, ESRI Spatial Analyst, American Forests CITYgreen, and basic graphics software.

The map accompanying this article presents factors in the GIS Microenvironment Ana-lysis of the Claremont Colleges and is designed to be interactive. The layers tab on the left margin of the map permits users to activate or hide map layers used in the analysis, including buildings, tree canopy, landscape, hardscape, and buffer zones.

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