gis-based scenario tool for assessing property tax revenue changes ...
GIS-BASED SCENARIO TOOL FOR ASSESSING PROPERTY TAX REVENUE CHANGES FROM SELECTIVE NATURALIZATION OF THE ILLINOIS RIVER FLOODPLAINS
Tarun Chandrasekhar Zorica Nedovic-Budic Raymond Kan Doug Johnston
University of Illinois at Urbana-Champaign Department of Urban and Regional Planning 111 Temple Buell Hall 611 Lorado Taft Drive Champaign, IL 61820 Tel: (217) 244-5402 Fax: (217) 244-1717 E-Mail: [email protected]
2 ABSTRACT
The naturalization of river systems is now on the agenda of many states and communities in the U.S. In the State of Illinois, researchers and non-profit organizations are actively studying the potential for naturalization as well as the physical, biological, and economic impacts of different naturalization scenarios along the Illinois River floodplain and backwater areas. This paper adds to the ongoing research by introducing a geographic information system-based scenario tool that was developed to examine and assess changes in expected property tax revenue for local communities under alternative naturalization proposals along the La Grange Reach of the Illinois River floodplain. By looking at one crucial component of a typical fiscal impact analysis using a scenariogeneration tool, we wish to convey to the public, planners, and key decision makers the impacts that may otherwise be lost or pass over in coarser, more regionalized economic models. We found that if no residential or commercial development is allowed in the restored areas, then the average loss in tax revenue from that land for each county in the La Grange Reach is 80-90% from the base year. If marginal development is allowed in the bluff area, then property tax revenues may actually increase.
3 INTRODUCTION
The history of the Illinois River watershed and floodplains is dynamic and indicative of the changes in economic development philosophy and social values over time. The 326mile long (525 km) Illinois River is a major tributary in the upper Mississippi River system and a source of much of economic productivity to the State of Illinois. However, emerging knowledge and changes in values over the last century progressed have put a different lens on the Illinois River and the wide range of natural services it once furnished locally and regionally (Sparks et al. 2000). At the turn of the 20th Century, the Illinois River Basin offered bountiful resources and fertile land that were harvested and converted, respectively, at incredible rates – in 1908, 10% of the total US harvest of freshwater fish (over 25 million pounds) came from the River; by 1930 more than 100,000 acres of floodplain (over 1/3 of current levee-protected area) had been converted to agriculture production (Sparks et al. 2000; Illinois River Strategy Team 1997). Burgeoning industries and rapid urbanization in the Chicago region led to the decision in 1900 to discharge wastewater into the Illinois River. To allow for adequate water levels for shipping, a modern system of locks and dams was set in place by the 1930s, permanently altering water levels on the River and starving backwater areas (Sparks et al. 2000).
These economic and social decisions and actions confounded to change the physical and erode the biological characteristics of the Illinois River basin. By the 1950s, pollution and modified water levels had virtually destroyed all aquatic vegetation from the River and its backwater lakes (Illinois River Strategy Team 1997). The intensification of agriculture led to soil erosion and sediment loading, which directly caused an abrupt
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decline in the quality of fish and wildlife habitat (Sparks et al. 2000). Today, the annual catch of fish is one-twentieth of the heydays of the early 1900s. Over 14 million tons of sediments are transported annually through the Illinois River watershed (Illinois River Strategy Team 1997).
Much progress has been made in the last few decades to better manage the River. For example, water quality conditions have greatly improved under the Clean Water Act and the rate of soil loss in the River Basin is now below the state average (Illinois River Strategy Team, 1997). Sparks et al. (1999), however, find that “hydrologic and habitat limitations remain as major barriers to ecosystem recovery.” (p. 3). In the past decade, once-natural, but today almost fully cultivated, floodplain ecosystems are increasingly being recognized for both their potential to be naturalized or restored. Naturalization, in essence, “is a step further in environmental policy, beyond preservation of pristine habitat and prevention of harm” towards sustainable development (Teclaff and Teclaff 1994, p. 910). Naturalization involves conversion of some of components of human-altered ecosystems to a more naturalized state and at the same time involves maintenance or enhancement of existing social and economic uses (Sparks et al 2000).
In the U.S., various partnerships among private landowners, non-governmental environmental organizations, and government agencies have been actively embarking on floodplain and uplands naturalization activities through buy-outs of agricultural levee districts and rehabilitation of degraded floodplain areas (Sparks et al. 2000). However, in order for floodplain naturalization to become a politically salient and sustainable management option in Illinois, the direct and indirect benefits that naturalization can
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bring to communities in terms of improved quality of life and enhanced local economies must be demonstrated. Building local support is important for moving decision-makers toward appropriate naturalization policies, funding, and activities (Sparks et al 1999).
Recent efforts to model the economic impacts of removing levee-protected agricultural land from production at a middle stretch of the Illinois River show that the impact on economic output value is very small relative to the overall output value for the State. Isserman (2000, unpublished research) used the Impact Analyses and Planning (IMPLAN) model to assess several alternative development scenarios consistent with naturalization. In one scenario, agricultural production was removed from a 6,300-ac (2,550 ha) levee district in the La Grange Reach of the Illinois River basin. The losses were 35 person-jobs and $2.1 million in output value, which are only 0.12% and 0.18%, respectively, of the region (which is defined as all of the counties in which the levee districts exist). At the state level, the losses are even more miniscule at 0.00039% of labour and 0.00037% of output value. In addition, by changing the substitution activity, economic returns can be realized. For example, if a refuge management is developed and recreation encouraged, then this development scenario would generate 76 new jobs and $3.7 million in output value according to IMPLAN.
However, the coarse regional or countywide analyses of naturalization may not be of sufficient detail to show the economic, fiscal, and social impacts on local communities. Naturalization, after all, may lead to a considerable alteration in land cover and existing physical landscape and may entail a wide range of implications. Lost farmland may result in some population decline and decrease in local revenues. Conversely, restoring
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agricultural land to natural conditions can potentially stimulate demand and provide opportunities for recreational services, help diversify an otherwise agriculture-dependent economy, and induce new residential and commercial development (Sparks et al. 1999, 2000). However, tourism and recreation may not be the panacea that many believe them to be. Keith et al. (1996) found that those rural Utah counties that base their economy on tourism and recreation “exhibit annual employment variability much greater than those counties which rely on alternative economic activity.” (p.96) They suggest that these counties would likely experience fiscal stress due to confounding capital needs, variable employment cycles, and the lower-wage quality of employment. The impacts of adopting a floodplain naturalization management strategy include physical, ecological, economic, and social dimensions that need to be assessed.
In this paper, we introduce a geographic information system (GIS)- based tool that has been developed with local planners and decision-makers in mind. The tool helps explore the changes in tax revenues as an aspect of the typical fiscal impact analysis and a major source of local government revenue. This GIS-based tool allows a user to interactively select and delineate sites for naturalization, designate new land use type, and estimate the changes in county-level tax revenues. We first review literature on assessing impacts associated with development, with emphasis on fiscal impact analysis, as well as the emerging role of GIS-based planning support tools. Second, we present the project background and methodology. Third, we explain the development of the GIS-based tool and show results of several scenarios used to test its functionality. In the conclusion, we present lessons learned and opportunities for refinement and enhancement of the tool
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with other aspects of development impact assessment, and we propose areas of future research.
LITERATURE REVIEW Development Impact Assessment Burchell et al. (1994) define development impact assessment as “the process of estimating and reporting the effects of residential and nonresidential construction on a host political subdivision, usually a local community, school district, special district, and/or county” (p.1). Development refers to land use changes in the context of additions and improvements to the land and real estate property. In a more recent publication, Edwards (2000) casts a wider net by describing development impact assessment as “a process to comprehensively evaluate the consequences of development on a community” (p.3). This definition precludes assumptions of what constitutes development, which in our context of large river floodplain naturalization may be regarded de-development, whereby agricultural land is removed from agricultural production and returned to a predevelopment state.
Impact assessment seeks to improve development by a-priori assessment (Barrow, 1997) of future consequences of specific proposed actions (Runyan, 1977). Indirect benefits include improving responsive and informed decision-making, promoting communication and conflict resolution among local officials and residents, allowing constructive involvement by local groups in public and private decision-making, facilitating interagency cooperation and efficiency, and promoting fairness and consistency in the development process (Edwards 2002, Runyan 1977).
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Conventional development impact assessment examines the anticipated impacts of a particular development on a community in generic, but interrelated, classes: economic, environmental, social, transportation, market, and fiscal impacts (Edwards 2000, Burchell 1994). Each class comprises more detailed and specific impacts. Different authors seem to provide slightly different ways of grouping the generic classes. For example, Canter et al. (1985) consider economic, public service, social, fiscal, and quality of life impacts under a broader socio-economic impact framework, whereas Edwards (2000) adopts the same framework but considers fiscal and transportation impacts as separate, individual classes. (Canter et al. include transportation impacts in the social impact component).
A recent approach developed by the American Farmland Trust to assess the impact of exurban development, and related to a fiscal impact analysis, is the Cost of Community Services (COCS). This approach broadly highlights the revenues and cost of various land use types in a community for a typical year; a COCS ratio shows how much a local government expends on public services for every dollar received in revenue for each conventional land use type. However, due to perceived limitations and contested assumptions, the COCS approach is not suitable as a substitute for a fiscal impact analysis (Edwards 2000, Prindle 2000).
Objectives of Fiscal Impact Analysis In general, economic impact assessments examine employment intensity, income and spending patterns, and economic multiplier effects to specify direct, indirect, and induced impacts, which are expressed in terms of jobs created, wages and salaries, and expenditures. These impacts are related to private sector actors and interactions. The
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public sector counterpart to economic impact assessment is fiscal impact analysis. (Burchell et al. 1994, GMI 1997).
Fiscal impact analysis, or cost-revenue analysis, aims to determine what impacts economic development or public policy will have on government finances, given projected changes in taxes and revenues and requirements to pay for additional public services and other expenditures (Burchell and Listokin 1978, Edwards 2000, Canter et al. 1985). Canter et al. (1985) suggest that effective fiscal impact analysis includes both short-term and long-term implications of development on the welfare of communities. Short-term effects include tax rates and public service demands; long-term implications are related to community goals.
In the typical case of communities experiencing rapid development, Roberts (1985) describes four kinds of financial-related problems that local governments may experience as a consequence of uncertainty in both development and public costs. The first problem is insufficient increases in revenue to cover increased expenses. This is symptomatic of inelastic tax revenue sources that do not respond adequately to cover the increased expenditures to meet required provision of public services. The total mixture of revenues that each type of development produces is important to monitor.
The second problem is insufficient short-term revenue to cover front-end costs of new public facilities. This refers to legal or political constraints in choosing a financing method, such as bonds and bonding capacity, to sufficiently cover the high upfront costs of new public facilities and services.
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The third problem is insufficient revenue available “in the right places or for the right purposes” (p.4), which refers to the inability by a local government to use funds generated by a certain taxing district for an unrelated, but possibly quite urgent, purpose. Categorical intergovernmental transfer payments can also restrict the discretion of local governments.
The fourth problem is (a perceived) inequitable distribution of increased public costs by new development on taxpayers. A local service district may be providing service to a different district without charging the true cost of providing that service. Additionally, new residents may have different and higher demands for the level or quality of public services, driving up taxes for old and new residents alike.
Methods of Fiscal Impact Analysis Even though fiscal impact analysis has evolved from an “ad hoc and overly simplistic projection that employed the same methodology in all cases to a more standardized and comprehensive assessment that encompasses different approaches suitable to varying applications” (Burchell et al. 1994, p.126), requirements for the completion of fiscal impact analyses as part of a formal planning process still remain inconsistent and, thus, few formal procedures exist (Siegel et al. 2000).
The general approach to assessing fiscal impacts is to examine the cost and revenue streams of government budgets. The cost side comprises operating costs and capital costs. The revenue side comprises real property revenues, other operating revenues, and capital revenues and credits. The net fiscal impact is nothing more than the difference between total revenues and totals costs (Siegel et al. 2000). Canter et al. (1985) evaluate
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the significance of fiscal impacts by converting the fiscal predictions into three measures – percent project-induced increase in revenues and expenditures, percent project-induced change in the community’s deficit or surplus, and percent change in reserve bonding capacity – and determining their significance, either by professional judgment or by a weighted technique.
Burchell et al. (1994) describe three common approaches to survey and predict operating costs and revenues: per capita, case study, and econometric. The per capita method measures municipal costs and revenues based on existing population and employment and development-induced changes in population and employment. Costs and revenues are allocated into residential and non-residential land uses. However, the per capita method does not account for excess or deficient capacity in municipal services and assumes that the cost of services for new development is the same as for existing facilities and current demand.
The case study or marginal costing method addresses the issue of lumpiness in municipal services by relying “on intensive site-specific interviews of public officials knowledgeable of local service conditions and capacities as the primary means of determining the effects of population growth on public services and costs.” (Burchell et al.1994, p.130). In this method, existing relationships between demand and supply of public services in the community are taken into explicit consideration. Edwards (2002), in fact, outlines a modified procedure that combines both the per capita and case study methods. Edwards calculates per capita operating costs and revenues associated with
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development using the per capita method and examines capital facilities using the case study approach.
The dynamic or econometric method applies “statistical techniques to time-series data…or may use cross-sectional data from multiple jurisdictions representing a variety of development patterns” (Siegel et al. 2000, p.4) to present a “moving picture” (Burchell et al. 1994, p.130) of interacting effects and impacts on a community. This is different from the previous methods, which look at a community’s profile only at one point in time.
Limitations of Fiscal Impact Analysis Fiscal impact analysis has its share of important limitations and caveats. A major consideration, as reported by Burchell et al. in 1994, is the lack of testing of reliability. Post-development numbers are not compared to projections, which undermines the empirical legitimacy of fiscal impact analysis.
Heikkila and Davis (1997) attack the underpinning of conventional fiscal methods, most notably the per capita multiplier, and argue instead for a welfare-based measure to indicate what dollar amount of compensation to existing residents would just be required for them to be as well off as they were initially before the development.
Other specific limitations with fiscal impact analysis include: Overlapping jurisdictions: Fiscal impact analysis generally is restricted in scope to a particular level of government and does not consider positive and negative spillover effects on other jurisdictions and vice-versa (Edwards 2002).
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Interaction of Land Uses: “Fiscal impact analysis does not capture the interactions among land uses when development occurs” (Edwards 2002 p.12). Residential impacts may offset the fiscal benefits of commercial developments (Siegel et al. 2000).
Cumulative Impacts: Fiscal impact analysis generally is restricted to assessing the impacts stemming from a specific development proposal, e.g., a shopping mall. An assessment of cumulative impacts from a series of interrelated developments may be necessary to tease out the fiscal impacts of anticipated development projects over time. Additionally, depending on whether a particular community is experiencing rapid growth or is fully developed (i.e., built out), important assumptions like per capita demand for services will be variable or stable with time (Siegel et al. 2000).
Planning Support Tools The GIS-based tool presented in this paper can be loosely classified as a planning support tool. In general, a planning support system refers to a set of geographic informationrelated tools used in planning activities (Geertman 2001). Planning support systems contribute to “the planning process via integrated developments usually based on multiple technologies and common interface” (Nedovic-Budic 1999, p.83).
GIS is the central technology in many decision support systems. Advancements in computer hardware and software applications have resulted in the development and proliferation of generic GIS packages. At the same time, planners, technicians, and researchers have been recognizing the practical limitations of these commercial software packages and have often customized and refined them to suit their “analytical, problem-
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solving, and decision-making” needs (Klosterman 2001, Harris and Batty 2001, NedovicBudic 1999, p.81).
Planning support systems as an evolving concept offer the potential to bring information, models, and visualizing tools to the public realm. Those tools are expected to help envision a greater number of higher quality alternative futures and facilitate more informed public debates (Harris and Batty 1993, Nedovic-Budic 1999, Geertman 2001). The support tools will also be useful in planning for floodplain naturalization. More specifically, those tools could help devise effective for governing future management and sustainability of the Illinois River basin.
PROJECT BACKGROUND AND METHODOLOGY Goals and Objectives This project was part of a larger multidisciplinary effort at the University of Illinois at Urbana-Champaign to study and model the physical, biological, and economic potential and impacts of restoring large river floodplains using the Illinois River as a study site. While a conventional fiscal impact analysis looks at both the cost and revenue streams of the government ledger to arrive at a net fiscal impact, the GIS-based tool presented concerns only with changes in property tax revenue. The tool allows the user to create new land use scenarios and compare the annual property tax revenues to baseline (existing) conditions. What-if scenarios can thus be generated by varying the input parameters, which are the land use type, the size of the chosen site, and the average equalized assessed value (EAV) of properties by type in a particular township.
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Study Area The study area covers the La Grange Reach – the middle 77-mile (124 km) section of the Illinois River, bounded upstream by the Peoria Lock and Dam and downstream by the La Grange Lock and Dam. The Reach includes territories of eight counties: Peoria, Tazewell, Fulton, Mason, Schuyler, Cass, Brown, and Morgan (Figures 1). The La Grange Reach contains extensive agricultural levees, but also natural areas and remains of backwater lakes. The area is thus suitable for exploring various naturalization scenarios.
Figure 1. La Grange Reach Study Area
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Database Requirements ESRI’s ArcGIS was used to develop the user interface and database. The user interface was developed using ESRI’s ArcObjects and Microsoft’s Visual Basic for Applications (VBA). The database contains both spatial and non-spatial information on land cover, jurisdictional boundaries, tax rates for 34 taxing districts, and average assessed value for various land use types. (Table 1 lists the datasets used and their coverage and sources). Table 1 Spatial and Non-spatial Datasets
Description
Extent
Level
Source *
Scale 1:100,000
Land cover map (23)
8 counties
County
IGIS
Land cover map (15)
Floodplain (Peoria to LaGrange Lock & Dam)
Floodplain
USGS
County lines
8 counties
County
IGIS
1:62,500
Townships lines
8 counties
Township
IGIS
1:62,500
Levee Boundaries
Illinois
Levee district
USGS
?
Tax Rates (1997 and 1998)
8 counties
Tax district
IDR***
--
Assessed value of property
8 counties
Township
IDR
--
**
?
* Illinois Geographic Information System ** United States Geological Survey ***Illinois Department of Revenue
Two land cover maps were used in developing the baseline dataset (Figure 2). The first map comprises 15 land cover classes within the floodplain of the La Grange Reach. The second, coarser map is a LANDSAT image of 23 land cover types within the boundaries of the eight counties.
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a
b
Figure 2. a) USGS Floodplain Land Cover Classification, b) LANDSAT Land Cover Classification
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Equalized assessed values (EAV) of property and total acreage for each of the five land use types in 2001 were obtained from the county assessors. Even though the county assessment lists six land use types – Residential, Commercial, Industrial, Agricultural, Railroad Property, and Mineral – the latter two types were combined into a fifth class called Barren Land. Dividing EAV by the area of a land use type in a township yields the EAV-per-acre multiplier for that land use in the township. Since residential land use is reported in number of parcels, we assumed an average parcel size of 0.5 acre.
Tool Development Figure 3 illustrates the method of combining in ArcGIS the raw datasets into a database that is then used to derive estimated tax revenues of baseline conditions (Step 1), and the steps taken by using the user interface to generate alternate land use scenarios (Step 2). In Step 1, the baseline feature class (ArcGIS layer with data) is created by first cropping a one-mile buffer around the floodplain. Second, the feature class is intersected with the two land cover feature classes. Third, the baseline feature class is overlaid with the township and tax district feature classes. Fourth, the feature class is joined with the object class (ArcGIS table of information) on the average per acre assessed property value for each land use type in each township.
The EAV for each contiguous land use type in each township is determined by first assigning the 23 different land cover classes outside the floodplain and the 15 land cover classes within the floodplain to the five land use types; and, second, by multiplying the area of each contiguous land use type by the per acre EAV multiplier. For the assignment rules we assumed that:
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the value of developed land is equivalent to the average value of residential, commercial, and industrial land use types
annual row crop cover is equivalent to 100% of agricultural land use value; and,
all other land cover types are equivalent to predetermined fractions of the value of agricultural land use.
[Figure 3 About Here]
Figure 3. Step 1: Development of Baseline GIS Layer Step 2: Scenario Building Process
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The tax rates of all taxing districts in each township are aggregated so that there is one tax rate associated for each polygon. Polygons represent any contiguous areas within a township with the same land cover type. Each polygon represents a distinct land cover type with embedded information – area in acres, total tax rate per acre, average assessed value, and total property tax revenue.
To calculate the tax revenues of each distinctive land use polygon, the following relationship is used:
R=
As LVs 100 TS 43560
where R = annual tax revenue Ts = tax rate of applicable taxing districts for the polygon As = area of the polygon (in square feet) LVs = equalized assessed land value of the polygon
Step 2 takes the baseline scenario featureclass output from Step 1, the township feature class, the tax rate featureclass, and the assessed value table as inputs to produce alternative land use scenarios via an user interface. The user delineates a proposed site to be converted and creates a new polygon feature class by using the Create Polygon function. The new polygon may overlap multiple existing land uses and cross over township boundaries (Figure 4). Alternatively, the user can use the Export Levee Polygons tool to convert an entire levee district simply by selecting the appropriate polygon in the levee district layer and exporting it to the New Scenario layer. The user can assign a new land use and/or land value to the selected naturalization site polygon. These steps can be repeated to generate many scenarios. Finally, the user can choose to output a region-wide report.
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a
b
c d
e f
g
Figure 4. a) ArcGIS file open dialog box, b) Tool file, c) Scenario building taskbar, d) Delineated site, e) New site properties dialog box; selecting new land cover, f) Editing township land value, g) County comparison report
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TOOL TESTING AND RESULTS In order to test the tool and understand the relation of revenue generated with the change in land use and land cover, the following scenarios were chosen:
1. Scenario A - Converting all agricultural land within the floodplain to forest preserve (temporarily flooded closed tree canopy)
2. Scenario B - Converting 50% of the agricultural land to forest preserve (temporarily flooded closed tree canopy land cover) and the other half to shrubland / wetland (temporarily flooded cold-deciduous shrubland)
3. Scenario C - Converting all agricultural land to shrubland / wetland (temporarily flooded cold-deciduous shrubland)
4. Scenario D – Converting all agricultural land to grassland (rural and urban)
5. Scenario E - Converting 33% of the agricultural land to shrubland / wetland (temporary flooded cold-deciduous shrubland), 33% to grasslands, 33% of the land to forest preserve (temporarily flooded closed tree canopy), and 1% land in the one mile bluff area around the floodplain to developed land (0.95% residential development and 0.05% commercial).
Figure 5 shows the change in revenue across the five scenarios. Scenario A shows an average 84 % decrease in tax revenue per county when all the land is converted to close canopy forest. This is because the land cover for this region is predominantly agricultural – a use with a higher land value than closed canopy tree. Scenario B is a mix of forest
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preserve and shrubland. Since shrubland has a lower assessed value than forest preserve, Scenario B shows a comparable decrease in the tax revenue of 83%. Similarly, Scenario C comprising of only shrubland shows an 87% decrease in tax revenue. And Scenario D comprising of only grassland shows an 83% decrease in tax revenue. Scenario E incorporates the development of residential and commercial area in 1.0% of the total land around the forest preserve, grassland and shrubland. A mix of the three uses with marginal residential\commercial development yields a slight increase (1.5%) in property tax revenue. Scenario A
Scenario B
Scenario C
Scenario D
Scenario E
10
0
-10
-20
-30
-40
-50
-60
-70
-80
-90
-100
Scenario A
Scenario B
Scenario C
Scenario D
Scenario E
Figure 5. Percentage Change in Property Tax Revenues From Baseline Conditions By Site CONCLUSIONS The issue of naturalizing agricultural or degraded landscapes is not so much about the inherent goal of naturalization, but rather the unintended impacts from it. Frequently naturalization activities are taking place in economically depressed regions of Illinois.
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The fiscal burden that naturalization can wrought on a county is clearly demonstrated with a scenario tool developed in a geographic information system. Looking at agricultural lands within a 1-mile buffer of the Illinois River in the La Grange Reach region, four of the five scenarios that were examined showed average losses in annual property tax revenue of over 80%. Only in the last scenario, where one-third of agricultural land is converted to shrubland/wetland, one-third to grasslands, one-third to forest preserve, and one percent is developed into residential and commercial uses, that annual property tax revenues in the Reach are actually above the base year values. In order to increase the flow of ecological benefits from naturalization without impinging on the flow of fiscal benefits at the county level, urban development should not be discouraged absolutely.
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REFERENCES Sparks, R.E. et al. 2000. Technical support of public decisions to restore floodplain ecosystems: a status report on the Illinois River project, USA. In: Smits, A.J.M.., Nienhuis P.H., and Leuven, R.S.E.W. (Eds.) New approaches to river management, The Netherlands, pp. 225-247. Illinois River Strategy Team. 1997. Integrated management plan for the Illinois River watershed. Springfield, Illinois: Office of the Lieutenant Governor. Sparks, R.E. et al. 1999. Strategic renewal of large floodplain rivers: integrated analysis – Project Description. Keith, J. et al. 1996. Recreation as an economic development strategy: some evidence from Utah. Journal of Leisure Research, 28(2), pp. 96-107. Burchell, R.W. et al. 1994. Development Impact Assessment Handbook. Washington, D.C.: Urban Land Institute. Edwards, M.W. 2000. Community guide to development impact analysis. Madison, WI: University of Wisconsin-Madison. Retrieved July 12, 2003 from University of Wisconsin-Madison website: http://www.lic.wisc.edu/shapingdane/facilitation/all_resources/impacts/analysis_back ground.htm Barrow, C.J. 1997. Environmental and Social Impact Assessment: An Introduction. New York: John Wiley. Runyan, D. 1977. Tools for community-managed impact assessment. Journal of the American Institute of Planners, 43: pp.125-135. Prindle, A.M. and Blaine, T.W. 1998. Costs of community services. Columbus, OH: Ohio State University Extension. Retrieved July 12, 2003 from Ohio State University website, http://ohioline.osu.edu/cd-fact/1260.html Canter, L.W., Atkinson, S.F., Leistritz, F.L. 1985. Impact of Growth: A Guide for Socioeconomic Impact Assessment and Planning. Chelsea, MI: Lewis Publishers. Hollis, L., Porter, D., and Stallworth, H. 1997. Assessing the impacts of development choices. Retrieved July 12, 2003 from The Growth Management Institute website: http://www.gmionline.org/assessing_the_impacts.htm Burchell, R.W. and Listokin, D. 1978. The Fiscal Impact Handbook: Projecting the Local Costs and Revenues Related to Growth. New Brunswick, NJ: Center for Urban Policy Research.
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Roberts, T.H. 1985. Funding public capital facilities: how community planning can help. In: Nicholas, J.C. (Ed.) The Changing Structure of Insfrastructure Finance, Florida: pp. 1-22. Siegel, M.L., Terris, J., and Benfield, K. 2000. Developments and dollars: an introduction to fiscal impact analysis in land use planning. Retrieved September 20, 2002 from http://www.nrdc.org/cities/smartgrowth/dd/ddinx.asp Geertman, S. 2001. Participatory planning and GIS: a PSS to bridge the gap. Environment and Planning B: Planning and Design, 29(1), pp. 21-35. Harris, B and Batty, M. 1993. Locational models, geographic information and planning support systems. Journal of Planning Education and Research, 12, pp. 184-198. Klosterman, R.E. 1997. Planning support systems: a new perspective on computer-aided planning. Journal of Planning Education and Research, 17(1), pp. 45-54. Nedovic-Budic, Zorica. 2000. Geographic information science implications for urban and regional planning. Journal of the Urban and Regional Information Systems Association, 12(2): pp. 81-93.
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Appendix A. County Assessor’s Land Use
Assignment of Land Cover Classes to Equivalent Land Uses % Value USGS Floodplain DNR LANDSAT Land Cover Equivalent State-wide Land (Land Use) Cover
% Value Equivalent (Land Use)
Residential
High Density
100% Ag
Commercial
Medium-High Density
Industrial
Medium Density
Barren
Low Density
Agricultural
Major Roadways
Active Railroads
Abandoned Railroads Row Crop
Small Grains
Orchards/Nurseries Urban Grassland Rural Grassland Deciduous Closed Canopy Forest Deciduous Open Canopy Forest Coniferous Undifferentiated Open Water Perennial Streams Shallow Marsh/Wet Meadow Deep Marsh Forested Wetlands Swamp Shallow Water Wetlands Barren Land
Annual row-crop forbs or grasses Developed; default to Anderson Classification Lowland or submontane cold-deciduous closed tree canopy Open water; default to Anderson Classification Permanently flooded temperate or subpolar hydromorphic rooted vegetation Roadside grass/forbs; default to Anderson Classification Saturated temperate or subpolar grassland Seasonally flooded colddeciduous closed tree canopy Seasonally flooded temperate or subpolar grassland Seasonally/temporarily flooded mudflats Tall sod temperate grassland Temperate cold-deciduous shrubland Temporarily flooded colddeciduous closed tree canopy Temporarily flooded colddeciduous shrubland Temporarily flooded sand flats
33% R + 33% C + 33% I 30% Ag
0% Ag 0% Ag
20% Ag
20% Ag 30% Ag
20% Ag
0% Ag 20% Ag 15% Ag 30% Ag
15% Ag 10% Ag
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Tax District Layer
Township Layer LANDSAT Land Cover Average EAV Table 1-mile buffer
Study Area Join
River
Floodplain Land Cover
Tarun Chandrasekhar Zorica Nedovic-Budic Raymond Kan Doug Johnston
University of Illinois at Urbana-Champaign Department of Urban and Regional Planning 111 Temple Buell Hall 611 Lorado Taft Drive Champaign, IL 61820 Tel: (217) 244-5402 Fax: (217) 244-1717 E-Mail: [email protected]
2 ABSTRACT
The naturalization of river systems is now on the agenda of many states and communities in the U.S. In the State of Illinois, researchers and non-profit organizations are actively studying the potential for naturalization as well as the physical, biological, and economic impacts of different naturalization scenarios along the Illinois River floodplain and backwater areas. This paper adds to the ongoing research by introducing a geographic information system-based scenario tool that was developed to examine and assess changes in expected property tax revenue for local communities under alternative naturalization proposals along the La Grange Reach of the Illinois River floodplain. By looking at one crucial component of a typical fiscal impact analysis using a scenariogeneration tool, we wish to convey to the public, planners, and key decision makers the impacts that may otherwise be lost or pass over in coarser, more regionalized economic models. We found that if no residential or commercial development is allowed in the restored areas, then the average loss in tax revenue from that land for each county in the La Grange Reach is 80-90% from the base year. If marginal development is allowed in the bluff area, then property tax revenues may actually increase.
3 INTRODUCTION
The history of the Illinois River watershed and floodplains is dynamic and indicative of the changes in economic development philosophy and social values over time. The 326mile long (525 km) Illinois River is a major tributary in the upper Mississippi River system and a source of much of economic productivity to the State of Illinois. However, emerging knowledge and changes in values over the last century progressed have put a different lens on the Illinois River and the wide range of natural services it once furnished locally and regionally (Sparks et al. 2000). At the turn of the 20th Century, the Illinois River Basin offered bountiful resources and fertile land that were harvested and converted, respectively, at incredible rates – in 1908, 10% of the total US harvest of freshwater fish (over 25 million pounds) came from the River; by 1930 more than 100,000 acres of floodplain (over 1/3 of current levee-protected area) had been converted to agriculture production (Sparks et al. 2000; Illinois River Strategy Team 1997). Burgeoning industries and rapid urbanization in the Chicago region led to the decision in 1900 to discharge wastewater into the Illinois River. To allow for adequate water levels for shipping, a modern system of locks and dams was set in place by the 1930s, permanently altering water levels on the River and starving backwater areas (Sparks et al. 2000).
These economic and social decisions and actions confounded to change the physical and erode the biological characteristics of the Illinois River basin. By the 1950s, pollution and modified water levels had virtually destroyed all aquatic vegetation from the River and its backwater lakes (Illinois River Strategy Team 1997). The intensification of agriculture led to soil erosion and sediment loading, which directly caused an abrupt
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decline in the quality of fish and wildlife habitat (Sparks et al. 2000). Today, the annual catch of fish is one-twentieth of the heydays of the early 1900s. Over 14 million tons of sediments are transported annually through the Illinois River watershed (Illinois River Strategy Team 1997).
Much progress has been made in the last few decades to better manage the River. For example, water quality conditions have greatly improved under the Clean Water Act and the rate of soil loss in the River Basin is now below the state average (Illinois River Strategy Team, 1997). Sparks et al. (1999), however, find that “hydrologic and habitat limitations remain as major barriers to ecosystem recovery.” (p. 3). In the past decade, once-natural, but today almost fully cultivated, floodplain ecosystems are increasingly being recognized for both their potential to be naturalized or restored. Naturalization, in essence, “is a step further in environmental policy, beyond preservation of pristine habitat and prevention of harm” towards sustainable development (Teclaff and Teclaff 1994, p. 910). Naturalization involves conversion of some of components of human-altered ecosystems to a more naturalized state and at the same time involves maintenance or enhancement of existing social and economic uses (Sparks et al 2000).
In the U.S., various partnerships among private landowners, non-governmental environmental organizations, and government agencies have been actively embarking on floodplain and uplands naturalization activities through buy-outs of agricultural levee districts and rehabilitation of degraded floodplain areas (Sparks et al. 2000). However, in order for floodplain naturalization to become a politically salient and sustainable management option in Illinois, the direct and indirect benefits that naturalization can
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bring to communities in terms of improved quality of life and enhanced local economies must be demonstrated. Building local support is important for moving decision-makers toward appropriate naturalization policies, funding, and activities (Sparks et al 1999).
Recent efforts to model the economic impacts of removing levee-protected agricultural land from production at a middle stretch of the Illinois River show that the impact on economic output value is very small relative to the overall output value for the State. Isserman (2000, unpublished research) used the Impact Analyses and Planning (IMPLAN) model to assess several alternative development scenarios consistent with naturalization. In one scenario, agricultural production was removed from a 6,300-ac (2,550 ha) levee district in the La Grange Reach of the Illinois River basin. The losses were 35 person-jobs and $2.1 million in output value, which are only 0.12% and 0.18%, respectively, of the region (which is defined as all of the counties in which the levee districts exist). At the state level, the losses are even more miniscule at 0.00039% of labour and 0.00037% of output value. In addition, by changing the substitution activity, economic returns can be realized. For example, if a refuge management is developed and recreation encouraged, then this development scenario would generate 76 new jobs and $3.7 million in output value according to IMPLAN.
However, the coarse regional or countywide analyses of naturalization may not be of sufficient detail to show the economic, fiscal, and social impacts on local communities. Naturalization, after all, may lead to a considerable alteration in land cover and existing physical landscape and may entail a wide range of implications. Lost farmland may result in some population decline and decrease in local revenues. Conversely, restoring
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agricultural land to natural conditions can potentially stimulate demand and provide opportunities for recreational services, help diversify an otherwise agriculture-dependent economy, and induce new residential and commercial development (Sparks et al. 1999, 2000). However, tourism and recreation may not be the panacea that many believe them to be. Keith et al. (1996) found that those rural Utah counties that base their economy on tourism and recreation “exhibit annual employment variability much greater than those counties which rely on alternative economic activity.” (p.96) They suggest that these counties would likely experience fiscal stress due to confounding capital needs, variable employment cycles, and the lower-wage quality of employment. The impacts of adopting a floodplain naturalization management strategy include physical, ecological, economic, and social dimensions that need to be assessed.
In this paper, we introduce a geographic information system (GIS)- based tool that has been developed with local planners and decision-makers in mind. The tool helps explore the changes in tax revenues as an aspect of the typical fiscal impact analysis and a major source of local government revenue. This GIS-based tool allows a user to interactively select and delineate sites for naturalization, designate new land use type, and estimate the changes in county-level tax revenues. We first review literature on assessing impacts associated with development, with emphasis on fiscal impact analysis, as well as the emerging role of GIS-based planning support tools. Second, we present the project background and methodology. Third, we explain the development of the GIS-based tool and show results of several scenarios used to test its functionality. In the conclusion, we present lessons learned and opportunities for refinement and enhancement of the tool
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with other aspects of development impact assessment, and we propose areas of future research.
LITERATURE REVIEW Development Impact Assessment Burchell et al. (1994) define development impact assessment as “the process of estimating and reporting the effects of residential and nonresidential construction on a host political subdivision, usually a local community, school district, special district, and/or county” (p.1). Development refers to land use changes in the context of additions and improvements to the land and real estate property. In a more recent publication, Edwards (2000) casts a wider net by describing development impact assessment as “a process to comprehensively evaluate the consequences of development on a community” (p.3). This definition precludes assumptions of what constitutes development, which in our context of large river floodplain naturalization may be regarded de-development, whereby agricultural land is removed from agricultural production and returned to a predevelopment state.
Impact assessment seeks to improve development by a-priori assessment (Barrow, 1997) of future consequences of specific proposed actions (Runyan, 1977). Indirect benefits include improving responsive and informed decision-making, promoting communication and conflict resolution among local officials and residents, allowing constructive involvement by local groups in public and private decision-making, facilitating interagency cooperation and efficiency, and promoting fairness and consistency in the development process (Edwards 2002, Runyan 1977).
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Conventional development impact assessment examines the anticipated impacts of a particular development on a community in generic, but interrelated, classes: economic, environmental, social, transportation, market, and fiscal impacts (Edwards 2000, Burchell 1994). Each class comprises more detailed and specific impacts. Different authors seem to provide slightly different ways of grouping the generic classes. For example, Canter et al. (1985) consider economic, public service, social, fiscal, and quality of life impacts under a broader socio-economic impact framework, whereas Edwards (2000) adopts the same framework but considers fiscal and transportation impacts as separate, individual classes. (Canter et al. include transportation impacts in the social impact component).
A recent approach developed by the American Farmland Trust to assess the impact of exurban development, and related to a fiscal impact analysis, is the Cost of Community Services (COCS). This approach broadly highlights the revenues and cost of various land use types in a community for a typical year; a COCS ratio shows how much a local government expends on public services for every dollar received in revenue for each conventional land use type. However, due to perceived limitations and contested assumptions, the COCS approach is not suitable as a substitute for a fiscal impact analysis (Edwards 2000, Prindle 2000).
Objectives of Fiscal Impact Analysis In general, economic impact assessments examine employment intensity, income and spending patterns, and economic multiplier effects to specify direct, indirect, and induced impacts, which are expressed in terms of jobs created, wages and salaries, and expenditures. These impacts are related to private sector actors and interactions. The
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public sector counterpart to economic impact assessment is fiscal impact analysis. (Burchell et al. 1994, GMI 1997).
Fiscal impact analysis, or cost-revenue analysis, aims to determine what impacts economic development or public policy will have on government finances, given projected changes in taxes and revenues and requirements to pay for additional public services and other expenditures (Burchell and Listokin 1978, Edwards 2000, Canter et al. 1985). Canter et al. (1985) suggest that effective fiscal impact analysis includes both short-term and long-term implications of development on the welfare of communities. Short-term effects include tax rates and public service demands; long-term implications are related to community goals.
In the typical case of communities experiencing rapid development, Roberts (1985) describes four kinds of financial-related problems that local governments may experience as a consequence of uncertainty in both development and public costs. The first problem is insufficient increases in revenue to cover increased expenses. This is symptomatic of inelastic tax revenue sources that do not respond adequately to cover the increased expenditures to meet required provision of public services. The total mixture of revenues that each type of development produces is important to monitor.
The second problem is insufficient short-term revenue to cover front-end costs of new public facilities. This refers to legal or political constraints in choosing a financing method, such as bonds and bonding capacity, to sufficiently cover the high upfront costs of new public facilities and services.
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The third problem is insufficient revenue available “in the right places or for the right purposes” (p.4), which refers to the inability by a local government to use funds generated by a certain taxing district for an unrelated, but possibly quite urgent, purpose. Categorical intergovernmental transfer payments can also restrict the discretion of local governments.
The fourth problem is (a perceived) inequitable distribution of increased public costs by new development on taxpayers. A local service district may be providing service to a different district without charging the true cost of providing that service. Additionally, new residents may have different and higher demands for the level or quality of public services, driving up taxes for old and new residents alike.
Methods of Fiscal Impact Analysis Even though fiscal impact analysis has evolved from an “ad hoc and overly simplistic projection that employed the same methodology in all cases to a more standardized and comprehensive assessment that encompasses different approaches suitable to varying applications” (Burchell et al. 1994, p.126), requirements for the completion of fiscal impact analyses as part of a formal planning process still remain inconsistent and, thus, few formal procedures exist (Siegel et al. 2000).
The general approach to assessing fiscal impacts is to examine the cost and revenue streams of government budgets. The cost side comprises operating costs and capital costs. The revenue side comprises real property revenues, other operating revenues, and capital revenues and credits. The net fiscal impact is nothing more than the difference between total revenues and totals costs (Siegel et al. 2000). Canter et al. (1985) evaluate
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the significance of fiscal impacts by converting the fiscal predictions into three measures – percent project-induced increase in revenues and expenditures, percent project-induced change in the community’s deficit or surplus, and percent change in reserve bonding capacity – and determining their significance, either by professional judgment or by a weighted technique.
Burchell et al. (1994) describe three common approaches to survey and predict operating costs and revenues: per capita, case study, and econometric. The per capita method measures municipal costs and revenues based on existing population and employment and development-induced changes in population and employment. Costs and revenues are allocated into residential and non-residential land uses. However, the per capita method does not account for excess or deficient capacity in municipal services and assumes that the cost of services for new development is the same as for existing facilities and current demand.
The case study or marginal costing method addresses the issue of lumpiness in municipal services by relying “on intensive site-specific interviews of public officials knowledgeable of local service conditions and capacities as the primary means of determining the effects of population growth on public services and costs.” (Burchell et al.1994, p.130). In this method, existing relationships between demand and supply of public services in the community are taken into explicit consideration. Edwards (2002), in fact, outlines a modified procedure that combines both the per capita and case study methods. Edwards calculates per capita operating costs and revenues associated with
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development using the per capita method and examines capital facilities using the case study approach.
The dynamic or econometric method applies “statistical techniques to time-series data…or may use cross-sectional data from multiple jurisdictions representing a variety of development patterns” (Siegel et al. 2000, p.4) to present a “moving picture” (Burchell et al. 1994, p.130) of interacting effects and impacts on a community. This is different from the previous methods, which look at a community’s profile only at one point in time.
Limitations of Fiscal Impact Analysis Fiscal impact analysis has its share of important limitations and caveats. A major consideration, as reported by Burchell et al. in 1994, is the lack of testing of reliability. Post-development numbers are not compared to projections, which undermines the empirical legitimacy of fiscal impact analysis.
Heikkila and Davis (1997) attack the underpinning of conventional fiscal methods, most notably the per capita multiplier, and argue instead for a welfare-based measure to indicate what dollar amount of compensation to existing residents would just be required for them to be as well off as they were initially before the development.
Other specific limitations with fiscal impact analysis include: Overlapping jurisdictions: Fiscal impact analysis generally is restricted in scope to a particular level of government and does not consider positive and negative spillover effects on other jurisdictions and vice-versa (Edwards 2002).
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Interaction of Land Uses: “Fiscal impact analysis does not capture the interactions among land uses when development occurs” (Edwards 2002 p.12). Residential impacts may offset the fiscal benefits of commercial developments (Siegel et al. 2000).
Cumulative Impacts: Fiscal impact analysis generally is restricted to assessing the impacts stemming from a specific development proposal, e.g., a shopping mall. An assessment of cumulative impacts from a series of interrelated developments may be necessary to tease out the fiscal impacts of anticipated development projects over time. Additionally, depending on whether a particular community is experiencing rapid growth or is fully developed (i.e., built out), important assumptions like per capita demand for services will be variable or stable with time (Siegel et al. 2000).
Planning Support Tools The GIS-based tool presented in this paper can be loosely classified as a planning support tool. In general, a planning support system refers to a set of geographic informationrelated tools used in planning activities (Geertman 2001). Planning support systems contribute to “the planning process via integrated developments usually based on multiple technologies and common interface” (Nedovic-Budic 1999, p.83).
GIS is the central technology in many decision support systems. Advancements in computer hardware and software applications have resulted in the development and proliferation of generic GIS packages. At the same time, planners, technicians, and researchers have been recognizing the practical limitations of these commercial software packages and have often customized and refined them to suit their “analytical, problem-
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solving, and decision-making” needs (Klosterman 2001, Harris and Batty 2001, NedovicBudic 1999, p.81).
Planning support systems as an evolving concept offer the potential to bring information, models, and visualizing tools to the public realm. Those tools are expected to help envision a greater number of higher quality alternative futures and facilitate more informed public debates (Harris and Batty 1993, Nedovic-Budic 1999, Geertman 2001). The support tools will also be useful in planning for floodplain naturalization. More specifically, those tools could help devise effective for governing future management and sustainability of the Illinois River basin.
PROJECT BACKGROUND AND METHODOLOGY Goals and Objectives This project was part of a larger multidisciplinary effort at the University of Illinois at Urbana-Champaign to study and model the physical, biological, and economic potential and impacts of restoring large river floodplains using the Illinois River as a study site. While a conventional fiscal impact analysis looks at both the cost and revenue streams of the government ledger to arrive at a net fiscal impact, the GIS-based tool presented concerns only with changes in property tax revenue. The tool allows the user to create new land use scenarios and compare the annual property tax revenues to baseline (existing) conditions. What-if scenarios can thus be generated by varying the input parameters, which are the land use type, the size of the chosen site, and the average equalized assessed value (EAV) of properties by type in a particular township.
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Study Area The study area covers the La Grange Reach – the middle 77-mile (124 km) section of the Illinois River, bounded upstream by the Peoria Lock and Dam and downstream by the La Grange Lock and Dam. The Reach includes territories of eight counties: Peoria, Tazewell, Fulton, Mason, Schuyler, Cass, Brown, and Morgan (Figures 1). The La Grange Reach contains extensive agricultural levees, but also natural areas and remains of backwater lakes. The area is thus suitable for exploring various naturalization scenarios.
Figure 1. La Grange Reach Study Area
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Database Requirements ESRI’s ArcGIS was used to develop the user interface and database. The user interface was developed using ESRI’s ArcObjects and Microsoft’s Visual Basic for Applications (VBA). The database contains both spatial and non-spatial information on land cover, jurisdictional boundaries, tax rates for 34 taxing districts, and average assessed value for various land use types. (Table 1 lists the datasets used and their coverage and sources). Table 1 Spatial and Non-spatial Datasets
Description
Extent
Level
Source *
Scale 1:100,000
Land cover map (23)
8 counties
County
IGIS
Land cover map (15)
Floodplain (Peoria to LaGrange Lock & Dam)
Floodplain
USGS
County lines
8 counties
County
IGIS
1:62,500
Townships lines
8 counties
Township
IGIS
1:62,500
Levee Boundaries
Illinois
Levee district
USGS
?
Tax Rates (1997 and 1998)
8 counties
Tax district
IDR***
--
Assessed value of property
8 counties
Township
IDR
--
**
?
* Illinois Geographic Information System ** United States Geological Survey ***Illinois Department of Revenue
Two land cover maps were used in developing the baseline dataset (Figure 2). The first map comprises 15 land cover classes within the floodplain of the La Grange Reach. The second, coarser map is a LANDSAT image of 23 land cover types within the boundaries of the eight counties.
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a
b
Figure 2. a) USGS Floodplain Land Cover Classification, b) LANDSAT Land Cover Classification
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Equalized assessed values (EAV) of property and total acreage for each of the five land use types in 2001 were obtained from the county assessors. Even though the county assessment lists six land use types – Residential, Commercial, Industrial, Agricultural, Railroad Property, and Mineral – the latter two types were combined into a fifth class called Barren Land. Dividing EAV by the area of a land use type in a township yields the EAV-per-acre multiplier for that land use in the township. Since residential land use is reported in number of parcels, we assumed an average parcel size of 0.5 acre.
Tool Development Figure 3 illustrates the method of combining in ArcGIS the raw datasets into a database that is then used to derive estimated tax revenues of baseline conditions (Step 1), and the steps taken by using the user interface to generate alternate land use scenarios (Step 2). In Step 1, the baseline feature class (ArcGIS layer with data) is created by first cropping a one-mile buffer around the floodplain. Second, the feature class is intersected with the two land cover feature classes. Third, the baseline feature class is overlaid with the township and tax district feature classes. Fourth, the feature class is joined with the object class (ArcGIS table of information) on the average per acre assessed property value for each land use type in each township.
The EAV for each contiguous land use type in each township is determined by first assigning the 23 different land cover classes outside the floodplain and the 15 land cover classes within the floodplain to the five land use types; and, second, by multiplying the area of each contiguous land use type by the per acre EAV multiplier. For the assignment rules we assumed that:
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the value of developed land is equivalent to the average value of residential, commercial, and industrial land use types
annual row crop cover is equivalent to 100% of agricultural land use value; and,
all other land cover types are equivalent to predetermined fractions of the value of agricultural land use.
[Figure 3 About Here]
Figure 3. Step 1: Development of Baseline GIS Layer Step 2: Scenario Building Process
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The tax rates of all taxing districts in each township are aggregated so that there is one tax rate associated for each polygon. Polygons represent any contiguous areas within a township with the same land cover type. Each polygon represents a distinct land cover type with embedded information – area in acres, total tax rate per acre, average assessed value, and total property tax revenue.
To calculate the tax revenues of each distinctive land use polygon, the following relationship is used:
R=
As LVs 100 TS 43560
where R = annual tax revenue Ts = tax rate of applicable taxing districts for the polygon As = area of the polygon (in square feet) LVs = equalized assessed land value of the polygon
Step 2 takes the baseline scenario featureclass output from Step 1, the township feature class, the tax rate featureclass, and the assessed value table as inputs to produce alternative land use scenarios via an user interface. The user delineates a proposed site to be converted and creates a new polygon feature class by using the Create Polygon function. The new polygon may overlap multiple existing land uses and cross over township boundaries (Figure 4). Alternatively, the user can use the Export Levee Polygons tool to convert an entire levee district simply by selecting the appropriate polygon in the levee district layer and exporting it to the New Scenario layer. The user can assign a new land use and/or land value to the selected naturalization site polygon. These steps can be repeated to generate many scenarios. Finally, the user can choose to output a region-wide report.
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a
b
c d
e f
g
Figure 4. a) ArcGIS file open dialog box, b) Tool file, c) Scenario building taskbar, d) Delineated site, e) New site properties dialog box; selecting new land cover, f) Editing township land value, g) County comparison report
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TOOL TESTING AND RESULTS In order to test the tool and understand the relation of revenue generated with the change in land use and land cover, the following scenarios were chosen:
1. Scenario A - Converting all agricultural land within the floodplain to forest preserve (temporarily flooded closed tree canopy)
2. Scenario B - Converting 50% of the agricultural land to forest preserve (temporarily flooded closed tree canopy land cover) and the other half to shrubland / wetland (temporarily flooded cold-deciduous shrubland)
3. Scenario C - Converting all agricultural land to shrubland / wetland (temporarily flooded cold-deciduous shrubland)
4. Scenario D – Converting all agricultural land to grassland (rural and urban)
5. Scenario E - Converting 33% of the agricultural land to shrubland / wetland (temporary flooded cold-deciduous shrubland), 33% to grasslands, 33% of the land to forest preserve (temporarily flooded closed tree canopy), and 1% land in the one mile bluff area around the floodplain to developed land (0.95% residential development and 0.05% commercial).
Figure 5 shows the change in revenue across the five scenarios. Scenario A shows an average 84 % decrease in tax revenue per county when all the land is converted to close canopy forest. This is because the land cover for this region is predominantly agricultural – a use with a higher land value than closed canopy tree. Scenario B is a mix of forest
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preserve and shrubland. Since shrubland has a lower assessed value than forest preserve, Scenario B shows a comparable decrease in the tax revenue of 83%. Similarly, Scenario C comprising of only shrubland shows an 87% decrease in tax revenue. And Scenario D comprising of only grassland shows an 83% decrease in tax revenue. Scenario E incorporates the development of residential and commercial area in 1.0% of the total land around the forest preserve, grassland and shrubland. A mix of the three uses with marginal residential\commercial development yields a slight increase (1.5%) in property tax revenue. Scenario A
Scenario B
Scenario C
Scenario D
Scenario E
10
0
-10
-20
-30
-40
-50
-60
-70
-80
-90
-100
Scenario A
Scenario B
Scenario C
Scenario D
Scenario E
Figure 5. Percentage Change in Property Tax Revenues From Baseline Conditions By Site CONCLUSIONS The issue of naturalizing agricultural or degraded landscapes is not so much about the inherent goal of naturalization, but rather the unintended impacts from it. Frequently naturalization activities are taking place in economically depressed regions of Illinois.
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The fiscal burden that naturalization can wrought on a county is clearly demonstrated with a scenario tool developed in a geographic information system. Looking at agricultural lands within a 1-mile buffer of the Illinois River in the La Grange Reach region, four of the five scenarios that were examined showed average losses in annual property tax revenue of over 80%. Only in the last scenario, where one-third of agricultural land is converted to shrubland/wetland, one-third to grasslands, one-third to forest preserve, and one percent is developed into residential and commercial uses, that annual property tax revenues in the Reach are actually above the base year values. In order to increase the flow of ecological benefits from naturalization without impinging on the flow of fiscal benefits at the county level, urban development should not be discouraged absolutely.
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REFERENCES Sparks, R.E. et al. 2000. Technical support of public decisions to restore floodplain ecosystems: a status report on the Illinois River project, USA. In: Smits, A.J.M.., Nienhuis P.H., and Leuven, R.S.E.W. (Eds.) New approaches to river management, The Netherlands, pp. 225-247. Illinois River Strategy Team. 1997. Integrated management plan for the Illinois River watershed. Springfield, Illinois: Office of the Lieutenant Governor. Sparks, R.E. et al. 1999. Strategic renewal of large floodplain rivers: integrated analysis – Project Description. Keith, J. et al. 1996. Recreation as an economic development strategy: some evidence from Utah. Journal of Leisure Research, 28(2), pp. 96-107. Burchell, R.W. et al. 1994. Development Impact Assessment Handbook. Washington, D.C.: Urban Land Institute. Edwards, M.W. 2000. Community guide to development impact analysis. Madison, WI: University of Wisconsin-Madison. Retrieved July 12, 2003 from University of Wisconsin-Madison website: http://www.lic.wisc.edu/shapingdane/facilitation/all_resources/impacts/analysis_back ground.htm Barrow, C.J. 1997. Environmental and Social Impact Assessment: An Introduction. New York: John Wiley. Runyan, D. 1977. Tools for community-managed impact assessment. Journal of the American Institute of Planners, 43: pp.125-135. Prindle, A.M. and Blaine, T.W. 1998. Costs of community services. Columbus, OH: Ohio State University Extension. Retrieved July 12, 2003 from Ohio State University website, http://ohioline.osu.edu/cd-fact/1260.html Canter, L.W., Atkinson, S.F., Leistritz, F.L. 1985. Impact of Growth: A Guide for Socioeconomic Impact Assessment and Planning. Chelsea, MI: Lewis Publishers. Hollis, L., Porter, D., and Stallworth, H. 1997. Assessing the impacts of development choices. Retrieved July 12, 2003 from The Growth Management Institute website: http://www.gmionline.org/assessing_the_impacts.htm Burchell, R.W. and Listokin, D. 1978. The Fiscal Impact Handbook: Projecting the Local Costs and Revenues Related to Growth. New Brunswick, NJ: Center for Urban Policy Research.
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Roberts, T.H. 1985. Funding public capital facilities: how community planning can help. In: Nicholas, J.C. (Ed.) The Changing Structure of Insfrastructure Finance, Florida: pp. 1-22. Siegel, M.L., Terris, J., and Benfield, K. 2000. Developments and dollars: an introduction to fiscal impact analysis in land use planning. Retrieved September 20, 2002 from http://www.nrdc.org/cities/smartgrowth/dd/ddinx.asp Geertman, S. 2001. Participatory planning and GIS: a PSS to bridge the gap. Environment and Planning B: Planning and Design, 29(1), pp. 21-35. Harris, B and Batty, M. 1993. Locational models, geographic information and planning support systems. Journal of Planning Education and Research, 12, pp. 184-198. Klosterman, R.E. 1997. Planning support systems: a new perspective on computer-aided planning. Journal of Planning Education and Research, 17(1), pp. 45-54. Nedovic-Budic, Zorica. 2000. Geographic information science implications for urban and regional planning. Journal of the Urban and Regional Information Systems Association, 12(2): pp. 81-93.
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Appendix A. County Assessor’s Land Use
Assignment of Land Cover Classes to Equivalent Land Uses % Value USGS Floodplain DNR LANDSAT Land Cover Equivalent State-wide Land (Land Use) Cover
% Value Equivalent (Land Use)
Residential
High Density
100% Ag
Commercial
Medium-High Density
Industrial
Medium Density
Barren
Low Density
Agricultural
Major Roadways
Active Railroads
Abandoned Railroads Row Crop
Small Grains
Orchards/Nurseries Urban Grassland Rural Grassland Deciduous Closed Canopy Forest Deciduous Open Canopy Forest Coniferous Undifferentiated Open Water Perennial Streams Shallow Marsh/Wet Meadow Deep Marsh Forested Wetlands Swamp Shallow Water Wetlands Barren Land
Annual row-crop forbs or grasses Developed; default to Anderson Classification Lowland or submontane cold-deciduous closed tree canopy Open water; default to Anderson Classification Permanently flooded temperate or subpolar hydromorphic rooted vegetation Roadside grass/forbs; default to Anderson Classification Saturated temperate or subpolar grassland Seasonally flooded colddeciduous closed tree canopy Seasonally flooded temperate or subpolar grassland Seasonally/temporarily flooded mudflats Tall sod temperate grassland Temperate cold-deciduous shrubland Temporarily flooded colddeciduous closed tree canopy Temporarily flooded colddeciduous shrubland Temporarily flooded sand flats
33% R + 33% C + 33% I 30% Ag
0% Ag 0% Ag
20% Ag
20% Ag 30% Ag
20% Ag
0% Ag 20% Ag 15% Ag 30% Ag
15% Ag 10% Ag
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Tax District Layer
Township Layer LANDSAT Land Cover Average EAV Table 1-mile buffer
Study Area Join
River
Floodplain Land Cover
