35 resultados para Geographic Information Systems (GIS)


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********NOTE: There are nine sections to this manual, all in separate files.************* **********NOTE: Large files may take longer to open******** The basis of real property assessment in Iowa is market value as defined in Iowa Code §441.21. Iowa Code §§ 421.17(17) and 441.21(h) provide that assessment jurisdictions follow the guidelines and rules in this manual to help achieve uniformity in assessments. Assessors are encouraged to use the International Association of Assessing Officers’ Standard on Mass Appraisal of Real Property in their mass appraisal practices. Estimating market value in mass appraisal involves accurately listing properties, developing a sales file that includes the primary influences on market value, and developing models for subsets of properties that share common market influences using recognized mass appraisal techniques. The assessment of an individual property should not be based solely on the sale price. The Uniform Standards of Professional Appraisal Practice (USPAP) standard 6 says “In developing a mass appraisal, an appraiser must be aware of, understand, and correctly employ those recognized methods and techniques necessary to produce and communicate credible mass appraisals.” Accurate listing of property is the basis of a good mass appraisal program. On-site inspection and listing of property is essential in developing a good data base for revaluation. A physical review, including an on-site verification of property characteristics, should be conducted at least every four to six years. Land values should be reviewed every two years. Factors influencing the market of each property type should be identified and collected so that these factors can be considered in the mass appraisal model. It is equally important to maintain the data once it is collected. Accessing local government permit systems should be a part of a good data maintenance program along with an inspection program. Current cadastral maps and geographical information systems (GIS) are tools that are integral in checking accuracy of listings and maintaining a comprehensive data base.

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The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

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The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

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The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

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This report describes a statewide study conducted to develop main-channel slope (MCS) curves for 138 selected streams in Iowa with drainage areas greater than 100 square miles. MCS values determined from the curves can be used in regression equations for estimating flood frequency discharges. Multi-variable regression equations previously developed for two of the three hydrologic regions defined for Iowa require the measurement of MCS. Main-channel slope is a difficult measurement to obtain for large streams using 1:24,000-scale topographic maps. The curves developed in this report provide a simplified method for determining MCS values for sites located along large streams in Iowa within hydrologic Regions 2 and 3. The curves were developed using MCS values quantified for 2,058 selected sites along 138 selected streams in Iowa. A geographic information system (GIS) technique and 1:24,000-scale topographic data were used to quantify MCS values for the stream sites. The sites were selected at about 5-mile intervals along the streams. River miles were quantified for each stream site using a GIS program. Data points for river-mile and MCS values were plotted and a best-fit curve was developed for each stream. An adjustment was applied to all 138 curves to compensate for differences in MCS values between manual measurements and GIS quantification. The multi-variable equations for Regions 2 and 3 were developed using manual measurements of MCS. A comparison of manual measurements and GIS quantification of MCS indicates that manual measurements typically produce greater values of MCS compared to GIS quantification. Median differences between manual measurements and GIS quantification of MCS are 14.8 and 17.7 percent for Regions 2 and 3, respectively. Comparisons of percentage differences between flood-frequency discharges calculated using MCS values of manual measurements and GIS quantification indicate that use of GIS values of MCS for Region 3 substantially underestimate flood discharges. Mean and median percentage differences for 2- to 500-year recurrence-interval flood discharges ranged from 5.0 to 5.3 and 4.3 to 4.5 percent, respectively, for Region 2 and ranged from 18.3 to 27.1 and 12.3 to 17.3 percent for Region 3. The MCS curves developed from GIS quantification were adjusted by 14.8 percent for streams located in Region 2 and by 17.7 percent for streams located in Region 3. Comparisons of percentage differences between flood discharges calculated using MCS values of manual measurements and adjusted-GIS quantification for Regions 2 and 3 indicate that the flood-discharge estimates are comparable. For Region 2, mean percentage differences for 2- to 500-year recurrence-interval flood discharges ranged between 0.6 and 0.8 percent and median differences were 0.0 percent. For Region 3, mean and median differences ranged between 5.4 to 8.4 and 0.0 to 0.3 percent, respectively. A list of selected stream sites presented with each curve provides information about the sites including river miles, drainage areas, the location of U.S. Geological Survey stream flowgage stations, and the location of streams Abstract crossing hydro logic region boundaries or the Des Moines Lobe landforms region boundary. Two examples are presented for determining river-mile and MCS values, and two techniques are presented for computing flood-frequency discharges.

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What we do: Since 1892, the Iowa Geological and Water Survey (IGWS) has provided earth, water, and mapping science to all Iowans. We collect and interpret information on subsurface geologic conditions, groundwater and surface water quantity and quality, and the natural and built features of our landscape. This information is critical for: Predicting the future availability of economic water supplies and mineral resources. Assuring proper function of waste disposal facilities. Delineation of geologic hazards that may jeopardize property and public safety. Assessing trends and providing protection of water quality and soil resources. Applied technical assistance for economic development and environmental stewardship. Our goal: Providing the tools for good decision making to assure the long-term vitality of Iowa’s communities, businesses, and quality of life. Information and technical assistance are provided through web-based databases, comprehensive Geographic Information System (GIS) tools, predictive groundwater models, and watershed assessments and improvement grants. The key service we provide is direct assistance from our technical staff, working with Iowans to overcome real-world challenges. This report describes the basic functions of IGWS program areas and highlights major activities and accomplishments during calendar year 2011. More information on IGWS is available at http://www.igsb.uiowa.edu/.

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The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

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The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

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The Bridges Decision Support Model is a geographic information system (GIS) that assembles existing data on archaeological sites, surveys, and their geologic contexts to assess the risk of bridge replacement projects encountering 13,000- to 150-year-old Native American sites. This project identifies critical variables for assessing prehistoric sites potential, examines the quality of available data about the variables, and applies the data to creating a decision support framework for use by the Iowa Department of Transportation (Iowa DOT) and others. An analysis of previous archaeological surveys indicates that subsurface testing to discover buried sites became increasingly common after 1980, but did not become routine until after the adoption of guidelines recommending such testing, in 1993. Even then, the average depth of testing has been relatively shallow. Alluvial deposits of sufficient age, deposited in depositional environments conducive to human habitation, are considerably thicker than archaeologists have routinely tested.

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The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

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Drainage-basin and channel-geometry multiple-regression equations are presented for estimating design-flood discharges having recurrence intervals of 2, 5, 10, 25, 50, and 100 years at stream sites on rural, unregulated streams in Iowa. Design-flood discharge estimates determined by Pearson Type-III analyses using data collected through the 1990 water year are reported for the 188 streamflow-gaging stations used in either the drainage-basin or channel-geometry regression analyses. Ordinary least-squares multiple-regression techniques were used to identify selected drainage-basin and channel-geometry regions. Weighted least-squares multiple-regression techniques, which account for differences in the variance of flows at different gaging stations and for variable lengths in station records, were used to estimate the regression parameters. Statewide drainage-basin equations were developed from analyses of 164 streamflow-gaging stations. Drainage-basin characteristics were quantified using a geographic-information-system (GIS) procedure to process topographic maps and digital cartographic data. The significant characteristics identified for the drainage-basin equations included contributing drainage area, relative relief, drainage frequency, and 2-year, 24-hour precipitation intensity. The average standard errors of prediction for the drainage-basin equations ranged from 38.6% to 50.2%. The GIS procedure expanded the capability to quantitatively relate drainage-basin characteristics to the magnitude and frequency of floods for stream sites in Iowa and provides a flood-estimation method that is independent of hydrologic regionalization. Statewide and regional channel-geometry regression equations were developed from analyses of 157 streamflow-gaging stations. Channel-geometry characteristics were measured on site and on topographic maps. Statewide and regional channel-geometry regression equations that are dependent on whether a stream has been channelized were developed on the basis of bankfull and active-channel characteristics. The significant channel-geometry characteristics identified for the statewide and regional regression equations included bankfull width and bankfull depth for natural channels unaffected by channelization, and active-channel width for stabilized channels affected by channelization. The average standard errors of prediction ranged from 41.0% to 68.4% for the statewide channel-geometry equations and from 30.3% to 70.0% for the regional channel-geometry equations. Procedures provided for applying the drainage-basin and channel-geometry regression equations depend on whether the design-flood discharge estimate is for a site on an ungaged stream, an ungaged site on a gaged stream, or a gaged site. When both a drainage-basin and a channel-geometry regression-equation estimate are available for a stream site, a procedure is presented for determining a weighted average of the two flood estimates.

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The Rathbun Land and Water Alliance and partners have undertaken a highly effective approach to water quality protection through the Rathbun Lake Special Project. This approach is achieving a significant reduction in the sediment and phosphorus that impair water quality in Rathbun Lake and its tributaries as a result of the targeted application of best management practices (BMPs) for priority land in the watershed. This project application proposes to assist landowners to apply BMPs that will reduce sediment and phosphorus delivery from priority land in one targeted sub-watershed as part of the Rathbun Lake Special Project. Features of this project are: (1) use of geographic information system (GIS) analysis to identify priority land that requires BMPs; (2) assistance for landowners to apply BMPs on 1,450 acres that will reduce the annual delivery of sediment by 2,160 tons and phosphorus by 8,210 pounds; (3) evaluation of the benefits from BMP application using GIS analysis and water quality monitoring; and (4) watershed outreach activities that encourage landowners to apply BMPs for priority land to protect water quality.

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The federal government is aggressively promoting biofuels as an answer to global climate change and dependence on imported sources of energy. Iowa has quickly become a leader in the bioeconomy and wind energy production, but meeting the United States Department of Energy’s goal having 20% of U.S. transportation fuels come from biologically based sources by 2030 will require a dramatic increase in ethanol and biodiesel production and distribution. At the same time, much of Iowa’s rural transportation infrastructure is near or beyond its original design life. As Iowa’s rural roadway structures, pavements, and unpaved roadways become structurally deficient or functionally obsolete, public sector maintenance and rehabilitation costs rapidly increase. More importantly, costs to move all farm products will rapidly increase if infrastructure components are allowed to fail; longer hauls, slower turnaround times, and smaller loads result. When these results occur on a large scale, Iowa will start to lose its economic competitive edge in the rapidly developing bioeconomy. The primary objective of this study was to document the current physical and fiscal impacts of Iowa’s existing biofuels and wind power industries. A four-county cluster in north-central Iowa and a two-county cluster in southeast Iowa were identified through a local agency survey as having a large number of diverse facilities and were selected for the traffic and physical impact analysis. The research team investigated the large truck traffic patterns on Iowa’s secondary and local roads from 2002 to 2008 and associated those with the pavement condition and county maintenance expenditures. The impacts were quantified to the extent possible and visualized using geographic information system (GIS) tools. In addition, a traffic and fiscal assessment tool was developed to understand the impact of the development of the biofuels on Iowa’s secondary road system. Recommended changes in public policies relating to the local government and to the administration of those policies included standardizing the reporting and format of all county expenditures, conducting regular pavement evaluations on a county’s system, cooperating and communicating with cities (adjacent to a plant site), considering utilization of tax increment financing (TIF) districts as a short-term tool to produce revenues, and considering alternative ways to tax the industry.

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The Rathbun Land and Water Alliance and partners have undertaken a highly effective approach to water quality protection through the Rathbun Lake Special Project. This approach is achieving a significant reduction in the sediment and phosphorus that impair water quality in Rathbun Lake and its tributaries as a result of the targeted application of best management practices (BMPs) for priority land in the watershed. This application proposes to assist landowners to apply BMPs that will reduce sediment and phosphorus delivery from priority land in targeted sub-watersheds as part of the Rathbun Lake Special Project. Features of this project are: (1) use of geographic information system (GIS) analysis to identify priority land that requires BMPs; (2) assistance for landowners to apply BMPs for 4,000 acres that will reduce the annual delivery of sediment by 6,000 tons and phosphorus by 20,000 pounds; (3) evaluation of the benefits from BMP application using GIS analysis and water quality monitoring; and (4) watershed outreach activities that encourage landowners to apply BMPs for priority land to protect water quality.

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This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.