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Geographic (spatial) analysis

One of the primary roles of GIS is to use the Geographic Information System to perform analyses for the various County Service Groups, and to teach them how to perform such analyses themselves.

Spatial relationships

The term spatial relationship can be best explained through an example. Consider the question "How many wells are in Volusia County?" This query is nonspatial in nature. The answer does not require knowledge of the physical location of the wells nor does it describe where the wells are in relation to one another. On the other hand, a question that asks "How many wells are in the County that are 10 inches in diameter and are 1000 feet apart?" is spatial in nature. To answer this question, one must have the ability to determine the location of each well, measure the distance between the wells and examine their attributes (e.g., diameter). A GIS can readily provide such information.

A GIS can do this because it has the ability to link spatial data with information (facts and figures) about a particular feature on a map. The information is stored as attributes, or characteristics, of the graphically represented feature. For example, without a GIS, a street network might be represented by simple street centerlines, in which case the actual visual representation of the road would not yield much information. To obtain the information about the road, such as type (paved, gravel, etc.), you would have to take the street name from the map and use it to query a separate database. As shown below, the GIS allows you illustrate the database on the map by using different symbols to draw the roads; such as by drawing heavy line, a regular line, or a dotted line to show whether the road is paved, surface-treated, or unpaved. The result of such a display is that the user can determine information about features on the map simply by looking at them.

In the County's ARC/INFO GIS software the 'ARC' part of the software handles the features, while the 'INFO' part handles the feature descriptions. A map depicting the County paving plan was produced by importing TIS mainframe data into 'INFO' and merging it with the GIS street centerline file stored in 'ARC'.

Types of spatial analysis

Frequently on this page, reference is made to "spatial analysis" or "geographic analysis." Performing such an analysis is a complex task performed by GIS personnel only after a great deal of planning and research. This is because "spatial analysis" is an umbrella term covering many different procedures. Descriptions of several types of spatial analyses performed by the GIS staff can be found by following the hyperlinks below:

• Spatial overlay
• Boundary analysis
• Address matching and geocoding
• Proximity analysis
• Buffer analysis
• Network analysis

Many GIS projects involve a combination of the various types of geographic analyses. For example, a project completed for VOTRAN to assist in route planning and target marketing utilized spatial overlay, buffering and network analysis. As shown in the illustration, six layers of data were overlaid to determine relationships between existing routes, low-income areas and the locations of medical facilities. Network analysis was performed to generate the routes. Then 3/4 mile buffers representing the maximum distance VOTRAN thought a person would walk to a bus stop were created around the routes. Following the analysis, routes were adjusted and a direct mail campaign was launched within certain zip codes to target potential new customers.

Data conversion

Rarely are all the data required to perform the above described analyses available from one source. And more often than not, the data are not in an immediately usable format. Therefore, a great deal of GIS staff time is devoted to data preparation and the integration of various datasets. Common data types incorporated into the GIS include tabular or statistical information from sources such as the mainframe or PCs, CAD files, Global Positioning System (GPS) coordinates, satellite imagery, and even video images.

If the data to be used are not already in digital form, that is, in a form the computer can recognize, various techniques can be used to capture the information. Maps can be digitized, or hand-traced with a computer mouse to collect the coordinates of features. Electronic scanning devices can also convert map lines and points into digital data. Identities of the objects on the map as well as their spatial relationships must then be specified.

Once all the information is in the GIS it must be manipulated so that it registers, or fits, with information gathered from other sources. So before the digital data can be analyzed, they may have to undergo other manipulations, especially projection conversions. A projection is a mathematical means of transferring information from the Earth's three-dimensional curved surface to a two-dimensional medium, such as paper or a computer screen. Different projections are used for different types of maps because each projection is particularly appropriate for certain uses.

The integration of data which may have been obtained from various sources, computerized at various scales, and based upon different projection systems, is a complex task and remains a major challenge.

Spatial Overlay

One basic way to create or identify spatial relationships is through the process of spatial overlay. Spatial overlay is accomplished by joining and viewing together separate data sets that share all or part of the same area. The result of this combination is a new data set that identifies the spatial relationships. Volusia County GISdata are stored in the State Plane Coordinate System which provides a common datum for registration of all data layers. This allows the user to view and analyze those portions of the various layers which cover the same place on the Earth.

The power of spatial overlay is illustrated by the project highlighted in the figure below. Three layers of data were used in the analysis which was designed to identify the development potential of land within the County. Polygons (enclosed areas) were assigned a rating based on vegetation type, soil type and whether they were in the 100-year floodplain. Then the three layers were combined to create a new layer which contained all the previous information. Finally, a comprehensive rating was determined by performing a weighted average of the three separate rating items. The result was a map contrasting suitable and unsuitable areas for development based on the land characteristics.

Network Analysis

Network analysis is used for identifying the most efficient routes or paths for allocation of services. This involves finding the shortest or least-cost manner in which to visit a location or a set of locations in a network. The "cost" in a network analysis is frequently distance or travel time. The illustration below shows how GIS staff performed such an analysis to highlight areas within a two-mile driving distance from a fire station.

Network analysis can also be used to optimize the allocation of resources. This example also shows the amount of overlap between the service areas of two fire stations. Fire Services was therefore able to optimize their response times by forming a plan based on this information. Even in cases such as this, when relocating a distribution center is impractical, such information can prove valuable in forming protocols.

Buffer Analysis

Buffer analysis is used for identifying areas surrounding geographic features. The process involves generating a buffer around existing geographic features and then identifying or selecting features based on whether they fall inside or outside the boundary of the buffer.

For example, the GIS was used to identify the locations of hazardous chemical storage sites in relation to health care facilities. The purpose of the project was to facilitate the evacuation of the health care facilities in the event of a leak or spill of hazardous materials. The process involved representing each hazardous material storage site on the map as a point. Each point was coded with information that indicated the type of chemical stored, as well as the rate of spread with low and high wind speeds. In the case of a spill, evacuation of each health care facility would be initiated based on its location in relationship to the spread of the chemical.

Other Types of Spatial Analysis

Overlay and combination operations

Overlay operations involve the placement of one map layer (set of features) A, on top of a second map layer, B, to create a map layer, C, that is some combination of A and B. C is normally a new layer, but may be a modification of B. Layer A in a vector GIS will consist of points, lines and/or polygons, whilst layer B will normally consist of polygons. All objects are generally assumed to have planar enforcement, and the resulting object set or layer must also have planar enforcement. The general term for such operations is topological overlay, although a variety of terminology is used by different GIS suppliers, as we shall see below. In raster GIS layers A and B are both grids, which should have a common origin and orientation — if not, resampling is required.

· The process of overlaying map layers has some similarity with point set theory, but a large number of variations have been devised and implemented in different GIS packages. The principal operations have previously been outlined as the spatial analysis component of the OGC simple features specification (Table 4‑2). The open source package, GRASS, is a typical example of a GIS that provides an implementation of polygon overlay which is very similar to conventional point set theory (Figure 4‑15).

Figure 4‑15 GRASS overlay operations, v.overlay

Input A	Input B
A Intersection B	A Union B (A AND B, A must be a polygon)
A NOT B	A XOR B (A must be a polygon)

Source: http://grass.itc.it/screenshots/vector.php

Functions provided by GRASS include:

· Intersection, where the result includes all those polygon parts that occur in both A and B

· Union, where the result includes all those polygon parts that occur in either A or B, so is the sum of all the parts of both A and B

· Not, where the result includes only those polygon parts that occur in A but not in B (sometimes described as a Difference operation), and

Exclusive or (XOR), which includes polygons that occur in A or B but not both, so is the same as (A Union B) minus (A Intersection B)

TNTMips provides similar functionality and uses much the same terminology as GRASS (AND, OR, SUBTRACT, XOR) under the heading of vector combinations rather than overlay operations, and permits lines as well as polygons as the “operator” layer.

Note: (a) these operations may split up many of the original polygons (and/or lines) to create a new set of features, each with their own (inherited and derived) attributes (lengths, areas, perimeters, centroids, and associated attributes from A and/or B). New composite regions (with associated combined attribute datasets) are often the desired end result, in which case borders between adjacent polygons may be dissolved and datasets merged in order to achieve this end result; (b) operations are not generally symmetric, i.e. AB is not necessarily the same as BA, both from a point of view of the geometry and associated attribute data held in tables.

In ArcGIS operations of this type are known by the general term “Overlay”, whilst in Manifold the ArcGIS Overlay operations are described as Topological Overlays to distinguish these composite operations from the more component based operations that Manifold describes as Spatial Overlays. Other vector GIS packages use descriptions such as cookie cutters (or EXTRACT operations) and spatial joins, and without doubt the terminology is confusing — the exact consequences of such operations applied using any particular GIS package will be different and should be examined very carefully. The ArcGIS implementation provides four main Overlay functions: Intersection and Union, which are essentially similar to those illustrated in Figure 4‑15, and two additional operations: Identity, which splits up the elements in B based on the position of elements in A; and Update, which amends those parts of B that intersect with A such that in these regions B’s geometry and associated data reflects those of A.

The Manifold GIS generalizes the notion of overlay to include spatial proximity, for example lines that touch areas, and areas that are adjacent to (immediate neighbors of) other areas. The full set of permitted methods is shown in Table 4‑3.

Table 4‑3 Spatial overlay methods, Manifold GIS

	Contained	Containing	Intersecting	Boundary	Touching	Neighboring
Areas, A	A,L,P	A	A,L	P	A,L	A,L
Lines, L	L,P	A,L	A,L	P	A,L	A,L
Points, P		A,L			P	A,L

Manifold also permits polygons within a layer to be overlapping, which can result in more complex output patterns. In all cases the Manifold Spatial Overlay process transfers data (fields) from a source object (set of features of the same type) to a target object (also a set of features of the same type) according to transfer rules. These rules specify how the data fields are to be transferred (e.g. copied, summed) conditional upon the spatial overlay method. As such they are rather like an SQL "Update table" or "Create table" command, subject to "Where" conditions.

Polygon-on-polygon overlay, which is a relatively common procedure, frequently results in the creation of very small thin polygons known as slivers. These may be the genuine result of an overlay operation (i.e. valid objects and data) or they may be artifacts, created as a result of differences in the original data capture, manipulation or storage process associated with A and B, even though they should exactly match in places. Such slivers may be removed automatically during the overlay operation, usually by setting tolerance levels, or by post-processing, e.g. removing all polygons with a width less than a tolerance value and replacing these with an arc along the sliver centerline or assigning them to the largest adjacent polygon (e.g. in ArcGIS use the ELIMINATE function in ArcToolbox; in Manifold use the Normalize Topology function).

Overlays involve operations where two distinct sets of spatial object are combined in particular manner, visualized as overlaying one upon the other. Many other forms of combination are possible. For example, with a single layer of polygons, boundaries between polygons could be removed (dissolved) if the polygons are adjacent/share a common boundary and meet certain criteria. The attributes of the newly formed polygon will be the sum or some other measure of the component parts. If a new map layer is created by this process rather than an existing layer modified the process is sometimes described as merging rather than dissolving.

Manifold permits the use of the Dissolve operation on lines and points as well as polygons. In the case of lines, multiple line segments are replaced with a single line segment, whilst with points multiple points are replaced by a single center point. The attribute used to guide the dissolve process may be transferred to the new object(s) as: Blank (i.e. do not transfer values for this field); Average; Count; Maximum; Minimum; Sample (randomly chosen value from the original object); or Sum. Other fields are transferred according to transfer rules set for each field.

ArcGIS supports two additional composite operations: Erase and Symmetric difference. In the Erase operation objects in A overlaid on B result in the removal of those parts of B that intersect with A (essentially the NOT operation of GRASS). Symmetric difference is similar to Erase, but those parts of A that do not intersect with B are included in the output set also (essentially the XOR operation we described earlier for GRASS). In addition ArcGIS supports operations such as Split, Append (a merge operation) and Integrate, which combine or separate features according to well-defined rules. Collectively within ArcGIS these various facilities are described as Geoprocessing Tools, and in ArcGIS V8 were available via a “Geoprocessing Wizard” but in ArcGIS V9 are provided in ArcToolbox as separately identified functions.

Types of GIS Analysis

Information Retrieval:

With a GIS we can point at a location, object, or area on the screen and retrieve recorded information about it from the DBMS, which holds the information about the map’s features. In order for a GIS to answer the question "what is where?" we need to carry out retrieval. Retrieval is the ability of the DBMS or GIS to get back on demand data that were previously stored (Clarke, 1997). As Clarke put it "Geographic search is the secret to GIS data retrieval"

Searches by attribute

Most GIS systems include as part of the package a fairly basic relational database manager, or simply built on the exiting capabilities of a database system. All DBMS include functions for basic data display. Searches by attribute are then controlled by the capabilities of database manager. Find is the basic attribute search (Clarke, 1997). Find is intended to get a single record. Find can be browse or by searches. Examples include show attributes, show records, generate a report, find, recode, select, renumber, sort, compute allows the creation of new attributes based on calculated values, restrict, join, replace; all are examples of data reorganization. Attribute queries are not very useful for geographic search as they don’t or difficult to indicate location; so they just work as humble assistants in our geographical searching needs.

Searches by geography

In a map database the records are features. The GIS spatial retrieval is the generating maps, which allow searching for information visually and highlights the result, (Clarke, 1997). For example to generate a report; the spatial equivalent would to produce a finished map; the spatial equivalent of a find is locate. Spatial equivalents of the DBMS queries result in locating sets of features, or building new GIS layers. These include: Spatial searching, browsing the map and picking features, Spatial sorting to identify features that result from attribute sorting, Recoding features spatially, that is changing the scope of their attribute, is equivalent to spatial merge, Spatial select is to extract specific features. The form of select used most is buffer operation. Buffering is a spatial retrieval around points, lines, or areas based on distance, a join operation is the cross-construction of a database by merging attributes across flat files, in spatial terms it is called overlay. Thus overlay is a spatial retrieval operation that is equivalent to an attribute join. Combinations of spatial and attribute queries can build some complex and powerful GIS operations, such as weighting e.g. dominant ethnic group in an area. Entire suites of geographic searches are searches and tests by relations of points, lines, and areas. Typical GIS searches are point in polygon, line in polygon, and point distance to line (Clarke, 1997).

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Map Overlay in GIS

the process of taking two different thematic maps of the same area and overlaying them one on top of the other to form a new map layer.

“The ability to integrate data from two
sources using map over is perhaps the key
GIS analysis function”.

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ArcGIS Spatial Analyst: Derive Answers from Your

ArcGIS Spatial Analyst is an extension to ArcGIS Desktop that provides powerful tools for comprehensive, raster-based spatial modeling and analysis. Using ArcGIS Spatial Analyst, you can derive new information from your existing data, analyze spatial relationships, build spatial models, and perform complex raster operations.

Self-documenting models make it easy for others to understand the spatial analysis process applied, examine what-if scenarios, and compare results. With ArcGIS Spatial Analyst tools, you can

• Find suitable locations.
• Calculate the accumulated cost of traveling from one point to another.
• Perform land-use analysis.
• Predict fire risk.
• Analyze transportation corridors.
• Determine pollution levels.
• Perform crop yield analysis.
• Determine erosion potential.
• Perform demographic analysis.
• Conduct risk assessments.
• Model and visualize crime patterns.

Read success stories to see how organizations worldwide use ArcGIS Spatial Analyst to help solve real-world problems.

Moving away from Poverty A Spatial Analysis of Poverty and Migration in Albania

This paper analyses recent patterns of migration and poverty in Albania, a country that - following the collapse of the communist regime in 1990 – has been experiencing high migration rates. Using a combination of survey and census data, the paper characterises spatial patterns in the distribution of poverty and migration at a high level of geographic disaggregation. The results emphasise the importance of analysing internal and international migration as different phenomena, as the two appear to be associated in opposite ways to observed poverty and welfare levels. While poverty acts as a push factor for internal migration, it seems to be a constraining factor for the more costly international migration. The results also suggest that rural migration to urban areas contributes to the relocation of poverty in urban areas.

Spatial Analysis and GIS: A Primer

Understanding the spatial distribution of data from phenomena that occur
in space constitute today a great challenge to the elucidation of central questions
in many areas of knowledge, be it in health, in environment, in geology, in
agronomy, among many others. Such studies are becoming more and more
common, due to the availability of low cost Geographic Information System (GIS)
with user-friendly interfaces. These systems allow the spatial visualization of
variables such as individual populations, quality of life indexes or company sales
in a region using maps. To achieve that it is enough to have a database and a
geographic base (like a map of the municipalities), and the GIS is capable of
presenting a colored map that allows the visualization of the spatial pattern of the
phenomenon.
Besides the visual perception of the spatial distribution of the
phenomenon, it is very useful to translate the existing patterns into objective and
measurable considerations, like in the following cases:

· Epidemiologists collect data about the occurrence of diseases. Does the
distribution of cases of a disease form a pattern in space? Is there any
association with any source of pollution? Is there any evidence of
contagion? Did it vary with time?

· We want to investigate if there is any spatial concentration in the
distribution of theft. Are thefts that occur in certain areas correlated to
socio-economic characteristics of these areas?

· Geologists desire to estimate, from some samples, the extension of a
mineral deposit in a region. Can those samples be used to estimate the
mineral distribution in that region?

· We want to analyze a region for agricultural zoning purposes. How to
choose the independent variables – soil, vegetation or geomorphology –
and determine what the contribution of each one of them is to define
where each type of crop is more adequate?

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GPS Navigation Improvements

The Global Navigation System was designed for the US Military. The first GPS satellite was launched early in 1978 and the twenty fourth of the first generation satellites was launched in October 1985. The launching of the GPS system forever changed the way wars are waged and ultimately land and water navigation by the public around the world. President Ronald Reagan decreed the GPS signals were to be available to the public for their benefit. Receiving GPS signals is free if you own or purchase a GPS unit.

The only difference in the signals received by the US Military and the public is signal accuracy. Signals received by the public are accurate to within one meter anywhere in the world. Military GPS signals are more accurate. Also US government installations and other sensitive sites are automatically blocked from civilian GPS units for the sake of safety.

The GPS satellite system is managed by the US Air Force. These satellites orbit the earth in precise orbits once each day.

Civilian use of the GPS system has taken off in the last ten years. Units are now available for practically any use you can imagine. Units are available for cars, commercial trucks, agriculture, ships, boats and multiple other uses. Handheld units have become very popular for hunting, fishing, camping, hiking, biking and units are available that are only used to track people, cars and animals. Of course surveyors and map makers also use GPS technology. Ocean going shippers now use individual units in cargo shipments to keep up with cargo for more accurate timing and delivery operations. Carriers such as UPS use GPS units for more precise routing and finding addresses for delivery.

Other governments like Russia and China are working on GPS technology for their own use. It seems like the world has really taken notice of our Yankee ingenuity and is trying to catch up with our technology.

GPS receivers need data from three satellites for basic navigation and four for precise information. WAAS is a synonym for Wide Area Augmentation System, developed for the Federal Aviation Administration for aircraft safety. Using WAAS planes can take off and land without any visual information. It allows accuracy to within three meters anywhere in the world.

Join the GPS revolution and realize the benefits.

Author: LaZinnia Manley All Rights Reserved 08-24-2009

For more information visit me at Garmin Handheld GPS.

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How GIS Maps Are Used Today

GIS refers to technology known as geographic information systems. These systems capture, analyze, and present data based on location. The presentation is usually in the form of a map, but can also be output in other forms for analysis or to convey information. These systems are used by many industries, state and local government authorities, the Federal government and the military. Most of the systems are fairly similar, with the exception of the military which has different uses for the data. The use of GIS mapping has actually been around since the 1960's with the early computers. However, due to the massive amounts of data involved in these applications, there use did not become more widespread until the early 1980's.

This is when the computing resources became significantly faster at an affordable price. The earliest application of GIS technology was in Canada for a mapping project conducted by the federal Department of Forestry and Rural Development. The technology was used to develop detail mapping of rural land throughout Canada. The government was interested in determining where land was available for various purposes including agriculture, recreation and forestry. With the introduction of less costly and higher powered technology, the uses of GIS maps has grown significantly.

The applications have gone beyond simply presenting a map of land by type of use, to characteristics and demographics about the land. In the retail environment, companies will develop maps integrated with census and other data, to identify locations for building new stores or conducting various marketing activities. Governments can create maps to identify where services are needed, for example, locating areas where that are underserved by physicians or hospitals.

Law enforcement agencies have been using GIS to create maps identifying areas with criminal activity in order to increase patrols in that area. Events like 9/11 and Hurricane Katrina have allowed emergency responders to identify escape routes and relocation facilities. The advantage of GIS mapping is that it produces output, in the forms of map and other data, in a single place. By linking this data, it provides an easy to understand representation of the information. As computing capabilities increase the available applications will also grow.

For more information on GIS Maps and the related technology, please visit http://www.intermap.com.

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Life is a GPS

Anyone who owns a recent model car with a GPS system is familiar with the turn by turn instructions it provides. When you remain on course it simply tells you how many miles until your next turn and whether it will be a right or a left. If you are off course, however, it will either tell you to recalculate or make a legal U turn ahead.

Life is like that GPS system. We go along on one course until circumstances dictate a change in direction. Many people are now recalculating their career path due to the economic conditions. When you honestly review exactly where you are at the moment, how does that match your goal projections? Are you on target to achieve your goals? When you think about your day, do you get excited and happy to go to work? Do you dread Monday mornings?

Your immediate feeling when you wake up and think about starting your day indicates your feelings about what you are doing for a living. If you are excited and grateful for the opportunity, wonderful. I suspect that is not the case or you would not be researching opportunities for home based businesses. What you do for a living does not have to be drudgery. When you are your own boss and you have total control of your future, it is exciting, challenging and rewarding.

If your work feel like being a salve to someone else's dictates and desires, maybe it is time to have the GPS of your life recalculate your future and change directions. Life is too short to be miserable. Miserable and under paid really deserves recalculating.

In order to reset the GPS to a new direction, we need to define exactly what destination might be best for you. There are several questions to ask yourself.

1. What are you doing when you are the most happy?
2. What are you doing when you feel the most productive?
3. What are you doing when you feel the most challenged and liking it?
4. What are you doing when you feel the most profitable?
5. What are you doing when you are learning something new and liking it?

The answers to these questions give you a clue as to the new direction you would like for your life and career path to follow. It really is possible to earn an ideal living, enjoy what you are doing and know you are giving real value to people at the same time.

The ideal situation is to get out of bed every morning like a child on Christmas morning. I have heard Dr. Srikumar Rao, legendary professor at the Columbia School of Business and the London School of Business, says you should feel so grateful for what you are doing for your career that you want to get down on your knees in gratitude.

If this level of excitement and gratitude does not resemble your feelings about what you do for a living, it is time to explore the idea of recalculating the GPS for your life.

26 years experience as a successful entrepreneur, post-graduate degrees in Communication and Alternate Dispute Resolution, and a proven track record as a teacher, coach and mentor, revealed the success formula.

Network marketing achievements for the last 4 years. Executive Committee, Ethics Committee, Certified Consultant Seminar Program, Leadership Support Team, Leadership Award Synergy Saturday, Empower Magazine, Millionaire Mastermind Group and selected as Consultant of the Month by Network Marketing Magazine in July 2007.

Elaine Love, Owner
Results For Life LLC
Certified Master M3 Consultant
http://www.NewMillionaireBlueprint.com

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