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Aerial photography and satellite images are extra sources for collecting data and identifying attributes which can be mapped in layers over a location facsimile of scale. The scale of a map and geographical rendering area representation type are very important aspects since the information content depends mainly on the scale set and resulting locatability of the map's representations.
Uncertainty is a significant problem in designing a GIS because spatial data tend to be used for purposes for which they were never intended. Some maps were made many decades ago, where at that time the computer industry was not even in its perspective establishments. This has led to historical reference maps without common norms. Map accuracy is a relative issue of minor importance in cartography. All maps are established for communication ends.
Maps use a historically constrained technology of pen and paper to communicate a view of the world to their users.
Cartographers feel little need to communicate information based on accuracy, for when the same map is digitized and input into a GIS, the mode of use often changes. The new uses extend well beyond a determined domain for which the original map was intended and designed. A quantitative analysis of maps brings accuracy issues into focus. The electronic and other equipment used to make measurements for GIS is far more precise than the machines of conventional map analysis.
The truth is that all geographical data are inherently inaccurate, and these inaccuracies will propagate through GIS operations in ways that are difficult to predict, yet have goals of conveyance in mind for original design.
A GIS can also convert existing digital information, which may not yet be in map form, into forms it can recognize, employ for its data analysis processes, and use in forming mapping output. For example, digital satellite images generated through remote sensing can be analyzed to produce a map-like layer of digital information about vegetative covers on land locations.
Another fairly recently developed resource for naming GIS location objects is the Getty Thesaurus of Geographic Names GTGN , which is a structured vocabulary containing about 1,, names and other information about places. Data representation GIS data represents real objects such as roads, land use, elevation, trees, waterways, etc. Real objects can be divided into two abstractions: discrete objects e.
Traditionally, there are two broad methods used to store data in a GIS for both kinds of abstractions mapping references: raster images and vector. Points, lines, and polygons are the stuff of mapped location attribute references. A new hybrid method of storing data is that of identifying point clouds, which combine three-dimensional points with RGB information at each point, returning a "3D color image".
GIS Thematic maps then are becoming more and more realistically visually descriptive of what they set out to show or determine. Raster A raster data type is, in essence, any type of digital image represented by reducible and enlargeable grids.
Anyone who is familiar with digital photography will recognize the Raster graphics pixel as the smallest individual grid unit building block of an image, usually not readily identified as an artifact shape until an image is produced on a very large scale.
A combination of the pixels making up an image color formation scheme will compose details of an image, as is distinct from the commonly used points, lines, and polygon area location symbols of scalable vector graphics as the basis of the vector model of area attribute rendering. While a digital image is concerned with its output blending together its grid based details as an identifiable representation of reality, in a photograph or art image transferred into a computer, the raster data type will reflect a digitized abstraction of reality dealt with by grid populating tones or objects, quantities, cojoined or open boundaries, and map relief schemas.
Aerial photos are one commonly used form of raster data, with one primary purpose in mind: to display a detailed image on a map area, or for the purposes of rendering its identifiable objects by digitization.
Additional raster data sets used by a GIS will contain information regarding elevation, a digital elevation model , or reflectance of a particular wavelength of light, Landsat, or other electromagnetic spectrum indicators. Digital elevation model, map image , and vector data Raster data type consists of rows and columns of cells, with each cell storing a single value.
Raster data can be images raster images with each pixel or cell containing a color value. Additional values recorded for each cell may be a discrete value, such as land use, a continuous value, such as temperature, or a null value if no data is available. While a raster cell stores a single value, it can be extended by using raster bands to represent RGB red, green, blue colors, colormaps a mapping between a thematic code and RGB value , or an extended attribute table with one row for each unique cell value.
The resolution of the raster data set is its cell width in ground units. Database storage, when properly indexed, typically allows for quicker retrieval of the raster data but can require storage of millions of significantly sized records.
Vector In a GIS, geographical features are often expressed as vectors, by considering those features as geometrical shapes.
Different geographical features are expressed by different types of geometry: Points A simple vector map, using each of the vector elements: points for wells, lines for rivers, and a polygon for the [lake Zero-dimensional points are used for geographical features that can best be expressed by a single point reference—in other words, by simple location. Examples include wells, peaks, features of interest, and trailheads.
Points convey the least amount of information of these file types. Points can also be used to represent areas when displayed at a small scale. For example, cities on a map of the world might be represented by points rather than polygons. No measurements are possible with point features. Lines or polylines One-dimensional lines or polylines are used for linear features such as rivers, roads, railroads, trails, and topographic lines. Again, as with point features, linear features displayed at a small scale will be represented as linear features rather than as a polygon.
Line features can measure distance. Polygons Two-dimensional polygons are used for geographical features that cover a particular area of the earth's surface. Such features may include lakes, park boundaries, buildings, city boundaries, or land uses. Polygons convey the most amount of information of the file types.
Polygon features can measure perimeter and area. Each of these geometries are linked to a row in a database that describes their attributes. For example, a database that describes lakes may contain a lake's depth, water quality, pollution level. This information can be used to make a map to describe a particular attribute of the dataset.
For example, lakes could be coloured depending on level of pollution. Different geometries can also be compared. For example, the GIS could be used to identify all wells point geometry that are within one kilometre of a lake polygon geometry that has a high level of pollution.
Vector features can be made to respect spatial integrity through the application of topology rules such as 'polygons must not overlap'. Vector data can also be used to represent continuously varying phenomena. Contour lines and triangulated irregular networks TIN are used to represent elevation or other continuously changing values.
TINs record values at point locations, which are connected by lines to form an irregular mesh of triangles. The face of the triangles represent the terrain surface. Advantages and disadvantages There are some important advantages and disadvantages to using a raster or vector data model to represent reality: Raster datasets record a value for all points in the area covered which may require more storage space than representing data in a vector format that can store data only where needed.
Raster data is computationally less expensive to render than vector graphics There are transparency and aliasing problems when overlaying multiple stacked pieces of raster images Vector data allows for visually smooth and easy implementation of overlay operations, especially in terms of graphics and shape-driven information like maps, routes and custom fonts, which are more difficult with raster data.
Vector data can be displayed as vector graphics used on traditional maps, whereas raster data will appear as an image that may have a blocky appearance for object boundaries. Vector data is more compatible with relational database environments, where they can be part of a relational table as a normal column and processed using a multitude of operators.
Vector file sizes are usually smaller than raster data, which can be tens, hundreds or more times larger than vector data depending on resolution. Vector data is simpler to update and maintain, whereas a raster image will have to be completely reproduced. Example: a new road is added.
Vector data allows much more analysis capability, especially for "networks" such as roads, power, rail, telecommunications, etc. Examples: Best route, largest port, airfields connected to two-lane highways.
Raster data will not have all the characteristics of the features it displays. Non-spatial data Additional non-spatial data can also be stored along with the spatial data represented by the coordinates of a vector geometry or the position of a raster cell.
In vector data, the additional data contains attributes of the feature.
For example, a forest inventory polygon may also have an identifier value and information about tree species. In raster data the cell value can store attribute information, but it can also be used as an identifier that can relate to records in another table.
Software is currently being developed to support spatial and non-spatial decision-making, with the solutions to spatial problems being integrated with solutions to non-spatial problems. The end result with these flexible spatial decision-making support systems FSDSSs  is expected to be that non-experts will be able to use GIS, along with spatial criteria, and simply integrate their non-spatial criteria to view solutions to multi-criteria problems.
This system is intended to assist decision-making. Data capture Example of hardware for mapping GPS and laser rangefinder and data collection rugged computer.
The current trend for GIS is that accurate mapping and data analysis are completed while in the field. Depicted hardware field-map technology is used mainly for forest inventories, monitoring and mapping. Data capture—entering information into the system—consumes much of the time of GIS practitioners.
There are a variety of methods used to enter data into a GIS where it is stored in a digital format. Existing data printed on paper or PET film maps can be digitized or scanned to produce digital data. A digitizer produces vector data as an operator traces points, lines, and polygon boundaries from a map. Scanning a map results in raster data that could be further processed to produce vector data. Survey data can be directly entered into a GIS from digital data collection systems on survey instruments using a technique called coordinate geometry COGO.
New technologies allow to create maps as well as analysis directly in the field, projects are more efficient and mapping is more accurate. Remotely sensed data also plays an important role in data collection and consist of sensors attached to a platform. Sensors include cameras, digital scanners and LIDAR, while platforms usually consist of aircraft and satellites. Recently with the development of Miniature UAVs, aerial data collection is becoming possible at much lower costs, and on a more frequent basis.
For example, the Aeryon Scout was used to map a 50 acre area with a Ground sample distance of 1 inch in only 12 minutes. Soft-copy workstations are used to digitize features directly from stereo pairs of digital photographs. These systems allow data to be captured in two and three dimensions, with elevations measured directly from a stereo pair using principles of photogrammetry. Currently, analog aerial photos are scanned before being entered into a soft-copy system, but as high quality digital cameras become cheaper this step will be skipped.
Satellite remote sensing provides another important source of spatial data. Here satellites use different sensor packages to passively measure the reflectance from parts of the electromagnetic spectrum or radio waves that were sent out from an active sensor such as radar.
Remote sensing collects raster data that can be further processed using different bands to identify objects and classes of interest, such as land cover. When data is captured, the user should consider if the data should be captured with either a relative accuracy or absolute accuracy, since this could not only influence how information will be interpreted but also the cost of data capture.
In addition to collecting and entering spatial data, attribute data is also entered into a GIS. For vector data, this includes additional information about the objects represented in the system. After entering data into a GIS, the data usually requires editing, to remove errors, or further processing. For vector data it must be made "topologically correct" before it can be used for some advanced analysis.
For example, in a road network, lines must connect with nodes at an intersection. Errors such as undershoots and overshoots must also be removed. For scanned maps, blemishes on the source map may need to be removed from the resulting raster. For example, a fleck of dirt might connect two lines that should not be connected. GIS is a science. Its value relies upon its coverage. The way in which geographic information is created and exploited through GIS affects us as citizens.
There are perhaps 50 other books on GIS now on the world market. It is a foolish individual who sees it only as a commodity like baked beans or shaving foam. It underpins the rapid growth of trading in geographic information gcommerce. For this reason we devote an entire section of this book to management issues. These are available. This is by no means the only available software for learning GIS: It is taught as a component of a huge range of undergraduate courses throughout the world.
In this second edition. These books. Many of these developments have been. As we say elsewhere in this book. This book is the companion for everyone who desires a rich understanding of how GIS is used in the real world. We have not attempted to set down any kind of rigid GIS curriculum beyond the core organizing principles. Our audience Originally.
We thus convey this success through use of real not contrived. We hope that instructors will be happy to use this book as a core teaching resource.
They are cross-linked in detail to individual chapters and sections in the book. GIS is an important transferable skill because people successfully use it to solve real-world problems. The format of the book is intended to make learning about GIS fun. They were not designed as books for those being introduced to the subject.
There are. It is very easy to lose touch with what is new in GIS. And you need to be exposed — for that is reality — to the inter-dependencies in any organization and the tradeoffs in decision making in which GIS can play a major role. With this in mind. Such users might desire an up-to-date overview of GIS to locate their own particular endeavors.
We have tried to provide a number of ways in which they can encourage their. GIS is not just about machines. We have structured the material in each of the sections of the book in a cumulative way. But even this does not convey the excitement of learning about GIS that only comes from doing. This companion can be thought of as a textbook. Our Instructor Manual see www. GIS today is both an increasingly mature technology and a strategically important interdisciplinary meeting place.
To differing extents. Success in GIS often comes from dealing as much with people as with machines. We hope that we have again created something novel but valuable by our lateral thinking in all these respects. A review and research task — involving integration of issues discussed in the chapter with those discussed in additional external sources. Thus the book is complemented by a website www. We have recognized that GIS is driven by real-world applications and real people.
It has been written by a multinational partnership. The book that you have in your hands has been completely restructured and revised. The examples of GIS people and problems that are scattered through this book have been chosen deliberately to illuminate this commonality. A review of material contained in the chapter. One of the authors is an employee of a leading software vendor and two of the other three have had business dealings with ESRI over many years.
A compare and research task — similar to the review and research task above. Only by a combination of approaches can such crucial matters as principles. We have linked our book to online learning resources throughout. At the end of each chapter we provide four questions in the following sequence that entail: The very nature of GIS as an underpinning technology in huge numbers of applications. Just as scientists need to be aware of the complexities of interactions between people and the environment.
Summary This is a book that recognizes the growing commonality between the concerns of science. The on-line lab classes have also been designed to allow learning in a self-paced way. We wish to point out. These are addressed in the Instructor Manual to the book www. As the title implies. The new learning paradigm This is not a traditional textbook because: Conventions and organization We use the acronym GIS in many ways in the book. In short. We remain convinced of the need for high-level understanding and our book deals with ideas and concepts — as well as with actions.
In a similar way. To complicate matters still further. Amy Garcia. Many of those listed above also helped us in our work on the second edition.
Sonja Curtis.. We also use the acronym in both singular and plural senses. Justin Norry.. Bethan Thomas. Ian Masser. Nancy Tosta. Scott Morehouse. Lou Page. Elanor McBay. Henk Ottens. Goodchild M. David Martin. Sally Wilkinson. Dick Birnie. Les Hepple. New York. Mike de Smith. Vanessa Lawrence. Doug Nebert. University College London Michael Goodchild. Josef Strobl. Mike Batty. Maguire D. We thank them all for those contributions and the discussions we have had over the years.
Peter Haggett. Christopher Roper.
Rob Garber. But much of it draws upon contributions made by friends and colleagues from across the world. Acknowledgments We take complete responsibility for all the material contained herein. Each of us remains indebted in different ways to Stan Openshaw.
Karen Siderelis. Andy Hudson-Smith. We distinguish between the various meanings where appropriate. Doug Richardson. Ian McHarg.
Steve Evans. Roger Tomlinson. Nick Chrisman.. John Calkins. Hugh Neffendorf. Peter Schaub. Randy Clast. Helen Ridgway. Alex Singleton. Rita Colwell. We cap the book off with an Epilog that summarizes the main topics and looks to the future..
Dave Unwin. Rich Harris. Muki Haklay. David Chapman. But this time around we additionally acknowledge the support of: Tessa Anderson. Analysis 12 through 16 and Management and Policy Chapters 17 through Andy Finch. Garry Scanlan. Redlands CA David Rhind. Jason Dykes. Greg Cho. Clint Brown. Management and Applications two volumes. Duncan Shiell.
Jan Rigby. Denise Lievesley. Jonathan Rhind. Martin Dodge. Please tell us — either way! Robert Laurini. David Willey. Bob Maher. Management and Applications abridged edition. Nancy Chin. We cannot mention all of them but would particularly like to mention the following. ESRI Inc. Larry Sugarbaker. John Leonard. Dawn Robbins. Carol Tullo. Jo Wood. Fraser Taylor. Aidan Slingsby.
Christian Castle. Russell Morris. Sarah Paul Longley. David Mark. Keith Clarke. Jonathan Raper. Richard Bailey.
The boundaries between these sections are in practice permeable. Elena Besussi. David Ashby. David Simonett. Peter Paisley. London October Further reading Maguire D.
Longley P. Jack Dangermond. Chuck Killpack. Tom Veldkamp. Gayle Gaynor. Nick Mann. Andy Coote. Jim Harper. Andrew Frank. Pip Forer. Brad Baker. Danny Dorling. David Miller. Paul Torrens. Sophie Hobbs. Sarah Smith. Sorin Scortan. City University. Mike Worboys. Max Egenhofer. Bob Barr.. Francis Harvey. Techniques Chapters 7 through Peter Verburg.
Karen Kemp. Daryl Lloyd. Cath Pyke. Hank Gerie. Larry Orman. Geof Offen. How do scientists use GIS. What is special about it? What is information generally. How do companies make money from GIS? What is geographic information science. Michael Goodchild.
David Maguire. What kinds of decisions make use of geographic information? What is a geographic information system. Governments solve geographic problems when they decide how to allocate funds for building sea defenses. Recognize the sometimes invisible roles of GIS in everyday life. Understand the many impacts GIS is having on society. Some of these are so routine that we almost fail to notice them — the daily question of which route to take to and from work.
The information needed to service the building is also local — the size and shape of the parcel. Problems that involve an aspect of location. Knowing where something happens can be critically important.
We travel over it and in the lower levels of the atmosphere. Scale or level of geographic detail is an essential property of any GIS project. Understand the significance of geographic information science. Here are three bases for classifying geographic problems.. Keeping track of all of this activity is important. In addition. Be familiar with a brief history of GIS. Travelers and tourists solve geographic problems when they give and receive driving directions.
We dig ditches and bury pipelines and cables. The global diffusion of the severe acute respiratory syndrome SARS epidemic. Transportation authorities solve geographic problems when they select routes for new highways. Others are quite extraordinary occurrences. Knowing where something happens is of critical importance if we want to go there ourselves or send someone there. Geographic information systems are a special class of information systems that keep track not only of events.
Forestry companies solve geographic problems when they determine how best to manage forests. Geodemographics consultants solve geographic problems when they assess and recommend where best to site retail outlets. Delivery companies solve geographic problems when they decide the routes and schedules of their vehicles.
The architectural design of a building can present geographic problems. Here are some more examples: Almost everything that happens. If so many problems are geographic. Therefore geographic location is an important attribute of activities. National Park authorities solve geographic problems when they schedule recreational path maintenance and improvement Figure 1. The tools and methods used by a scientist Applications Box 1.
Although science and practical problem solving are often seen as distinct human activities. The use of similar tools and methods right across science and problem solving is part of a shift from the pursuit of curiosity within traditional academic disciplines to solution centered. The use of GIS for both forms of activity certainly reinforces this idea that science and practical problem solving are no longer distinct in their methods. Location was crucial in the immediate aftermath and the emergency response.
September 11 Almost everyone remembers where they were when they learned of the terrorist atrocities in New York on September 11 When geographic data are used to verify the theory of continental drift. Others are better characterized as driven by human curiosity. Both use the most accurate measurement devices.
B telephone outages. Courtesy ESRI. A subway. In the short term. These terms are explored in the context of logistics applications of GIS in Section 2. Other problems that interest geophysicists. Some decisions are operational. But the events also have much wider implications for the handling and management of geographic information. Figures 1. At some points in this book it will be useful to distinguish between applications of GIS that focus on design.
GIS is able to bridge the gap between curiosity-driven science and practical problem-solving. With a single collection of tools. But in order to predict how consumers will respond to new locations it is necessary for retailers to analyze and model the actual patterns of behavior they exhibit. Geographic databases are often transactional see Sections The real world is somewhat more complex than this.
Finding new locations for retailers is an example of a normative application of GIS. Others are strategic. Others are tactical. Some of the best clues to our ancestry come from our family surnames. After all. Other applications are discussed to illustrate particular principles.
But many of the methods used in GIS are also applicable to other nongeographic spaces. In this book we have tended to avoid geospatial. Spatial refers to any space. So the discussion of analysis in this book is of spatial analysis Chapters 14 and Chapter 2 contains a more detailed discussion of the range and remits of GIS applications.
So why has geographic information spawned an entire industry. Part of the answer should be clear already — almost all human Where did your ancestors come from? As individuals. Research at. Similar GIS-based analysis can be used to generalize about Longley Surname Index 0— — 0 50 Goodchild — — — Kilometres — — — Maguire Rhind Source: A 9 This tells us quite a lot about migration. Figure 1. In all kinds of senses. But it is not central to resolving any specific problem within a specific timescale.
Longley Surname Index 0— — — — — Goodchild — — — Kilometres 0 50 Maguire Rhind Source: We use a variety of terms to describe what we know. Hungary activities and decisions involve a geographic component. Nevertheless it is worth trying to come to grips with their various meanings. Data consist of numbers. Raw geographic facts see Box When data are transmitted. Data clearly refers to the most mundane kind of information.
The internal meaning of the data is irrelevant in Figure 1. GIS does a better job of sharing data and information than knowledge. Examples include the knowledge built up during an apprenticeship. It is important to distinguish two types of knowledge: In a narrow sense. Information exists independently. Information is often costly to produce.
It can be considered as information to which value has been added by interpretation based on a particular context. Put simply. Data the noun is the plural of datum are assembled together in a database see Chapter Knowledge does not arise simply from having access to large amounts of information. It is voluminous. Although much geographic information is static. Some have argued that knowledge and information are fundamentally different in at least three important respects: It requires many special methods for its analysis see Chapters 14 and Display of geographic information in the form of a map requires the retrieval of large amounts of data.
It can be time-consuming to analyze. The term information can be used either narrowly or broadly. GIS provides an excellent example of the latter. It may be represented at different levels of spatial resolution. Geographic datasets. Because of its nature. One other characteristic of information is that it is easy to add value to it through processing. How the information is interpreted and used will be different for different readers depending on their previous experience.
Table 1. It may be represented in different ways inside a computer Chapter 3 and how this is done can strongly influence the ease of analysis and the end results. Form varies geographically. Others are Figure 1. It seems best to regard it as a multiplicity of information from different sources. Others are imposed by us.
Evidence is considered a half way house between information and knowledge. These two types of information differ markedly in their degree of generality. The ways in which the burning of fossil fuels affects the atmosphere are essentially the same in China as in Europe. We humans have accumulated a vast storehouse about the world.
Some of those processes are natural and built into the design of the planet. Geographers in particular have witnessed a longstanding debate. But processes can be very general. Knowledge requires much more assimilation — we digest it rather than hold it. Almost invariably. For example.
Major attempts have been made in medicine to extract evidence from a welter of sometimes contradictory sets of information.
Knowledge about how the world works is more valuable than knowledge about how it looks. Wisdom is in a sense the top level of a hierarchy of decision-making infrastructure. More sophisticated forms of knowledge include rule sets — for example. General knowledge comes in many forms. The software of a GIS captures and implements general knowledge.
Rules are used by the US Forest Service. In that sense a GIS resolves the old debate between nomothetic and idiographic camps. Both are essential. To support these efforts.
These maps simply classify land. In many parts of the USA and other countries efforts have been made to limit development of wetlands. Such problems employ methods known as multicriteria decision making MCDM. Ohio Department of Natural Resources. Geospatial Analysis: The three editions of this book published in , and by Troubador, Leicester, UK are hard copy versions of an extensive and detailed technical website, www.
It is broad in its treatment of concepts and methods and representative in terms of the software that people actually use. Ge ographical Information Systems: The updated and abridged Second Edition of Geographical Information Systems brought the definitive reference first published in to a whole new audience in a streamlined format.
The entire work is available in a Chinese edition. Geographic Information Systems and Science second edition. The second edition of the pre-eminent textbook in its field communicates the richness and diversity of GIS in a lucid and accessible format.
This fully revised and updated second edition reinforced the view of GIS as a gateway to science and problem solving, set out the scientific principles that govern its use, and described the impact of people on its development, design, and success.
The book was translated into Chinese and Polish. Advanced Spatial Analysis. Remote Sensing and Urban Analysis. A wide range of methodologies for the production and analysis of urban remote sensing data are outlined in this book. Surface models are considered for the analysis of integrated data sets, in which the scope of the applications is widened to consider the estimation of human population levels. Geographic Information Systems and Science.