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Introduction to GIS for Map Construction

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1 Introduction to GIS for Map Construction
In this lesson you will learn: common raster and vector data exchange formats sources of raster and vector data map construction principles bringing data into the GIS – the map view scaling and projecting the GIS map formatting and outputting the map – the layout view You are now familiar with the basic data needs of GIS, models of spatial data and attribute data, and the mapping capabilities of GIS and related graphic software. While GIS is certainly more than just spatial data and mapping, maps are perhaps the most fundamental building blocks of any GIS project. In this lesson we will begin to explore the process of map construction in a GIS. You will learn: common raster and vector data exchange formats sources of raster and vector data map construction principles the starting point for a GIS project – the map view scaling and projecting the GIS map formatting the GIS map for output – the layout view By the end of this lesson, you will have enough background to begin the process of collecting and organizing available secondary data for a GIS mapping project.

2 Raster data formats Generic raster data exchange formats:
TIFF filename.tif JPEG filename.jpg GIF filename.gif BMP filename.bmp Geographically-registered raster data exchange formats GEOTIFF filename.tif - with “world” file filename.tfw Compressed raster data exchange formats MrSID filename.sid - with geo-reference “world” file filename.sdw Proprietary & specialty formats ERDAS (.lan, .gis, .img) ESRI Grid (.grd) Intergraph (.cot, .cit, .rle) National Image Transfer Format (.ntf) Uncompressed ASCII satellite image (.bsq, .bil, .bip) Raster data, as you will recall, is essentially digital graphic imagery. GIS software supports a variety of generic raster data exchange formats, for inputting and outputting graphics or images. Among the more common of these generic exchange formats are TIFF, JPEG, GIF, and BMP – recognizable by their file suffixes. These exchange formats are also supported by many word processing, spreadsheet, presentation, drawing, and data analysis software packages and can contain anything from digital photographs and illustrations to scanned images. The generic raster data formats are generally poor choices for exchanging GIS data, since there is no explicit geographic reference information associated with the raster data. Two of the more important raster data exchange formats for GIS are GEOTIFF and MrSID. GEOTIFF associates a TIFF image with a secondary file that directs the GIS software where to position the image. This accompanying geographic reference file is often called a “world” file, and is viewable and editable with an ASCII editor, such as Notepad, or standard word processors. The world file simply contains the latitude and longitude, or easting and northing coordinates of the first and last pixels of the image. MrSID files utilize a so-called scalable compression technique to store the raster data information. The creation of MrSID raster files requires proprietary software, but most GIS packages have adopted MrSID as a standard raster data format for inputting images. The unique value of MrSID imagery is that the amount of compressed information used depends on the scale at which the image is displayed, thus saving valuable computer memory for other GIS operations. MrSID raster files can also be geo-referenced with an auxiliary “world” file containing the image coordinate information. The kinds of image processing software necessary to create orthophotos from aerial photographs or viewable images from satellite remote sensing and radar data are substantially more complex and specialized than GIS. Companies that produce such software often protect the intellectual property embedded in their software through proprietary data formats. The set of proprietary and specialty formats listed here is meant to be illustrative and is by no means a complete list of raster imagery file formats.

3 Raster data sources Types of publicly available raster data
map products scanned maps digital maps geospatial imagery aerial photography satellite remote sensing imagery aerial remote sensing imagery non-spatial imagery If you’re starting a GIS mapping project, the first two questions that probably come to mind are: “what types of GIS data can I get?” and “from where?”. The first type of raster data that may be available from public sources is what we’ll call “map products.” These are digital raster images of maps that have already been produced, either through conventional cartographic methods, GIS, CAD, or computer mapping. Printed maps, or map-like images, may be scanned using digital scanners and saved in TIFF, JEPG, GIF, or BMP format. Alternatively, the scanned map may be geo-referenced using GIS or other geospatial software and saved in GEOTIFF or geo-referenced MrSID formats. Some digital maps may be generated directly from GIS, CAD, or mapping software and saved in GEOTIFF or unreferenced raster formats. The second type of public raster data you will encounter is imagery. Panchromatic aerial photography is often used as raster data source for updating GIS spatial data, especially by county and municipal governments. Depending on the demographic history and landscape geography of the region for which you are constructing your GIS map, aerial imagery may be available from as early as the 1930s and 40s. Aerial imagery is generally captured at a fairly large scale. To be useful in GIS or other mapping, the image needs to be rectified to remove lens and platform motion distortion, and ortho-rectified to remove planimetric distortion due to variation in landscape elevation. Ideally, the imagery should also be geo-referenced. Satellite remote sensing data are much smaller in scale, with pixel ground resolutions between 10 and 80 meters. This imagery is planimetric by nature, and usually geo-referenced. Larger scale remote sensing information, such as radar or Lidar, is now collected from aerial platforms. The use of these data typically requires more processing than is available in GIS software, but pre-processed images may be available for purchase. Finally, GIS and other mapping software does not inherently distinguish between a scanned map or aerial photograph and the TIFF image saved in your digital camera. Where appropriate, non-spatial imagery can also be used to create or decorate GIS maps.

4 Raster data sources – imagery
Potential sources of raster data public domain data state-level geospatial data clearinghouses repository public libraries privately-sponsored geospatial data clearinghouses fee licensed data source public agency (NASA, NIMA, USGS, United Nations, etc.) local government source contractor (aerial photography company, land surveyor, etc.) contract data Alright, so how and where do we find these raster data? Unfortunately, there is no master spatial data library somewhere and relatively few Internet search engines specifically catalog data, maps or imagery. So probably the first place to start looking in the public domain is for geospatial data clearinghouses. Most states in the United States have set up geospatial data clearinghouses where public domain data pertaining to their state can be downloaded. The bulk of these data are derived from federal government sources, since agencies like the USGS, NASA, and Census Bureau are charged with mapping and/or collecting imagery and data for the country and sharing those products with the public. Each state should also have at least one federal depository library which receives copies of data or maps produced by these agencies; indeed many major public university libraries are designated as secondary depositories and maintain data and map collections. You will also find public domain spatial data available through geospatial data clearinghouses sponsored by GIS software vendors, trade magazine publishers, and other private organizations. Whether the original geospatial data product was prepared last week or fifty years ago by a public agency, maintaining those data and ensuring their availability is not a costless endeavor. For geospatial imagery especially, expect to pay a small to modest data reproduction or licensing fee. Indeed, if its imagery that you seek, your first point of search should be with the public agency that generated those imagery. NASA and the USGS both participate in imagery archival through the Earth Resources Observation Systems (EROS) Data Center; archived imagery is available there for a modest cost-recovery fee. Your local government may also be willing to share some of its raster GIS data for a modest fee. However, the aerial imagery used by local governments for tax mapping and assessment may actually owned by the company that produced the original imagery. Of course if cost and time are not significant impediments, you could contract with a private vendor for custom imagery or map products. Whatever the source of data, make sure that you read and keep a copy of any and all copyright or licensing agreements.

5 Raster map products: 1. DRGs
Maps and map products produced by the USGS and other civilian agencies of the federal government are generally considered to be public domain, and therefore copyright free. In terms of their content, USGS topographic maps are incredibly rich in both detail and geographic coverage. So why not make these map images available for use in GIS? Well, in fact, they are. Known as Digital Raster Graphics, or DRGs, these scanned maps are produced in GEOTIFF format and available in several different styles from the USGS and state geospatial data clearinghouses. The basic DRG is produced by scanning the paper map at 500 to 1000 dpi in full color. This high resolution scan is then processed to standardize and reduce color variation, and generalized to a final raster resolution of 200 to 300 dpi. The image is then geo-referenced to UTM coordinates using at least 6 UTM tick marks along the outer margin of the map. The image show here is known as a collared-DRG, since the raster graphics file contains the entire map sheet, including the white margins and all text meta-data found on the original map. Collarless DRGs remove the paper map margin and show only the interior of the map. In addition to collared or collarless styles, some geospatial data clearinghouses have converted the geographic reference to NAD-27 latitude and longitude, or NAD-83 latitude and longitude. DRG products are available for 1:24,000 and 1:100,000 USGS topographic maps. DRGs are widely available and, in most cases, free. But before using any secondary data source in a GIS project, you should thoroughly read the meta-data associated with that product and understand its proper uses and limitations. These DRGs were produced from individual paper map sheets, each with its own projection standard lines. Consequently, even if you place two collarless DRGs side-by-side, they may not necessarily align without gaps or overlap. You should also be aware of the history of the original paper topographic map before abstracting any information from it. Can we really trust the contour information, for example, if the map was first produced in 1936 and photo-revised in 1975? What does photo-revised mean? Which map features were revised in 1975 and which were not? What is accuracy standard of information on the original map? The weakest link, the largest source of error in any GIS is its data. Portion of a Digital Raster Graphic, USGS 1:24,000 topographic map; downloaded from the Illinois State Geospatial Data Clearinghouse

6 Raster map products: 2. DOQs
A second type of government-produced raster map product commonly available in the public domain is the digital orthophoto quad, or DOQ. As the name suggests, these are aerial photographs that have been ortho-rectified to remove distortion due to platform motion, the camera lens, and landscape relief. DOQs are produced at a variety of scales, though typically larger in scale than the largest scale DRG. As you can see in this example, large scale DOQs are quite detailed, however features are neither classified nor identified. The cloverleaf structure in the middle bottom of this DOQ suggests that the feature running north-south through the middle of the photo is a limited-access highway. But what are those white elliptical objects just south and west of the cloverleaf … swimming pools?; athletic fields?, apartment buildings? DOQs made available in the public domain are generally geo-referenced and of newer vintage than the largest scale DRG for that area. In order to preserve the planimetric property of the image, digital orthophotos are usually fairly large in scale. This planimetric property also means that neighboring DOQs fit together seamlessly, that is, without gaps, as long as they are referenced to a plane coordinate system – such as State Plane, or UTM. As with any secondary data source, you should be sure to read and understand the meta-data associated with DOQ products, particularly as it identifies the date of the imagery and the geo-reference coordinate system. Lake County, IL DOQ; downloaded from the Illinois State Geospatial Data Clearinghouse

7 Raster map products: 3. DEMs
GTOPO30 DEM raster image of the northeastern portion of North America. Source: Land Processes Distributed Active Archive Center, USGS. Raster map products showing relief or elevation are known as digital elevation models, or DEMs. Larger-scale DEMs are usually produced from the contour information on topographic maps, by grid sampling and interpolation from point data to the raster grid. Small-scale DEMs are generated from smaller-scale topographic maps in similar fashion and therefore are more generalized than the original contour information. Very large scale DEMs can also be produced from GPS or conventional land surveying measurements, or photogrammetrically produced from stereo-pair aerial photography. The raster image shown here is produced on a 30-arc second grid; that is, each pixel in the raster data product has width equivalent of 30 arc seconds of longitude and a height equivalent of 30 arc seconds of latitude. Raw DEM data may also be available in vector format.

8 Raster map products: 4. LU/LC
Sample land use/land cover raster image produced by the USGS Regional Land Cover Characterization Project; derived from early 1990s 30-m Landsat Thematic Mapper data. Source: USGS, Knowing how land is currently being used in relation to the land around it is one of the keys to efficient utilization of land resources and the preservation of vital habitats. Generalized land use/land cover information is often difficult to develop and costly to maintain, especially at large map scales. Fortunately, satellite remote sensing methods have been developed that are capable or producing both large- and small-scale land use/land cover raster data. In addition to the ability to collect these data globally, satellite remote sensing methods also enable rapid and repeated updates to existing land use/land cover information. Here is a sample map representing land use/land cover raster data from the National Land Cover Database produced by the USGS in the mid-1990s from LandSat Thematic Mapper satellite data. The original satellite data resolution of 30-meter pixels is retained in the land use/land cover raster data. Notice the generalized land use/land cover classes specified in the map legend. The complete National Land Cover Data classification system identifies 21 general land cover classes; including perennial ice/snow, shrubland, orchard/vineyard, and fallow which are missing here. The National Land Cover Characterization 2001 database, available in 2006, presents newer data for the entire U.S.

9 Vector data formats Generic spatial data exchange formats
SDTS (spatial data transfer standard) Open GIS de facto standard exchange formats SHP (ESRI) MS-Access Proprietary & specialty formats E00 (ESRI); MAP (MapInfo); MGE (Intergraph) SDE (ESRI) Oracle Spatial The situation with vector spatial data is quite unlike that of raster data. In this case, the data formats are more or less unique to GIS and mapping, because at the infancy of GIS and computer mapping there was no external pressure to create and adopt standard data formats. Again, our purpose here is not to review all of the different vector data formats you may encounter, but to overview the general nature of vector data exchange formats. With the maturing of GIS and geospatial technologies has come greater interest in the development of universal data exchange formats. The first of these, the Spatial Data Transfer Standard, was initiated by mapping agencies of the U.S. federal government as means of ensuring universal access to their spatial data products. The SDTS currently supports five basic data models, referred to as profiles: topological vector data, raster data, transportation network data, point data, and CADD data. Unless your principal activity is the creation and publication of large spatial databases, the technical details of how to create SDTS data is far less important than knowing whether your GIS or mapping software can successfully input SDTS formatted data. A more recent effort at developing data format standards has developed under the aegis of the Open GIS Consortium. The idea of open GIS is that not only will the data be structured in a format that is accessible to all GIS and geospatial software, but that the formats will also be transparent. In other words, the host software won’t have to translate from exchange format to its own data format. Because of their widespread use, two formats have developed into de facto exchange standards for vector data. SHP, or shape files, were developed as the standard for ESRI’s ArcView software, one of the first truly desktop GIS implementations. SHP files are simple vector files; that is, they do not contain topological information. Newer object-oriented implementations of ESRI and Intergraph software have adopted Microsoft Access as the storage medium for spatial data, taking advantage of the power of database software and the extensive use of Access in Windows operating system environments. Finally, as we did with raster formats, we should also recognize proprietary and specialty vector data formats. ESRI’s ArcInfo software generates topological vector data in so-called coverage databases, that are exchangeable in E00 format. Similarly MapInfo software generates MAP format files, and older Intergraph software generates MGE files. For very large GIS files, such as those associated with tax assessment or land parcel data, many institutions prefer server-based software installations with very large and powerful database engines supporting the spatial data. The examples listed here include SDE, a database engine developed by a GIS software company (ESRI), and Oracle Spatial a spatial database engine developed by a database software company (Oracle).

10 Vector map products: 1. DLGs
Sample plot of DLG data showing political boundary (white), hydrography (blue) and transportation (tan) feature classes for Dancyville, TN. Source: USGS, If raster data can be produced from USGS topographic maps, why not vector data? Digital line graphs, or DLGs, are vector data representations of cartographic features derived from USGS topographic maps. Three scales of DLG data are available: large-scale DLG data are derived from 7½ minute topographic maps, 1:100,000 intermediate-scale DLGs from 30-minute by 60-minute topographic maps, and 1:2 million small-scale DLGs from sectional maps of the National Atlas. DLG feature class layers may include PLSS township, range and section lines; political unit boundaries; transportation features; hydrography; contours and spot elevations; survey control points; glacial and geologic features; cultural features; and vegetative cover. Since most of these features are fairly dynamic, it is important to know the vintage of the source map before using DLG data. DLG data are commonly available in Spatial Data Transfer Standard and SHP file formats.

11 Vector map products: 2. SSURGO & NWI
SSURGO soil polygons, from an portion of Marquette County, MI. Image courtesy of Michigan State University Two other sources of vector data derived from map products include SSURGO and NWI. SSURGO, the Soil Survey Geographic Database, is produced by the Natural Resources Conservation Service as a digital follow-up to the traditional county-level soil survey. These spatial data are composed of soil polygon mapping units, each associated with a particular generalized soil type. Spatial data are linked to an attribute database by means of a soil type ID. Like the traditional soil survey, the attribute data of SSURGO focus on the general physical characteristics of the soil, its seasonal hydrological characteristics, and its suitability for crops, vegetation, building construction, and septic systems. Spatial data within SSURGO are derived from maps originally produced at scales between 1:12,000 and 1:63,360 and are generally compiled to county-level geography. The National Wetlands Inventory, or NWI, is produced by the U.S. Fish and Wildlife Service from imagery sources. Similar to SSURGO, the basic geographic unit is a polygon feature – in this case depicting wetlands. Each wetland feature is assigned a generalized ID based on a 4-level hierarchical classification system. NWI vector data are distributed by 7-½ minute quadrangles, at a nominal map scale of 1:250,000. Both SSURGO and the NWI databases are based on the concept of minimal mapping units. That is, even though a persistent wetland may be present at a certain location, if its size is less than the minimal mapping unit it will not be shown in the NWI database. Soil characterizations smaller than the minimal mapping unit are generalized into larger polygons. Also, neither soils nor wetlands typically exhibit nice, neat, crisp boundaries: wetlands fill and recede, and most soil properties transition across space. When used properly, SSURGO and NWI are important spatial data sources for information related to the suitability of land for various types of uses. National Wetlands Inventory data, central Lake County, IL. Map image generated by Wetlands Mapper, a product of the U.S. National Map.

12 Vector map products: 3. TIGER/Line® data
One of the most important and widely-used vector databases was initially created by the U.S. Bureau of the Census to aid in the process of conducting the decennial census and mapping the demographic characteristics of places and regions. In fact, the widespread availability of free Tiger/Line data is as much responsible for the growth of GIS as a mapping and problem solving technology as is the development of desktop GIS software. The word “Tiger” is itself an acronym meaning “Topologically Integrated Geographic Encoding and Referencing.” TIGER was initially designed as a unified geographic source for tabulating census surveys to geographic areas and subsequently referencing data summaries to geographic reporting units – in other words, census blocks, block groups, tracts, and minor civil divisions. According to TIGER technical documentation, “[the] design of the TIGER® database adapts the theories of topology, graph theory, and associated fields of mathematics to provide a disciplined, mathematical description for the geographic structure of the United States and its territories. The topological structure of the TIGER® data base defines the location and relationship of streets, rivers, railroads, and other features to each other and to the numerous geographic entities for which the Census Bureau tabulates data from its censuses and sample surveys.” Though we haven’t yet introduced the concept of topology in relation to spatial data, this inherent property of the Tiger/Line data makes it extremely valuable for the kinds of advanced spatial analyses vital to transportation planning, epidemiology and health care delivery, vehicle routing, environmental impact analysis, facility siting, and thousands of other GIS applications. Nearly all TIGER data have their origins in 1:100,000 and larger-scale topographic maps produced by the USGS. Transportation and hydrological features were scanned by the USGS from the original maps, with topology, attribute information, and administrative boundary polygon information added by the Census Bureau. Updates and corrections to these base data were subsequently undertaken by local governments and Census field staff. However, since TIGER was not designed to be a cartographic or spatial database product, there was no accuracy criterion applied to the placement of updated or new features. So, while TIGER may show an essentially complete set of roads for an urban area, the positions and geometry of individual features won’t necessarily correspond to accurate orthophoto imagery. Tiger/Line data are published at a county-level geography and are commonly available in Spatial Data Transfer Standard and shapefile formats. Railroad, road, and hydrography Tiger/Line® data, DuPage County, IL. Data courtesy of the U.S. Bureau of the Census,

13 Map construction principles
Choose: map geography (content) map scale datum & coordinate system map projection Obtain, consistent with above: source material (maps, imagery, other data) permission to use source material The construction of any GIS project, just like the construction of any map, begins with an overall product design. A good map design include such questions as: what is it that I am trying to accomplish with this map?; who is the audience?; and what is the theme or message I want users to get from the map? Answers to these questions help the cartographer determine the appropriate type and style of map, how much geographic information should be included, and even the overall graphic look of the map. The second step of design involves the map’s content: what geography it will entail?, at what scale?, using what map datum and coordinate system?, on which map projection?. Once these basic design criteria have been resolved, the cartographer can then set about the process of obtaining relevant source material and data, that is either copyright-free or for which copyright permission has been received. With but few exceptions, the same basic considerations are relevant to the construction of maps or any spatial analysis project through GIS. Spatial data need to have the proper geographic extent and contain appropriate feature classes. Any data compiled from map sources retains the same scale limitations as the original map. Remember, it is better to have source material that is larger in scale than the map you are producing than source material that is smaller in scale and more highly generalized. The next criteria are just as critical to good GIS as they are to mapping. Regardless of source, and even if you are compiling the spatial data yourself, all geographic data in a GIS project should have a common datum and ideally utilize a common geographic coordinate system. The universal standard geographic coordinate system is latitude and longitude. But as you know, any geographic coordinate system is tied to the shape of our 3-dimensional earth via horizontal and vertical datums. GIS software may be able to interpret whether a spatial database uses latitude and longitude coordinates, but it cannot automatically determine whether those coordinates are referenced to NAD-27, WGS-84, or any other datum. There are tools available for converting latitude and longitude coordinates from one datum to another, and from geographic coordinates to planar coordinates. But you need to know the datum and coordinate system of the data you are using and make sure that they are converted to a common basis before using them. The final design criterion, map projection, is something that can be controlled within the GIS. However, if any raster data are involved, the GIS project will need to be set to match the raster data projection. These latter two criteria – datum and coordinate system, and raster data projection – are of the utmost importance to sound GIS mapping and analysis. Remember the adage, “garbage in, garbage out.” There’s no better way to ensure that your GIS project is garbage than to ignore the datum, coordinate system, and raster projection of the data that you are using.

14 Assembling the data – the map view
Much as an artist starts with ideas drawn out in a sketchbook before committing paint to canvas or chisel to stone, the graphic portion of a GIS project begins in a preliminary, data composition view -- commonly referred to a the “map view.” While individual GIS software products certainly differ, there is a great deal of commonality among them in terms of the look, structure, and functions of the map view. Let’s take a closer look at the example shown here. The graphic portion of a typical GIS map view has two major components – the “map window” onto which the spatial data are displayed and the table of contents, or legend identifying the data or layers accessible to the software. At the moment, this GIS project has no data; both the table of contents on the left and the large map window on the right are empty. Notice the common software look of pull-down menus and toolbars above the table of contents and map window. Both the content and layout of most toolbars are customizable and indeed various toolbars can be displayed or hidden at any time. Lastly there are two other elements of the typical map view unique to GIS and geospatial software: the geographic locator window and the map scale window. The geographic locator window reports the location of the cursor in the coordinate units assigned to the map view. In the case of this software it is located in the bottom margin and since there are no data in the project, the locator window reports “unknown units.” The map scale window presents exactly what its name suggests – the current scale of the map presented in the map view. Unlike the geographic locator feature of GIS software, the map scale window is usually dynamic. That is, the user can change the scale of the map view by typing a new representative fraction into the scale window; in this software the scale window is located in the first toolbar displayed beneath the pull-down menus at the top of the screen.

15 Assembling the data – the map view
Here’s another example of an empty map view. Compare the pull-down menu structure with the illustration on the previous slide. Notice that the table of contents for this software is referred to as a legend. Can you find the geographic locator and the map scale windows?

16 Add feature class to legend
Map view operations Zoom In Zoom Out Pan Measure distance Add Data Add feature class to legend The map view is essentially a palette for the construction of a map or the execution of some spatial analysis. Typical tools in the map view include operations for the addition and removal of spatial data layers, zoom and pan operations to change the map extent and scale, feature selection and feature information retrieval, distance measurement, and the standard array of save, open, and print functions. Like graphic illustration software, most GIS software include map export functions that allow you to save an image of the map view in BMP, JPEG, GIF, or TIF formats. However, as we shall see shortly, the map view is intended primarily as a “sketch palette” and has limited cartographic tools.

17 Setting map extent and feature scales
Unlike conventional cartography, where geographic features outside the extent of the map are simply deleted, GIS software enables the creation of many different maps from the same spatial data simply by changing the view scale and the location of the focal center of the map within the map view window. In this sense, you can think of the map view window a viewing frame; those portions of the spatial data that fall within the frame are displayed on the screen, whereas all other portions of the spatial data are invisible. Map scale can be changed by zooming in or out, or by entering the desired representative fraction in the map scale window. Map extent can be controlled in two ways. The first, and more time-consuming method is to pan left-right and up-down until the map view contains the desired geographic features. Alternatively, most GIS software allows the user to set a map extent, either by geographic coordinates or by selecting a rectangular region from within a small-scale map view, similar to the way the zoom tool works. From your background in mapping, you know that scale is an important factor in determining the content of the map. Smaller scale maps will generally have less detail than larger scale maps. This cartographic principle is recognized in GIS by its ability to dynamically link the display of individual data layers to map scale. In this example you can see that the legend entry for labels of major cities is displayed only when the map view has a scale somewhere between 1:1,950,000 and 1:500,000. Notice that the Legend Properties window also indicates that the highway marker numbers, major cities, highway interchange, and highway marker feature classes are also dynamically displayed by scale. Different feature classes can be configured to display at different scales. In this GIS project, for example, there are two data layers called “states.” The one at the bottom of the Legend depicts states as filled polygons, but only when the entire United States is displayed in the map view. The second “states” data layer generates the border outline of each state with the interior of the state unfilled. Thus at the scale of the map view shown, the state’s outline is drawn over the top of the counties data layer. The ability to set map extent and scale dependent views is particularly useful for dynamic GIS mapping.

18 Setting the map view projection
Another major design element that can be controlled through the map view window is the map projection. The map view window is a graphic tablet onto which spatial data are displayed. The spatial data may be expressed in geographic or projected coordinates, and in all cases those data are compiled to some specific datum. The graphic tablet of the map view window, on the other hand, operates in planar, screen units – think pixels, if you like. The software already has to convert geographic coordinates of the data into screen coordinates, so why not add the option of displaying those data on alternative map projections? Let’s be careful here! Specifying a projection and/or coordinate system for the map view window does not change the projection, coordinate system, or datum of the source data. But, in order to properly process any spatial data into the projection of the map view window, the software needs to know the coordinate system, projection, and datum of the source data. Here’s an example of the extent of options available for controlling the projection space of the map view window. Notice that this software gives the option of displaying data in the map view on either geographic, projected, or geocentric coordinate bases. The software offers a variety of standard map projections and even the ability to change the origin and standard lines of the map projection. Notice too that the software allows map datum conversions and the ability to view and even alter datum parameters. Because the parameters for the Albers Equal Area projection of the map in the background are designed for smaller-scale maps of North America, the border between Illinois and Wisconsin does not appear to run true east-west. You will often find it necessary to adjust one or more map projection parameters for small- and intermediate-scale maps. But it is generally inadvisable to play with datum parameters.

19 Formatting the map for output – the layout view
Though the map view gives enough tools and functionality to compose a GIS map, set the appropriate geographic extent, projection, and scale, it is not intended for final cartographic production. A second graphic window, commonly called the layout window, serves this purpose. The typical layout window has several unique properties not available within the map view. First, the layout window consists of a scalable template of the output medium. In this example, the default template is set for a printer with an 8½ -by- 11 sheet of paper in portrait mode. The template is scalable to other standard printer and plotter sizes, as well as custom output sizes. The second unique property of the layout window is that it is dynamically linked to the map view window. Any changes made to the content, extent, scale, or projection of the map performed in the map view are automatically updated in the layout map. Third, as the toolbars visible in the example suggest, the layout window has extensive tools and capabilities for drawing, graphic editing, and cartographic production. Let’s take a closer look at the cartographic elements of the layout window.

20 Layout elements As you know, a well constructed map is more than just a set of geographic features. To help the reader to properly use and interpret the map, it should have a title, legend, scale, directional orientation indicator, graticules, frame or neatline, and additional reference information regarding source data, production date, author, and so on. Each of these can be added to the layout map as a graphic element, which can then be edited, moved, rescaled, reformatted, and even deleted. Typically the map itself is entered in the layout window as a composite graphic – meaning that it is repositionable and scalable within the layout, but editable only through the map view. The example above shows a typical layout window with the map formatted for output on a standard printer, in landscape mode. Notice that a legend and map frame have been added, and that the map author is in the process of adding a title.

21 Layout elements Here’s another example of a map being composed in the layout window. The map title is complete and a scale bar and compass rose have been added. Notice in this case that the author has chosen to use a neatline around the map geography rather than a frame encompassing everything. Notice too that a latitude – longitude grid has been added to the final map, with graticule labels attached to the grid itself. The graticule grid, like most of the other cartographic elements in the layout window, is customizable. The map author could have chosen no grid, with graticule tick marks and labels along the edge of the neatline, the same grid with labels along the neatline instead of adjacent to the grid, different grid or graticule spacing, and a variety of other formats for the graticules, scale bar, and north arrow. Or if you’d prefer, the graphics and text editing tools can be used to add custom elements or embellishments to the layout map.

22 Printing the map Standard paper sizes Sheet Size width length units A
8.5 11 inches B 17 C 22 D 34 E 44 A5 14.8 21 centimeters A4 29.7 A3 42 A2 59.4 A1 84.1 A0 118.9 Most of the time you’ll want to print your map to printer, plotter, or other output device attached directly to your computer. Whether your printer or plotter is capable of handling different sizes of paper or not, it’s a good idea to go through page setup in the software and verify the print device, paper size, color handling, and resolution. Here are the dimensions of standard paper sizes used in desktop printers. Of course, you can also specify “custom” page sizes for your output. But in order to avoid print margin cut-off, you should always specify custom sizes smaller than or equal to the actual page dimensions of your printer or plotter.

23 Exporting the map The other option for outputting the final map is to export it to a graphics file format. Typical export formats include BMP, JPEG, and TIFF. If you have other graphics illustration, presentation, publication, or document exchange software installed on you computer, the GIS export function may also give you options for exporting the layout map to one of their standard file formats. If exporting to a raster graphics format, like BMP, JPEG, PDF, or TIFF, you may have to experiment with the resolution and quality settings of the export tool. Higher resolution doesn’t always mean a higher quality end product. Choosing too high of a resolution can introduce false shadowing on line features and make the map image appear unfocused. Remember too that a map file prepared at 300 dpi resolution will be at least four times the size of the file created at 150 dpi resolution. Finally, don’t assume that one resolution and quality setting is best for all types of maps. A map with raster data content will probably require higher resolution settings than one that is just vector data on a plain white background.

24 What you have learned In this lesson you learned: Common file formats for raster data include: BMP, JPEG, GIF, TIFF, GEOTIFF, and MrSID. The world file associated with GEOTIFF or MrSID raster data provide the information necessary to geographically register the raster data. Common file formats for vector data include: SDTS, Open GIS, SHP, and MS-Access. Small- and intermediate-scale geospatial data produced by state and federal government agencies is often available through state sponsored geospatial data clearinghouses, or directly from the agency responsible for producing the data. Some of the types of raster data that are generally available, free, include: DRGs, DOQs, DEMs, and land use/land cover images. Publicly available vector data include: DLGs, SSURGO, NWI, and Tiger/Line data. Scale, projection, datum and coordinate system are just as critical to the choice of spatial data for GIS as they are for conventional mapping. The data used in any GIS project should either be copyright-free, or properly licensed to you for use. GIS maps are assembled, edited, and formatted in the map view window and cartographically rendered for final output in the layout window. The content of the layout window is dynamically linked to the map view, hence all map construction operations, including setting the projection, scale, geographic extent, and feature symbolization, are performed in the map view window. Maps produced in a GIS can be output to printer or plotter devices, or exported and saved as raster graphics files (BMP, JPEG, TIFF, etc.). In this lesson, we’ve taken a bit of a break from the technical side of GIS to discuss how GIS can be used to produce maps. Let’s review what you’ve learned. Common file formats for raster data include: BMP, JPEG, GIF, TIFF, GEOTIFF, and MrSID. GEOTIFF is a geographically-registered raster format, while MrSID is a compressed format. The world files associated with GEOTIFF or MrSID raster data provide the information necessary to geographically register the raster data and are usually viewable or editable. Common file formats for vector data include: the Spatial Data Transfers Standard created by the U.S. Federal Geographic Data Committee, Open GIS, ESRI’s shapefile, and MS-Access. Many other proprietary formats also exist. Small- and intermediate-scale geospatial data produced by state and federal government agencies is often available through state-, or vendor- sponsored geospatial data clearinghouses, directly from the agency responsible for producing the data, or even from local government agencies. Among the types of raster data that are available for public use are: DRGs, DOQs, DEMs, and land use/land cover images. Vector data that are readily available include: DLGs, SSURGO, NWI, and Tiger/Line data. Whenever accessing published geospatial data, be sure that you keep a copy of the data use or copyright agreement and any and all meta-data associated with the raster or vector data file. The considerations for what constitutes appropriate data for a GIS project are similar to those involved in choosing source data for a conventional map. Be sure that you understand and document the scale, projection, datum and coordinate system of your spatial data. The data that you use should either be copyright-free, or properly licensed. GIS maps are assembled, edited, and formatted in the map view window and cartographically rendered for final output in the layout window. The content of the layout window is dynamically linked to the map view, hence all map construction operations, including setting the projection, scale, geographic extent, and feature symbolization, are performed in the map view window. Maps produced in a GIS can be output to printer or plotter devices, or exported and saved as raster graphics files (BMP, JPEG, TIFF, etc.). Don’t expect the printed, plotted or exported map to look exactly like the on-screen map, however. You will often need to experiment with the resolution and image quality settings in the export tool and with feature colors on printed or plotted maps.

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