The introduction of mass printing capabilities led to the last major revolution in cartography. We are now in the midst of the next paradigm shift – from print to online maps. As with printing, the Web has allowed maps to be created, disseminated, and used in ways that are completely different than in the past.

Online maps can play many more roles in communicating an increasing number of types of information. Cartographers can now think of their maps in new and sophisticated ways – the maps can portray much larger geographic extents than a typical computer screen (since readers can pan the display), they can be multi-scale (since readers can zoom), they can be real-time (as data from the source can be streamed to the server), they can be interactive (as readers query map content, change map layers, and more), they can be dynamic (as animations of the data are shown), and they can be communal (in that they are produced by a collective organizations).

Communal maps are composed of data from multiple sources at varying map scales and extents from contributors who best know the content for their local area ("local" not being restricted to only the largest scales). The key advantage of this communal characteristic of online maps is that the data on the maps is then the best available, that is, it's the most authoritative and current. Masses of individual depositors insure that the collective map has relevance and utility and is responsive to the users' needs. The communal composition of the map allows for uniformity of the essential mapped features, symbols, and labels, while local variations can provide for geographically unique features while being incorporated in ways that do not diminish or mask their importance or distinction.

The Web has introduced elements that precipitate the need for cartographers to sometimes radically shift the way they make maps to accommodate efficiencies that readers and users of their maps have available through ubiquitous web browsing functionality. It is no longer feasible to only consider a print map production or dissemination agenda – map readers now expect and even demand a different product and a more robust delivery system. The push-pull relationship between map readers and makers coupled with Web-enabled capabilities for maps has pushed cartography to the brink of its next paradigm shift.

Esri Press is honored to have republished three classic works by notable cartographers of the pre-digital age. The most notable release is Semiology of Graphics by Jacques Bertin (originally published in 1967), a book that presents the first and most comprehensive theoretical foundation to what we today call "Information Visualization". Bertin provides a universally-recognized theory of graphical symbols and modes of graphics representation that allow cartographers to transform geographic information into cartographic communiqués.

Released in Fall 2010, the book includes new information written by Bertin before his death earlier in 2010. It also includes a new forward by the original English translator, William Berg. Even those who have a copy of the original classic will want to see this new content.

That the book has been out of print for some time has been lamented by interested cartographers. That the book has been overlooked by many of today's map makers is lamentable. The newer generation of map makers has not been exposed to the enduring practical guidance on effective map design offered by Bertin. The availability of this reprinted book has the potential to correct some of the gravest mistakes we see in map making today, should Bertin's messages once again be adopted.

Bertin's reprinted work follows earlier releases of two other cartographic classics: Arthur H. Robinson's The Look of Maps (originally published in 1952) and Eduard Imhof's Cartographic Relief Presentation (originally published in 1965). The timelessness of the concepts presented in these books transcends the rapidly changing technology in which the concepts are put into practice. Linchpins in the foundation of modern cartography, they are now available once again to the modern community of professional cartographers, yet they also have a place on the bookshelves of recreational map makers.

This paper seeks not to demonstrate how to perform the techniques of these masters but rather to argue that modern-day map makers should reacquaint themselves with their concepts. For, inarguably, these books have earned and should retain a respected place in map making today. The basics presented in these books will appeal to traditionally trained cartographers, the new generation of neogeographers, and everyone in between who finds himself having or wanting to make maps.

This technical paper describes the design and production considerations for a map illustrating the distribution of Irish surnames. The large-format A0 print document uses classic Irish symbology and themes to create a visually striking representation of historic and numeric data relating to Irish surnames from the 1890 Irish census. The map was designed and produced entirely using Esri® ArcGIS® as an attempt to illustrate the flexibility and quality afforded by modern geographical information systems (GIS) for high quality cartographic design and production without recourse to alternative software.

A software-usability approach was taken by ESRI Switzerland to design and build a cartographic production system for the Swiss Federal Office of Topography (swisstopo). Building on the strengths of ESRI ArcGIS and ArcMap for data management, symbolisation and intuitive cartographic editing, an analysis was made to improve the general editing environment and provide tools specifically for cartographers. This paper discusses how usability tenets were applied in the design of reusable software components used for the production of multiple map products at swisstopo and other sites.

Collecting, processing, and maintaining geographic data for cartographic display are cost- and time-intensive endeavors. While cartographic data is ideally created for a specific or narrow scale range, cartographic demand typically covers a full scale spectrum from neighborhood to globe. Indeed, easy access to the Web has increased demand for multi-scale mapping. To maintain perspective on the effort of generating quality data, automated approaches to generalizing detailed data for display at progressively smaller scales is paramount. Web maps such as Bing Maps, Google Maps, and ArcGIS Online World Streetmap, emphasize the display of roads and streets and ArcGIS Online World Topographic Map includes buildings at the largest scales. A new user-directed solution recently implemented at Esri is designed to generalize road networks and buildings using an optimized approach, working with groups of features contextually to create multi-scale maps for both Web and print output.

Professionally produced map mashups should be as well designed as any professional graphical content available on the Internet. Today many map mashups produced by authoritative organizations or by credentialed professionals are not well designed or even legible. The simple map mash-up of points on a street or image base map usually produces a legible outcome, but map mash-ups adding complex line data, polygon data, or analytical surfaces typically produce indecipherable stacks of graphical content. By strategically designing base map layers to be separate-able to support map mashups, the layering of information in these mash-ups can be sequenced to support legibility. Polygons representing thematic content could be sandwiched between shaded relief on the bottom and then a layer of reference information representing boundaries, names, hydrography, etc. on top. This slightly more sophisticated approach has a much higher potential to result in a new professional quality map, instead of a stack of indecipherable graphical content.

As noted cartographer Professor Waldo Tobler wrote in 1959, "Automation, it would seem, is here to stay." Fifty years ago, Tobler clearly recognized the advantages that automation offers cartography in terms of increased speed and improved quality. Since then, the infrastructure that supports map making has continued to evolve, and we find ourselves regularly seeking the answers to the same basic questions Tobler asked a half century ago: "What possibilities exist for automation in cartography, and where can these be found?" The answers help us improve the map production process so that it requires less time, provides more consistency (and therefore higher quality), and results in reduced costs. But the answers are also constantly changing as hardware capabilities, software functionality, and other technical constraints and opportunities continue to shift and evolve. In this paper, we review the current state of automation in the context of GIS database-driven cartography, and we provide specific examples of situations in which automation can be capitalized upon in map production workflows.

La nouvelle technologie des représentations cartographiques reliées à une base de données – disponible dans ArcGIS depuis quelques années – a beaucoup contribué au fait que les cartes puissent être produites et mises à jour rapidement. L'office fédéral de topographie suisse (swisstopo), qui renouvelle toute sa chaîne de production de carte, développe un nouveau système utilisant la nouvelle technologie des représentations cartographiques. Ce système est constitué de bases de données, d'un système d'édition interactif (Genius-DB), ainsi que d'un système de généralisation automatique (SysDab). Le système Genius-DB est développé en collaboration avec ESRI Suisse, le système Sysdab est développé par une société tierce.

Pour chaque échelle de la carte, un propre modèle cartographique numérique (MCN) est créé. Les MCN sont dérivés d'un modèle topographique du paysage (MTP) et généralisés automatiquement. En outre, des relations entre le MTP non généralisé et les objets généralisés du MCN sont créées. Chaque MCN est constitué d'un modèle de données et d'un modèle de représentations. Afin que le travail des cartographes dans Genius-DB soit aussi productif que possible, une grande partie des tâches cartographiques est automatisée; comme par exemple la création de passages inférieurs et supérieurs. Pour les tâches manuelles restantes, les cartographes disposent d'outils d'édition „one-clic“ intuitifs et efficaces.

Many nations have captured a digital master spatial dataset at a detailed scale, but need to derive smaller scale or lower resolution products. Where this has been attempted in the past, it has usually involved the creation of specialized software, or substantial bespoke development. This paper covers recent industry experience gained in making and assessing research prototypes for generalization in the 1:10K to 1:50K range, on European SDI (Spatial Data Infrastructure) national framework data. The trials involved a commodity industry-standard GIS (ArcGIS from ESRI). As well as making processing workflow models built with the standard geoprocessing tools, the projects involved writing some tailored processes taking advantage of the underlying ArcObjects functionality. Stretching technology further, the projects developed and exercised use cases and constraints for 'Optimizer' functionality currently in the research stage of software development, providing valuable inputs into development strategies for possible future capabilities. The paper summarizes the use cases investigated, the capabilities established, and the lessons learned.

A new cartographic production system is being developed at the Federal Office of Topography in Switzerland (swisstopo). This new system consists of a cartographic database and interactive editing system (called Genius-DB) and a generalization system (called SysDab, built by a non-ESRI third party). Genius-DB is being built by ESRI Switzerland based on ESRI ArcGIS 9.2/9.3, a commercial off the shelf GIS software platform. Genius-DB is one of the first applications to make use of the cartographic representations technology that is new since ArcGIS 9.2. This paper is based on Eicher et al., 2007 and presents some background on this project, explains the driving forces behind upgrading the current system, and describes some selected theory important to the overall architecture of the system. The bulk of the paper explores some major technical themes in the project: the development of GIS data and representation models, designing overall workflows and data flows, and the optimization of the cartographic editing user experience.

This paper is a work in progress. Although not yet complete or polished, it offers gems of advice for such contouring-related topics as: Preparing the digital elevation model (DEM) for contouring, Determining a good contour interval for your map, assigning index contours, cleaning up contours, horizontal and vertical accuracy of contours, assigning depression contours, symbolizing contour lines, and creating supplementary contours and carrying contours. In it, I also present a multi-scale, multi-purpose contour data model. All of these topics are discussed with contour production and management with ArcGIS.

Effective use of GIS for map production requires a well designed cartographic data model. Cartographic data models are a formalization of the map's design stored in the features and attributes of a GIS database. Cartographic data modeling requires a clear understanding of the maps that are being produced and in addition the software that is used to produce the maps.

An advantage of data modeling is that it requires us to think about the map design and the map making process. This results in the codification of the geographic features, attributes and processes that produce the desired cartographic product through specified software. Arranging this information in a systematic form allows it to be shared and repurposed for other map making uses. In some cases, it is possible to translate the cartographer's thinking directly into the GIS data model; other times the requirements for the data model are more elusive because it is difficult to formalize how a cartographer completes certain tasks. There are a number of reasons for this elusiveness, including the iterative and inexact nature of some map making tasks, the lack of attention historically given to codification of some map making tasks, difficulties in translating the task to its expression in a digital environment, and incomplete knowledge of the data and/or software used to complete the tasks.

We have learned much about how to design cartographic databases over the past ten years and more. The lessons relate to translating the map's semantic model into a cartographic data model, informed data capture, database requirements for text placement and symbology, leveraging the database in order to maximize the software capabilities, and identifying opportunities for automated map production. Some of the lessons we have learned include that: the maps an organization produces drive all aspects of cartographic data modeling; a complete inventory of the graphic marks on the maps is required to inform many aspects of the data model; semantic models do not have to be exhaustive in order to be complete; development of the cartographic data model must inform primary data compilation; the data model should allow you to store the closest representation of the final map in the database as possible. We illustrate these lessons through multiple examples from various case studies.

We present continued work on ScaleMaster, a tool that guides and describes multi-scale map design and combinations of databases at widely ranging resolutions. This work complements multi-representation database (MRDB) research ongoing in Europe which is described in our recent paper on this topic (Brewer and Buttenfield 2007). We used U.S. databases, with the most detailed databases compiled by local governments at an anchor scale of 1:5,000. We also tested draft preprocessed Level of Detail (LoD) hydrography databases at resolutions suited to approximately 1:30,000 and 1:80,000 mapping. These data were used to produce maps at all scales ranging from 1:5,000 to 1:1,000,000 (1:5K to 1:1M). The series of draft maps we discuss were designed for reading at the coarse-resolutions of computer screens using ArcGIS 9.2.

Our demonstration maps were produced primarily using selection, elimination, and symbol design changes. Relying on these changes to the display for mapmaking through scale is in contrast to use of geometry changes produced by generalization operations such as simplification and displacement. We have constructed approximately 30 maps for each of four map types: topographic, zoning, soils, and population density. These topics span the range from reference to thematic mapping and include both human and physical themes. All of the maps are of Ada County, Idaho, with detail for Boise and Meridian cities. Jessica Acosta is the primary designer for the map series with feedback from research team members Cindy Brewer, Charlie Frye, Barbara Buttenfield, and Aileen Buckley. Jessica produced maps at scales throughout the 1:5K to 1:1M range for each topic and also documented her work in ScaleMaster diagrams.

Data capture of base cartographic features continues as a major activity in national mapping agencies, regional and local governments, and field science offices. Data modeling to create map products at a single scale and for a single purpose is both costly and labor-intensive. As a consequence, most organizations capture data once with the intention of modifying it for use in multiple products produced for display across a range of mapping scales and for reference, general purpose or special purpose mapping. In ICC member nations, National Mapping Agencies (NMAs) capture topographic data, image data, and base-cartographic vector data at the finest spatial resolution (e.g.,1 meter or sub-meter orthoimagery), for display at standardized mapping scales (e.g., 1;10,000, 1:25,000, 100,000, 250,000, or 1: 1 million), according to the mission and mandate of the agencies, e.g., defense and security, or natural resource management, or archival of natural landforms.

A new map production system is being developed at the Federal Office of Topography in Switzerland (swisstopo). This new system (called OPTINA-LK) consists of a cartographic database and interactive editing system (called Genius-DB) and a generalization system. Genius-DB is being built by ESRI Switzerland based on ESRI ArcGIS 9.2, a commercial off the shelf GIS software platform. Genius-DB is one of the first applications to make use of the cartographic representations technology that is new in ArcGIS 9.2. The paper presents some background on this project, explains the driving forces behind upgrading the current system, and describes some selected theory important to the overall architecture of the system. The bulk of the paper explores some major technical themes in the project: the development of GIS data and representation models, designing overall workflows and data flows, and the optimization of the cartographic editing user experience.

The task of generalization of existing spatial data for cartographic production can be expressed as optimizing both the amount of information to be presented, and the legibility/usability of the final map, while conserving data accuracy, geographic characteristics, and aesthetical quality. This paper provides an overview of a research project underway presently at ESRI to implement an optimization approach to constraint-based generalization within a commodity GIS (ArcGIS). In this approach, a set of rules are defined, one for each constraint. Each rule contains a satisfaction function, measuring the degree of violation of the constraint, and one or more actions which should improve the situation if the constraint is violated. An Optimizer kernel then has the responsibility of evaluating local and global satisfaction, and applying actions to appropriate features to improve the situation. In real generalization scenarios, it is often not possible to avoid some violation of constraints, and the goal of the Optimizer is therefore to maximize the overall satisfaction.

This paper describes the concepts and components needed to achieve optimization, the mathematics of the optimization process, and outlines a research prototype implementation. It also covers mechanisms for conserving topological integrity, which are built into the optimization framework. It then describes a set of example use cases, particularly covering displacement, but also others such as contextual simplification.

Many organizations have adopted a Geographic Information System (GIS) to assist in their demanding projects. At first they were more worried about building the database and getting trained on the use of the GIS software in performing analysis. They were, then, not so much interested in cartography. But, as skills developed, users started asking for more tools on how to improve their maps.

GIS software has introduced and improved several cartographic tools that can help the map maker automate all aspects of cartographic visualization and rendering of the map with minimum of efforts. This has certainly introduced new challenges in cartographic training; where instructor-led as well as Internet courses dedicated to serve the GIS user community were needed to be developed. The concept of a digital cartographic database and how an organization should consider cartography even at the onset of its database design efforts, has certainly introduced an added challenge on how teaching database design with cartography in mind has changed.

The objective of this paper is to introduce those sophisticated tools that will help automate the mapping efforts, to produce quality maps that are worthy of the time spent on complicated analysis, and clearly and impressively visualize the results. A sample of the tools that will be discussed are those to automate labeling and annotation, those to enhance map readability and figure-ground effect, and those to improve the map layout and symbology, to name but few; all in compliance with the international cartographic standards.

Generalization in the digital mapping and GIS world is the task of deriving smaller scale or lower resolution products from over-detailed spatial data. Optimization is one available mechanism for handling the often conflicting constraints involved in contextual generalization, where relationships with neighboring features are paramount. This paper studies the involvement of topological relationships in such constraints, and in the corresponding actions and reflexes which are invoked during optimization. It is based on investigations carried out while researching the development of an optimization engine as an extension to a commodity GIS (ArcGIS from ESRI).

In this article, we suggest that a universally accepted cartographic software program does not currently exist and has never existed, but mapping software capabilities are improving, and cartographers should be involved software developments for map making. We describe the current state of software development and explore what an ideal solution for the future would be. In a related vein, GIS and other data are not generally designed for cartography, but we are learning how they can be, and cartographers should also be involved in the modeling of GIS and other data used for map making.

This paper extends European research on generating cartographic base maps at multiple scales from a single detailed database. Similar to the European work, we emphasize reference maps. In contrast to the Europeans' focus on data generalization, we emphasize changes to the map display, including symbol deign or symbol modification. We also work from databases compiled at multiple resolutions rather than constructing all representations from a single high-resolution database. We report results demonstrating how symbol change combined with selection and elimination of subsets of features can produce maps through almost any range of map scales spanning 1:10,000 to 1:5,000,000. We demonstrate a method of establishing specific map display scales at which symbol modification should be imposed. We present a prototype decision tool called ScaleMaster that can guide multi-scale map design across a small or large range of data resolutions, display scales, and map purposes.

Historical maps have long captivated map readers with their aesthetic qualities and the intrigue they impart, partly because they were done by hand. In this paper, historical maps were examined to determine if they illustrated design techniques and symbology that are adaptable for maps today. If so, the design techniques were then replicated in a modern map making environment using geographic information systems (GIS). With this "history of cartography" approach, we attempt to discover the underlying technical process of creation.

There is a certain class of features on maps that are difficult to generate from traditional GIS databases – named features of the natural landscape. Physical features, such as mountain ranges, canyons, ridges and valleys, and named water bodies, such as capes, bays and coves, are often not found in GIS databases. This results in their omission on maps or at best their addition to the map as graphic type that is not georeferenced to the data used to make the map. This paper describes an inherently multi­scale GIS data model for physiographic features, and by extension named water bodies and named islands and island chains and groups, that can be used to create many different types of maps. The semantic model (what features to include), the representation (how to define the geometry of the features and their attributes), and the symbology (the specifications for both type properties and type placement) are discussed. In addition, the sensitivity of the representations and symbology to the software used for mapping are described. These issues are reviewed in hopes that others will be better able to use GIS data and software to make maps that include these features. Cartographers know that without the inclusion of the type for these names on maps, the products created are less informationally­ and cartographically­rich. If more GIS databases with these features in them were developed, non-cartographers using GIS software to make their maps, as well as cartographers who have not generally had these data at hand, could produce better products.

Keywords: cartographic data modeling, indeterminate boundaries, physiographic features, GIS

Commercial GIS software such as ESRI ArcGIS has historic strengths in geography, spatial data modeling, and data analysis, but has traditionally been perceived as less strong in cartographic representation, artistic freedom and map publishing. However, a set of major software advances in cartographic functionality has recently become available, which together with further developments under way, will greatly automate high quality cartographic production, while empowering the human cartographer.

This paper highlights how the advances arising from research and development at ESRI are applied in a production setting at swisstopo, the Swiss national mapping agency. Using a real world case study as an example, the paper explains how the developments at ESRI meet the various requirements of a mapping agency, from the rigor of a master geodatabase to the artistic freedom provided by the representation editing tools.

This paper extends European research on balancing the cartographic production workload. We emphasize the role of changes to the map display (such as symbol design or modification) in contrast to existing workload discussions that focus on changes to feature geometry. We report results demonstrating how symbol change combined with selection and elimination of subsets of features can produce maps through almost any range of scales. We demonstrate a method of establishing specific map display scales at which symbol modification should be imposed. We present a prototype decision tool called ScaleMaster that can be constructed for multi-scale map design across a small or large range of data resolutions, display scales, and map purposes.

The term "base map" has many specific meanings to a variety of organizations, products, and processes, but in the context of organizations who use GIS and who produce and publish maps, a base map contains the data that underpins all the map products and their common workflows in the organization. This paper describes a management strategy for the elements of a GIS base map that are critical to ensuring that an organization is successful in their map making work. A key to a successful multi-purpose multi-scale base map is a product driven approach. To illustrate this approach a hypothetical example of a local level governmental agency is used to show how the maps an organization will produce are used to inform the database design process. This example is based on real world experience working with many such organizations. This paper also contains discussions of several topics that impact multi-scale, multi-purpose base map data model design such as implications for data capture and deriving data for smaller scale maps. These ensuing discussions provide logical experience-driven basis for making better strategic decisions about base map data modeling.

The convenience of database-driven cartography has traditionally been offset by the design limitations of automated symbology. To address this, ArcGIS 9.2 introduces a rule-based way to store cartographic symbology alongside spatial data within a geodatabase. Symbology is applied intelligently to spatial features through powerful representation rules to achieve complex depictions. Geometric effects within rules can dynamically alter spatial geometry before symbology is applied, and values within the feature class table can define symbol properties to customize the appearance of features. The new framework offers geoprocessing tools that can automate aspects of symbolization and detect areas where symbols overlap even when the spatial geometry does not. The intelligent combination of components of the representation framework can result in intricate and insightful database cartography. This paper investigates the potential of the representation framework by building and describing a set of representation rules and geoprocessing models that experiment with traditional cartographic depictions that have proven difficult to automate in the past.

While research is underway at ESRI on solutions for adaptive and contextual generalization, the development of bulk generalization tools under the geoprocessing framework in ArcGIS has continued. One of the essential design aspects is to extend and redefine the scope of automation. Another is how to support the evaluation and further optimization of the output.

It is obviously important to use the most effective approaches and techniques to maximize the automation, so the new tools take advantage of the topology functions and TIN functions available in ArcGIS to preserve shared geometry and to derive generalized features. It is equally important that the tools provide feedback about the quality of the automated output, together with hints and tips to support further processing to complete the generalization tasks and hence increase productivity.

This paper introduces the existing and upcoming generalization tools, discusses major design decisions, and illustrates how these tools, along with other geoprocessing tools, can be used in various scenarios for model generalization and for cartographic generalization. It covers how the data can be generalized, but also the inspection and follow-up processes.

The demand for operable Multi-Resolution Databases (MRDBs) has grown to the point of wide acceptance in most national mapping agencies (NMAs), and in many local and state government organizations concerned with modeling and mapping cartographic data at different scales. The procedures that support MRDBs involve acquiring topographic data, image data, and base-cartographic vector data at a very fine spatial resolution. The initial dataset forms the basis for deriving coarser resolution versions of the dataset, through data modeling (i.e., generalization and other geoprocessing operations). A large body of work has been published (largely but not exclusively by European researchers) describing obstacles to, and solutions for, automating various aspects of the generalization required for MRDB derivation. That work is well known among the participants of this ICA Generalization Commission workshop and will not be reviewed here.

The convenience of database-driven cartography has traditionally been offset by the design limitations of automated symbology. To address this, ArcGIS 9.2 introduces a rule-based way to store cartographic symbology alongside spatial data within a geodatabase. Symbology is applied intelligently to spatial features through powerful representation rules to achieve complex depictions. Geometric effects within rules can dynamically alter spatial geometry before symbology is applied, and values within the feature class table can define symbol properties to customize the appearance of features. The new framework offers geoprocessing tools that can automate aspects of symbolization and detect areas where symbols overlap even when the spatial geometry does not. The intelligent combination of components of the representation framework can result in intricate and insightful database cartography. This paper investigates the potential of the representation framework by building and describing a set of representation rules and geoprocessing models that experiment with traditional cartographic depictions that have proven difficult to automate in the past.

Automated label or text placement has made great strides in recent years particularly with respect to labeling point and line features. However, the same cannot be said for polygons. One of the main difficulties is determining whether the text should be inside or outside the polygon's perimeter and whether the text should follow the general trend of the polygon or just flow horizontally within the polygon. The problem is relatively easy to solve when the polygon is substantially larger than the text, or if the text is substantially larger than the polygon. However, for many natural features such as smaller lakes, rivers, canyons, valleys, ridges, or mountain ranges, the text will occupy an area that is not substantially larger or smaller. Also, many of these kinds of features are not simple shapes, but instead have prongs, blobs, or bottlenecks; or are simply splotchy. Each of these kinds of shapes should be approached differently when it comes to cartographic text placement. This article describes a methodology for automatically describing such shapes in order to have Maplex, ESRI's cartographic label placement extension automatically place their names on a map.

There is a certain class of features on maps that are difficult to generate from traditional GIS databases – named features of the natural landscape. Physical features, such as mountain ranges, canyons, ridges and valleys, and named water bodies, such as capes, bays and coves, are often not found in GIS databases. This results in their omission on maps or at best their addition to the map as graphic type that is not georeferenced to the data used to make the map. This paper describes an inherently multi-scale GIS data model for physiographic features, and by extension named water bodies and named islands and island chains and groups, that can be used to create many different types of maps. The semantic model (what features to include), the representation (how to define the geometry of the features and their attributes), and the symbology (the specifications for both type properties and type placement) are discussed. In addition, the sensitivity of the representations and symbology to the software used for mapping are described. These issues are reviewed in hopes that others will be better able to use GIS data and software to make maps that include these features. Cartographers know that without the inclusion of the type for these names on maps, the products created are less informationally­ and cartographically­rich. If more GIS databases with these features in them were developed, non­cartographers using GIS software to make their maps, as well as cartographers who have not generally had these data at hand, could produce better products.

Keywords: cartographic data modeling, indeterminate boundaries, physiographic features, GIS

Cartography has been defined as the art, science, technology, and craft of making maps and is a discipline going back 30,000 years to cave paintings locating woolly mammoths. Maps have often been works of art, but also visualize the results of scientific and historical analysis. There is a large bank of accumulated cartographic wisdom describing how to make clear maps that convey the intended message.

From a cartographic perspective, GIS has great strengths in database-driven symbology, multipurpose mapping, and integrated query and analysis, but map publishers also need rich graphical representation and artistic freedom. So, a set of major software advances in cartographic functionality is under way for ArcGIS 9.2 that will facilitate and automate high-quality cartographic production while empowering the human cartographer with more creative flexibility.

The aim of this update is to provide the optimal tools and environment for the production cartographer, centered on the rigor of the geodatabase. A key aspect is to automate as much as possible but then allow cartographic freedom where needed. The system will release mapmakers from repetitive manual operations and free them to concentrate on applying their unique human visual abilities for design and interpretation.

It is a strategic goal of many national mapping agencies and other geographic data producers to build a master Digital Landscape Model (DLM) using a GIS, from which are derived coarser landscape models and corresponding cartographic products at a variety of scales. At the heart of such a production strategy lie the concepts of generalization (the abstraction of data to a smaller scale), and of multiple representation databases. This paper overviews a project underway at ESRI to implement multiple representations in the geodatabase, together with mechanisms for overriding and editing individual feature representations, for high-quality cartography. It then relates that to ongoing development to support efficient generalization processes and a robust framework for data derivation and abstraction.

ESRI is developing its GIS software to support cartographic representations inside a versioned geodatabase. Representations are usually described as a Digital Cartographic Model (DCM), as opposed to a Digital Landscape Model (DLM). A set of tools (including generalization operators) is involved in deriving the DCM from the DLM. One of the main benefits of the DCM representation mechanism is to support manual overrides, because there will always need to be human interventions. Thus, real cartographic data require a combination of automated and human work.

This paper covers the propagation of DLM updates to the DCM features and representations. The first challenge is to apply the same set of derivation rules using just update descriptions as input, instead of a whole new dataset. The second challenge is to prevent erasing the manual work of the cartographer, which represents much of the time spent to produce the final map. The paper describes how the database model is extended to keep track of the cartographer's manual work.

Remaining in the GIS environment during map production has many advantages but requires that an increasing range of cartographic effects and graphic design tools be embedded in the software. For example, cartographers want to position and curve type precisely; break lines for type over multicolor backgrounds with selective masking; clarify precise overpass, underpass, and merge relationships in complex road interchanges; control the way boundary lines interact as they intersect and overlay each other and hydrography; and design sophisticated mixtures of relief shading and hypsometric tints. The tools for accomplishing advanced cartographic effects are a mix of both analysis and representation tools. We challenged groups of students at the Pennsylvania State University with a series of compact design problems to be solved in both ESRI ArcGIS and Adobe Illustrator or Photoshop. In this paper, we highlight some new and hard to find cartographic options in the GIS software.

We present an information model that describes maps and informs the definition of GIS databases with the codification of map design to support automated map production. We present an approach to database modeling that considers the map production requirements from the outset, then defines the unique characteristics and requirements for the GIS data to support mapping, as well as the process models to create the maps. Our information model is derived from a communication model that encompasses traditional cartographic design and production processes to transform information about the geographic environment to geospatial data to maps. We tested our information model using a multi-scale GIS database to produce various map products. From our research, we find that the information model can be used to codify the map design and support the production process. The challenge remains to incorporate the flexibility to reflect the individualistic approaches of map makers in their design and compilation processes.

Though cartographic production based on geographic information systems has proven benefits, a major obstacle to the wide acceptance of GIS as a tool for production cartography has been its inflexibility in allowing cartographers to make changes to the representations of geographic features on a feature by feature basis. Consequently, many cartographers work either solely in a vector commercial graphics software package, or they divide their work between GIS and graphics software packages.

Software is being developed at ESRI based on the geodatabase to support map finishing in ArcGIS. Cartographer-centric tools allow users to modify feature symbolization and geometry. These tools work with the geodatabase and store changes as overrides that do not affect the underlying GIS data. This paper describes the cartographic finishing software under development at ESRI, with a focus on the design and function of manual cartographic editing tools, supplemented by tools for automating common processes.

Commercial GIS software such as ESRI ArcGIS has historic strengths in geography, spatial data modeling, and data analysis, but has traditionally been perceived as less strong in cartographic representation, artistic freedom and map publishing. However, a set of major software advances in cartographic functionality has recently become available, which together with further developments under way, will greatly automate high quality cartographic production, while empowering the human cartographer.

This paper overviews a related set of technology advances arising from research and development at ESRI. The aim is to provide the optimal tools and environment for the production cartographer, centered on the rigor of the master geodatabase but allowing artistic freedom where needed. It will release cartographers from the drudgery of repetitive actions and free them to concentrate on applying their unique human visual abilities for interpretation and design.

Many national mapping agencies (NMAs) are pursuing the idea of building a master database and deriving multiple scale products from it. To support this production goal, GIS-based generalization is a necessity. The solution for generalization involves data modeling, process automation, multiple representations, updating, and more. This paper focuses on the automation of generalization processes in ArcGIS (the GIS software created by ESRI, Inc.)

To automate generalization requires translating the cartographer's knowledge into computer logic and algorithms in order to derive desired results. Our starting point is the Generalization toolset in ArcToolbox, the powerful geoprocessing framework containing hundreds of data analysis and management tools and a ModelBuilder for process chaining. Existing and forthcoming tools along with on-going research cases will be used to illustrate the automation challenges, such as defining rules, recognizing certain patterns and contexts, and producing topologically correct output with feedback for evaluation and post-processing. Sample generalization models will also be presented.

On-demand projection of large raster datasets is becoming increasingly important as the growing interest in utilizing regional and global raster datasets as well as the use of terabyte-sized high-resolution images in GIS, and these raster datasets are normally not stored in the same projection/coordinate system. Current available algorithms do not meet the fast and accurate requirements of the on-demand raster projection. This paper presents a new algorithm based on a bilinear approximation mesh for transforming images from one projection to another. Implementation and tests show that the algorithm is accurate and fast and has built a solid foundation for GIS applications utilizing large image holdings of local or global raster data.

ArcGIS is professional Geographic Information Systems (GIS) software produced by Environmental Systems Research Institute (ESRI), Inc. of the United States of America. This software facilitates map design by giving users the ability to easily layout maps for printing, embedding in other documents, or electronic publishing.

This paper explores a sample of the different tools available in ArcGIS 9 for the purpose of creating professional maps. These tools are not only present as interactive cartographic tools in ArcMap but also as geoprocessing tools in ArcToolbox that can be utilized for automation of cartographic enhancement.

Some examples of what can be done include using geoprocessing tools to enhance the visibility of contour labels or the non ambiguous display of overlapping linear symbology; using tools, which were originally designed for analysis tasks, to enhance the figure-ground of the land-water masses; creating generalized renditions of features for use in smaller scale maps; processing raster data in ArcMap, ArcToolbox, and the Spatial Analyst extension to provide cartographically suitable three-dimensional (3D) background for the map to enhance visualization of the terrain; and tools for labeling and annotation, including the use of both the Standard and the Maplex label engines.

The introduction of new capabilities for multiple cartographic representations and overrides within a GIS database opens up alternative approaches to cartographic production. Many cartographic production organizations have expressed a strategy of building a Digital Landscape Model (DLM) in a central database, and from that deriving a range of cartographic products. To do this efficiently will require generalization tools and mechanisms for handling the Digital Cartographic Models (DCM) including multiple representations. It will also require a framework for controlling the flow of data from DLM to DCM, including updates.

This paper provides an update on a project presently underway at ESRI to implement high-quality cartography with multiple representations in the database, including override mechanisms that empower the cartographer to modify individual feature representations without affecting the master DLM data. It then relates that to ongoing development to provide efficient generalization processes and a robust framework for such DLM/DCM data derivation.

This paper presents an information model that describes maps and informs the definition of GIS databases to support automated map production. When GIS databases are constructed primarily for the inventory and analysis of geographic phenomena, the data requirements for map production are often not considered until after the data have been already been compiled. The resulting maps and production processes are therefore often approached by cobbling together the map data from any available GIS database. We present an alternative approach that considers the map requirements from the outset, then define the unique characteristics and requirements for the GIS data to support mapping, as well as the process models to create the maps. Our information model is derived from a communication model that encompasses traditional cartographic design and production processes to transform information about the geographic environment to geospatial data to maps. It defines rules for cartographic abstraction, symbology and labeling, graphic refinements (e.g., legibility, visual contrast, hierarchical organization, visual balance), and map compilation. We tested our information model using a multi-scale GIS database to produce various map products. From our research, we find that the information model must be flexible so as to reflect the individualistic approaches of map makers in their design and compilation processes.

The demand for a single, detailed cartographic database that supports map representations at multiple scales and for multiple purposes continues to challenge the discipline. Throughout the database life cycle, derived representations intermix with original compilation, making it difficult to distinguish data capture from data abstraction. As a consequence, database features that persist across compilation scales may vary in geometry, dimensionality, and singularity. Currently, most GIS and map production systems offer only minimal software support for linked multi-scale data management. Linkages between complex data representations can be established only on simple attributes (e.g., object IDs or timestamps). This paper presents relational database architecture to link representations and unify mapping at multiple scales and for multiple purposes. The architecture is being developed by empirical investigation and comparison of existing federal agency map series databases, and by systematic experimentation with cartographic abstraction and generalization applied to these data. Current work involves DLG and DIGEST data dictionaries for geographical footprints in Texas and in California. The separation of captured and derived data follows European work practice that captures data within Digital Landscape Models (DLM), and derives data from the DLM to a series of Digital Cartographic Model (DCM) databases for targeted scales and purposes.

Geographic information systems centered on relational databases are a powerful and proven way to collect, store, and analyze geographic data. Such systems are also used to produce cartographic products including maps and mapping datasets. However, existing mapping systems built on GIS databases fail to fully leverage relational database technology, mainly because most systems store geographic information – geometry and attributes – in the relational database, but store map definition and symbolization information in separate files. Also, map symbolization is accomplished by applying rules that assign symbology to sets of categorized features, a system that is seen by many cartographers as being too restrictive in not allowing one to interactively change individual cartographic graphic representations.

This paper proposes a GIS-based cartographic production system where cartographic information is stored with GIS data in the relational database. A system whereby dynamic cartographic symbolization and geometry processing rules are stored in ESRI's geodatabase is described. The representation of features is achieved initially by applying these sets of rules without manual intervention. The system then affords the cartographer the freedom to intervene and override any representation. Such overrides can take the form of changes to symbolization as well as geometry.

There are many ways to encapsulate semantic models in GIS and cartographic data. A semantic model is the set of terms used to describe features in the database or on a map. For instance, a semantic model defines whether a low lying saturated area on the landscape is called a swamp, marsh or bog. In order to make maps with GIS data, some part of the GIS data model must contain the data's semantic model so a mapmaker can symbolize the data for the map.

Valid Value Tables (VVTs) are a set of tables that may be used to store a semantic model in a geodatabase by defining the valid combinations of coded values that describe the kinds of features in the database. Coded values are numbers (requiring relatively small amounts of storage space in a database and low impact on digital networks) that represent larger, more descriptive, but inefficient text strings. Drawing data on maps in a GIS is faster when coded values are used to determine which symbols are used to draw features.

Base maps require a data model that supports the generation of high-quality digital cartographic products with varying levels of detail for a desired range of map scales. Base maps provide a framework for GIS data use and analysis, and commonly used GIS data from many domains may be combined with cartographic attributes to build the base map. This chapter presents a case study for a topographic base map at 1:24,000 scale, building on work in progress at TNRIS, based in Austin, Texas.

The original Atlas of Oregon was printed in 1976 and served as a definitive source of geographic information for the state of Oregon for 25 years. The second edition was released in October 2001, and a CD-ROM version was released a year later. A Web site has also been developed to deliver a set of educational materials that draw upon the atlas. Presentation of the atlas using multiple modes of communication creates a suite of integrated materials that can be used for a wide range of applications, including reference, education, research and policy making. In the twenty-five years that span the release of the first and second editions of the atlas, we have seen radical changes in the ways that atlases are produced and distributed. Technological changes have impacted all aspects of the atlas creation process, including atlas design, data collection, map compilation, media production, media distribution, and even communication between collaborators. This paper reviews the methods used for creation of the original Atlas of Oregon, and contrasts those with the techniques that were used to create the Second Edition. We also examine technological changes that have allowed for new mapping opportunities by expanding the modes of delivery to include CD ROMs and the Web. Each of these modes of communication presents a unique set of challenges and advantages for atlas mapping. Books continue to provide the highest quality graphics and a level of comfort that entices many readers, CD-ROMs and the Web allow for increased interactivity and animation, and the Web can also provide related services, such as hyperlinks to data sources and downloading capabilities. This paper examines modern techniques for atlas creation in each of these forms - book, CD-ROM and Web site. The atlas design, compilation, and production methods used for each of these three distribution modes are examined, and challenges for each are discussed. Distribution of the atlas using multiple modes of communication provides the opportunity to impart a wider range of information, creates more opportunities for effective communication, and may attract a larger audience; however, integration between these modes presents a set of challenges, and opportunities, unto itself. These are also discussed in this paper.

Many cartographic production organizations have a strategy of building a Digital Landscape Model (DLM) in a central database, and from that deriving a range of cartographic products. However, in the past, the cartographic presentation tools and symbolization mechanisms available in the GIS software that is used to build and maintain the DLM, have not provided the cartographic quality or the human freedom to produce directly the desired cartographic outputs. As a result, many organizations have had to fall back onto a divided workflow, where the cartographic finishing stages are done in publishing software dissociated from the central database.

This paper describes the rationale, scope, and technology of a project underway at present at ESRI to implement high-quality cartography with multiple representations in the database, including override mechanisms to empower the human cartographer to modify individual features and representation parts without affecting the master DLM data, and without unnecessary data duplication. This project is part of an ongoing strategic direction to deliver database-driven cartography capable of satisfying the demanding requirements of cartographic production organizations.

In a world overrun with information and consumers of digital information expect technology to make raw data presentable in seconds and finished content in hours. In this context, mapmakers are behind the times. The content and the processes for making commercially viable and government mandated maps are complex and must address using terabytes of imagery and detailed spatial data. Currently, many such maps require large amounts of budget-draining human attention to complete. Of the software that is prevalently used for making maps, none is capable of rapidly producing these maps. Rapidly, in this instance is not relative to how fast these maps were made ten and fifty years ago, but rather rapidly relative to how other vast quantities of data are processed in databases and by production software. For instance, the databases behind the world's banks and stock exchanges are capable of and are now expected to perform complex tasks on demand. In fairness to mapmakers, the irresistible forces of market-driven economies drove the speed and maturity of these financial databases and software systems. Thus, this paper's purpose is to describe an evolution in the maturity of the databases and software systems for mapmaking.

Atlases are changing. The paper paradigm of maps and atlases has pervaded recent cartographic history. By nature that paradigm serves, as well as defines, a specific audience in terms of use and presentation. In the lab and at the printing press, the paper paradigm demands certain design and production flows that will drastically change through evolutions in data structures, mapmaking techniques, and presentation methods. Technological transformations in mapping influence much of this change. The implications for the creation and distribution of atlases are significant. With that in mind, this paper addresses a number of issues that relate to the technological evolution of atlases from paper to digital products: the distinction between paper and digital products and services and the implications of that distinction for atlas design – particularly for web-based services; facilitating data and its application to the evolution of map/atlas products; and a redefinition of "atlas" and the "audience" for an atlas.

GIS databases contain classes of features that are representations of real world phenomena; and GIS and mapping software provide a means for encapsulating that information within a map. Typically ancillary cartographic information like legends, scale bars, graticules, text, etc. have been stored outside of the database within documents or as instructions in a program that reconstructs the map each time it is needed. As more mapping agencies and organizations move in the direction of centralized data holdings, the decentralized nature of traditional cartography will cause inconvenient management constraints. ESRI has spent the last year developing technology for storing this cartographic information within a traditional centralized DBMS structure. This allows cartographic information to be managed far more effectively than current methods permit. One of the chief values of this technology is the ability to keep cartographic products constantly up to date, i.e., each time a map is produced the most current information is used. This technology also allows for changes to the cartographic standard to be instantly applied to all products that use the standard. Another way to describe this topic is making the leap from database-derived cartographic information (passive) to database-driven cartographic information (active).

GIS databases contain classes of features that are representations of real world phenomena; and GIS and mapping software provide a means for encapsulating that information within a map. Typically ancillary cartographic information like legends, scale bars, graticules, text, etc. have been stored outside of the database within documents or as instructions in a program that reconstructs the map each time it is needed. As more mapping agencies and organizations move in the direction of centralized data holdings, the decentralized nature of traditional cartography will cause inconvenient management constraints. ESRI has spent the last year developing technology for storing this cartographic information within a traditional centralized DBMS structure. This allows cartographic information to be managed far more effectively than current methods permit. One of the chief values of this technology is the ability to keep cartographic products constantly up to date, i.e., each time a map is produced the most current information is used. This technology also allows for changes to the cartographic standard to be instantly applied to all products that use the standard. Another way to describe this topic is making the leap from database-derived cartographic information (passive) to database-driven cartographic information (active).

The union of cartography and GIS has not always been one of complete cohesion. Designing GIS databases has frequently left mapmakers with a difficult job and mapmakers have no consistent means for communicating cartographic requirements to database designers. Today there is a widely held expectation that GIS means maps, this is partly because maps or things that look like maps are easy to make using GIS software. Many organizations also expect to use their GIS data holdings in multiple mapping and analytical contexts. This article presents key concepts that show that GIS databases can be designed such that they facilitate rapid production of many high-quality cartographic products. At the heart of these concepts is the idea that standard database modeling practices can yield well designed GIS databases that support cartographic purposes as well. This article presents these ideas based on work completed at ESRI over the past two years on how to include cartographic information in a GIS data model to support creating a 1:24,000-scale base map.

Application of landscape textures can add life and realism to cartographic visualizations and presentations. "Bump mapping" is a term used in 3D graphic programs to refer to perturbating an object's surface with textures and patterns. These perturbations or "bumps" add tremendous realism to the object and to the visualization. This same principle can be applied in a GIS setting to add realism and interest to the presentation. Arcview Spatial Analyst can be an effective tool for this process. This presentation will illustrate how to use ArcView Spatial Analyst to create interesting and realistic textures for characterizing different landscape types for purposes of visualization. At least one case study will be demonstrated.

The first part of this article discusses some of the basics of terrain representation using ArcMap. The last part goes into a little more detail about how to achieve a Swiss-style hill-shade effect using the Spatial Analyst extension.

Most organizations need to use iconic symbols of some sort in their documents and maps. These icons may be a widely used standard like the Visa or MasterCard symbols or something custom like an organization's logo. Using these symbols in documents and presentations has often been a problem because the only way to do so was to scan the symbol and use it as a bitmap. Bitmap images offer a trade-off, quality at the expense of performance. For presentations bitmap images are particularly bad because they are often displayed at large sizes and are usually perceived to be of low quality. It is also difficult to publish documents that contain bitmaps due to large file sizes or incompatibilities in the bitmap formats.

Shaded or "painted" relief backdrops add tremendous visual interest and value to cartographic products. The addition of relief backdrops to maps has proven to be an effective technique for portraying realistic landscapes and geographical situations, and it is widely practiced in cartography today. However, the beautifully smoothed and colored shaded relief surfaces commonly seen as "backdrops" on many maps often do not reveal the true character of the ground being shown. By enhancing painted or shaded relief with textures and materials, more realistic information can be displayed. This provides map users with a better sense of the geographical situation present in the map. The information required to develop these geographic textures and materials can be derived from a number of widely available digital sources including digital aerial photography, satellite imagery and other GIS thematic data. Incorporation of this additional information is desirable and possible while still maintaining visual balance and readability. This presentation will discuss the concepts and philosophy behind the use of "geographic textures and materials". It will also provide a step-by-step application example showing how landscape-based textures and materials can be applied to cartographic backdrops using ArcGIS to create a dramatic, interesting, and informational cartographic presentation.

Combining layer tinting or "painting" with relief shading has proven to be a very effective method for portraying the landscape. Additionally, the "painted relief" is important in providing a backdrop for maps designed for land management and resource planning at the Bureau of Land Management's Oregon State Office. This article introduces a technique that gives cartographers a new capability of adding visual texture to maps, by combining layer tinted relief with a modified Digital Elevation Model (DEM) using SPOT or Thematic Mapper imagery or Digital Ortho-photography. This texturizing method has greatly enhanced the "painted" relief maps in communicating detailed landcover features. The result is not only more informative, but also very visually exciting because of the tactile appearance. This technique has been particularly useful in showing patterns of recent forest management activities in the Northwest. The techniques described here specifically uses ESRI Arc/Info software, but the general methodology could be applied using other mapping software.