Paul Hardy

This paper summarizes some of the key architectural elements and reviews some of the results of the AGENT project, a research project funded by the European Commission between 12/1997 and 11/2000 as part of the Esprit Programme. The project involved five partners and ...

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.

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 gene...

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.

The stated aim of many national mapping agencies (NMAs) is to build a master large-scale digital landscape model (DLM), from which medium- or small-scale DLMs are to be derived. The digital cartographic models (DCMs) and subsequent cartographic products are then compiled from the corresponding DLMs. Generalization is at the heart of such a production strategy. Meeting the challenge of integrating comprehensive generalization capabilities into ArcGIS (ESRI’s core GIS software product family) to fully support the aims of NMAs requires more research focused on advanced and comprehensive solutions, while the development of fundamental generalization tools continues. Generalization is about representing the geographic reality as faithfully as possible under map scale restrictions. Although automated tools have been developed to perform specific steps of generalization, such as aggregation of polygons or simplification of lines, it is obvious that post-inspections and corrections would be...

Abstract. 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.

The stated aim of many national mapping agencies (NMAs) is to build a master large-scale digital landscape model (DLM), from which medium- or small-scale DLMs are to be derived. The digital cartographic models (DCMs) and subsequent cartographic products are then compiled from the corresponding DLMs. Generalization is at the heart of such a production strategy. Meeting the challenge of integrating comprehensive generalization capabilities into ArcGIS (ESRI’s core GIS software product family) to fully support the aims of NMAs requires more research focused on advanced and comprehensive solutions, while the development of fundamental generalization tools continues. Generalization is about representing the geographic reality as faithfully as possible under map scale restrictions. Although automated tools have been developed to perform specific steps of generalization, such as aggregation of polygons or simplification of lines, it is obvious that post-inspections and corrections would be...

Many national mapping agencies (NMAs) are pursuing the idea of building a master database and deriving multiplescale 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 ...

Over the past few years, many national and regional mapping agencies have built a basic scale dataset covering their territory, often now referred to as ‘framework’ data. At the same time, there have been increasing requirements for rapid creation of multiple products at different scales and specifications, combined with great pressures to cut costs and reduce staffing. These conflicting requirements have given a real incentive to use automated generalisation. However, production-quality, intelligent tools for contextual generalisation have been scarce or unavailable. The advantages of object data modelling, active object toolkits and software agents have been proven by research projects, and by successful deployments of prototypes in production flowlines at national mapping agencies. Work is now underway, guided by the MAGNET consortium to develop a new production-ready object generalisation environment (Clarity). This is developed from the AGENT prototype, but building on experien...

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 gene...

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).

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, al...

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, which 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 highquality 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, an...

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.

Major mapping organisations are moving to a new production paradigm centred on building and maintaining (often using remote-sensed sources) a master database modelling the real world. From this database are then produced multiple maps, charts, geospatial data, and on-demand spatial visualisations such as Internet web mapping. This paper overviews the multi-scale, multi-product capabilities of a modern production application built on an objectoriented geospatial database. It specifically highlights its capabilities for dynamic representation dependent on scale, storage of multiple geometry per object, and automated generalisation, in order to explore the benefits and future directions of active object mapping in a multi-product context. Active generalisation methods rely on message passing to objects to ask them to simplify or displace themselves. Dynamic representation implemented as active object display behaviours allows individual objects to draw themselves differently according ...

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 develo...

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.

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, al...

ABSTRACT Photogrammetric feature extraction has been seen previously as a standalone activity, feeding into GIS and mapping systems. This traditional view is now challenged by the availability of new environments,which bring together the previously separate disciplines of photogrammetr y, object data modelling and cartography to produce a unified flowline for production of maps, charts, and geospatial data. This paper overviews,the capabilities of a modern,stereo photogrammetric,workstation and of a map,production application built on an object-oriented geospatial database, in order to explore the synergy arising from the close interfacing of the two. The logic and technology of the integration are discussed, and the merits of combining photogrammetry with active objects are assessed both for initial geodata capture and for subsequent map,update.

The recent availability of object-oriented database technology opens up new possibilities for map and chart representation, on paper as well as on computer screen. In a traditional map database, features are held as passive data: coordinates and attributes. It has been up to the application program to display or plot these in graphic form, usually by static lookup tables, based on a simple feature code. In the new object-oriented world, this constraint is broken as static features are replaced by dynamic objects. Instead of the application drawing the features according to a fixed representation derived from a feature code and stored coordinates, the application sends a message to each feature object, asking it to draw itself. Each object can decide how best to draw itself, using any available information. As well as object class (equivalent of feature code) and coordinates as before, this information can include combinations of attributes, relationships with other objects, either e...

Traditional relational databases and existing spatial transfer formats have been shown to be inadequate for creation, update and dissemination of the geospatial data so fundamental to modern life and commerce. This realisation has led to a shift to the Object paradigm for modelling geospatial data. This paper overviews the versioning and incremental update capabilities of a commercial object-oriented geospatial database. It specifically highlights its capabilities for multi-user simultaneous write access to continuous map data and the importance of versioned objects for generation of minimal update messages. It uses as examples the real-world implementation of the hydrographic electronic navigation chart (S57 ENC) service, with its weekly updates to mariners. It then outlines a new Spatial Object Transfer Format (SOTF), prototyped for the US National Imagery and Mapping Agency (NIMA). SOTF is specifically designed for the transfer of spatial object data, including provision of incre...

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. ABSTRACT (deutsch) Kommerzielle GIS Software wie ESRIs ArcGIS hat traditio...

Photogrammetric feature extraction has traditionally been a standalone activity, feeding data into GIS and mapping systems. New environments however, bring together the previously separate disciplines of photogrammetry, object data modelling and cartography to produce a unified flowline for production of maps, charts, and geospatial data. This paper overviews the capabilities of a modern stereo photogrammetric workstation and of a map production application built on an object-oriented geospatial database, to explore the synergy arising from the close interfacing of the two. The technology, merits and deployment of the integration are discussed.

The Internet is going mobile, and tomorrow's user will expect to easily retrieve everyday information via his/her hand-held wireless appliance (integrated phone plus browser). Much of this information will have a strong spatial component (where is the nearest?), and will need to be presented as some form of map. The constraints of the display size, and the on-demand nature of the information retrieval will require the use of active representation and automatic generalisation, to present the vital information to the user without unnecessary clutter. This paper analyses the impact of this new requirement on the cartographic business, and highlights the importance of active object technology in achieving the necessary presentation.

Many organisations such as national mapping agencies have collected large datasets of spatial data, often by digitising existing map series. However, they are discovering that the current and future demands for spatial datasets and mapping do not match the simple data models and unstructured feature data that they have at present. To create the required rich data models and appropriate mapping using the established GIS and digital mapping software tools has been a major challenge, which has not often been economically viable. However, there are now appearing new software products based on active objects in intelligent spatial object databases, which provide the necessary tools and infrastructure to make these tasks economically possible. This paper overviews the data modelling, dynamic topology, and active object capabilities of a commercial spatial data manipulation product, and shows how they are being used for large-scale spatial data re-engineering to create new national framewo...

Traditionally, Geographic Information Systems (GIS) were not noted for the cartographic quality of their map outputs. As such, GIS tended not to be used for the final map output stages of the workflows of major national mapping agencies or commercial map publishers. However, recent developments in the ESRI ArcGIS product suite have introduced powerful new facilities for database-centered cartographic production, capable of generating map outputs at visual quality levels comparable with those from specialized cartographic software or high-end professional graphics packages, while retaining the advantages of efficiency, consistency and automation arising from use of the GIS database. This paper describes the concepts and architecture of this new GIS-based cartographic workflow and illustrates the cartographic capabilities with visual examples. It then analyses gains and challenges involved in developing and deploying this new technology.

The stated aim of many national mapping agencies (NMAs) is to build a master large-scale digital landscape model (DLM), from which medium- or small-scale DLMs are to be derived. The digital cartographic models (DCMs) and subsequent cartographic products are then compiled from the corresponding DLMs. Generalization is at the heart of such a production strategy. Meeting the challenge of integrating

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