Multiple Representations with Overrides, and their relationship to DLM/DCM Generalization. Paul Hardy Dan Lee

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1 Multiple Representations with Overrides, and their relationship to DLM/DCM Generalization Paul Hardy Dan Lee 1

2 Context This is a forward-looking presentation, and much of the capabilities it describes are still under development. As such, it is intended to give guidance as to likely future direction and should not be interpreted as a commitment by ESRI to provide precise capabilities in specific releases. 2

3 Representations and Overrides 3

4 Five Stages of Symbolization Control Stage 1 - Linear Features (Tracks) Stage 2 - GIS Dash symbol Bad joins and bends 3 - Automatic Representation 4 - Manual Override 5 - Free Representation 4

5 Solution Concepts One environment through GIS to finishing Cartographic Representations High-quality rules for visualization Stored in the database Overrides Exceptions to the rules Human knows better than machine Can sometimes automate (cul-de de-sac roads) Stored in the database Representation editing tools Intuitive, similar to Illustrator 5

6 Representation Pipeline GIS Feature Representation Rule ID Overrides (if any) Shape Rule Geometric Effect Geometric Effect Basic Symbol Symbol Geometric Effect Basic Symbol Screen or Print 6

7 Demonstration Representations & Overrides 7

8 Cul-de de-sac Processing 8

9 Free Representation - editing of dashes for clarity 9

10 Cartographic Editing See [Eicher & Briat 2005] ICA paper Supporting Interactive, Manual Editing of Cartographic Representations in GIS Software 10

11 Road crossings Road intersections ambiguous Automatically calculate crossings Use crossing areas as mask Can add parapets automatically 11

12 Escarpment Stages of Control 1 Line features 2 GIS symbol 3 Representation 4 Manual Override 12

13 Data copyright swisstopo Swiss topographic map representation 13

14 Database-centered Workflows Enterprise Geodatabase Views Updates Maps Analysis Mission Critical Applications 14

15 Simple case existing features Feature Class (Roads) Cartographic Representation (Clearer roads) Town Plan Map 15

16 Multiple Representations Feature Class (Roads) Cartographic Representation (Clearer roads) Another Representation (Special roads) Town Plan map Leisure map 16

17 Enterprise (DLM) Case Cartographic Database Feature Class (Roads) Cartographic Representation (Better roads) Another Representation (Special roads) Extract via Geoprocessing: Copy Select Subset Generalize Town Plan map Leisure map DLM Feature Class (Detailed Roads) Landscape Database 17

18 Landscape Models, Cartographic Models, and Products Data Product Model Generalization Landscape Model Cartographic Generalization Cartographic Model Visual Product Course Routing Derive Features DLM Coarse Derive Features Derive Reps DCM_Small Rep250S Rep200A 1:250K Sheet 1:200K Atlas Derive Features DLM Medium Derive Features Derive Reps DCM_Mid Rep100T Rep50T 1:100K Topo 1:50K Topo Fine Routing Change in Real World DLM Fine (Master) Derive Features Derive Reps DCM_Basic Rep10S Rep10P 1:10K Sheet 1:10K PDF 18

19 Geoprocessing and Generalization 19

20 Geoprocessing ArcToolbox Core tools Python Scripts and AMLs Models (including other tools) Any executable 20

21 Generalization Generalization is about abstraction exaggerate the important subdue or remove irrelevant detail move reality to make space Needs pattern recognition Humans find hard, while computers find harder! 1:10,000 1:50,000 1:250,000 Crown Copyright, Courtesy OSGB 21

22 Generalization Algorithms Simplify buildings Aggregate buildings avoiding streets Displace buildings from roads Collapse double-line roads to centerlines Aggregate polygons Displace linear features 22

23 Generalization Process Models Data Ordnance Survey GB Crown Copyright 23

24 New Generalization Tools Four New tools to Generalize Database Features Simplify Polygon - Simplifies a polygon by removing small fluctuations or extraneous bends from its boundary and preserves its essential shape Simplify Building - Simplifies the boundary or footprint of a building polygon while maintaining its essential shape and size Aggregate Polygon - Combines disjoint and adjacent polygons into new area features based on a distance Collapse Dual Lines to Centerlines - Derives centerlines (single lines) from dual-line features 24

25 Simplify Polygons 25

26 Simplify Buildings 26

27 Aggregate Polygons Non-orthogonal Orthogonal 27

28 Collapse Dual-Lines To Centerline 28

29 Generalization is Hard Can t t do it a feature at a time Involves relationships with neighbours Can t t do it a layer at a time Relationships are with features of many classes Can t t do uniformly Even features of one class have different surroundings Can t t do it across whole map at once Must localize or partition Can t t do it just on geometry Needs understanding of topology and of attributes 29

30 Possible Generalization Flow Data Structure Enrichment Partitioning Meso area Classification Pattern & Group Detection If worse, undo Context Analysis Dispatch to Appropriate Algorithm Reclassify, Aggregate Exaggerate, Simplify, Displace, Typify, Check Loop until Done 30

31 Update Change at largest scale then propagate incremental differences See [Briat, Monnot, Kressmann 2005] ICA paper: Incremental Update of Cartographic Data in a Versioned Environment 31

32 Summary Advanced cartographic representation mechanisms and cartographic editing tools will soon become available in a commodity GIS. Together with production automation and graphics capabilities they will dramatically change the scope of automated cartography, facilitating the generation of multiple products from a central database. The human freedom enabled by the override system, combined with the symbolization rule pipeline, will permit high-quality attractive cartography within a database-centered environment. The representation and override mechanisms, together with the geoprocessing framework also form the foundation for generalization processes and incremental update propagation 32

33 Questions and Comments? 33

GIS-Based Generalization and Multiple Representation of Spatial Data

GIS-Based Generalization and Multiple of Spatial Data Paul Hardy, Dan Lee ESRI Inc, 380 New York St., Redlands, CA 92373, USA phardy@esri.com,dlee@esri.com Abstract. It is a strategic goal of many national