Jason Andersen, MGISSami Eria, PhD Geography

Department of GeographyUniversity of Minnesota

Critical Analysis of Brewer & Buttenfied (2010) – “Mastering Map Scale: Balancing Workloads Using Display and Geometry Change in Multi-scale Mapping”

CSCI 8715, Fall 2011

Week4: 29 Sept 2011

Problem Statement How can managers of

Multi Resolution Databases (MRDB) projects manage workloads incorporating tasks of varying complexities efficiently so as to produce a high quality cartographic product within budget and on time?

http://www.mapsofworld.com/usa/states/minnesota/

Problem Statement The significance of the

problem in context of spatial databases: managers of spatial databases at several national mapping agencies in the world face this problem while trying to produce cartographic map products at multiple scales

Brewer & Buttenfield contribute to the field of spatial databases by providing a conceptual model for understanding how managers can begin to start addressing the problem.

This problem is “hard” or challenging because the authors’ primary hypothesis in solving the problem is counter to expectations in the spatial databases community who expect a combination of tasks to increase overall workload

Major Contributions1. The creation of a new

conceptual model for determining the time and cost (workload) of producing a multi-scale map from multi-resolution spatial databases; in particular, the role played by the combination of symbol change and geometry change.

2. The extension of the model to further reduce the workload by the creation and incorporation of Level of Detail (LoD) spatial data into the map production process

Most significant Incorporation of LOD

Why Significant? LOD model was empirically tested

http://habib.wikidot.com/techniques

Key ConceptsSimple explanations Map Products often

needed for print media, e.g. paper maps, Web maps

National: Mapping Agencies (NMAs) compile data at specific resolutions for mapping at standard mapping scales

These mapping scales/resolutions are called “anchors”

Example NMA: Germany (uses ATKIS database)

Varying complexity as anchor data is used to map at varying scales

This has impacts on a mapping organization’s workload (includes various tasks)

Tasks include: symbolization (symbol

change)generalization (geometry

change)

Key Concepts Problems:

Time, cost, complexity

Database consistency across database versions after updates

Complicated workflows/workloads

A workload consists of multiple tasksLevel of difficulty of

each task determined by 1) length of time to complete task 2) Skill required 3) challenge in integrating changes into database

Key ConceptsProject managers Need to balance the three

parameters when carrying out multi-scale mapping projects, hence the concept of workload balancing.

What does this paper propose?

A model for managing the tasks in a multi-scale mapping project

Hypothesis A combination of

Symbol change tasksGeometry change tasks

will reduce the overall workload as compared to doing either one of these aloneThis is contrary to

expectations of most people in Spatial Databases

Further workload reduction by integration of LoD into the workflow

Exercise 1

Question: Which of the following is a smaller map scale and why?

A) 1:24k B) 1:250k

Question: Give a real life example of the use of LoD in a spatial database application?

Question: What is an example of 1. symbol /display

change2. geometry changewhen creating smaller

scale map products?

Key Concepts

Symbol + Geometry change

Include LoD

Symbol + Geometry change

Validation methodology

Strengths Simple

conceptualization of model

Good visualization of model

Empirical data used for case study 2

Weaknesses No empirical data for

case study 1

Assumptions of the model1. Data are produced at

one or more specific compilation resolutions anticipating the generation of varied map products.

2. The compiled data anchors the workload in the sense that it requires a minimum of work to create a product at the anchor’s mapping scale

3. Label changes not taken into consideration

Critique of an assumption that is unreasonable

Label changes cannot be left out of the modeling process because they are inherent to map production

Impact of removing this unreasonable assumption

Overall Workload is unreasonably low

Revisions

Preserve1. The conceptual

model for workload balancing involving symbol + Geometry change

2. The conceptual model for workload balancing involving LoD

Revise Carry out experiments

using empirical data to confirm the first conceptual model (symbol + Geometry change effects on workload)

Justification Without empirical data,

the model is weak and only hypothetical