generalization

Automatic Generalization up to 80% Correct

Contrary to common belief in the past, critical parts of the map production process, including cartographic generalization, can be automated to produce quality results. This saves valuable time and resources.

Automated Generalization - Case Study swisstopo

Read a case study about how axpand has over 75% correct automated generalization.

Automatic Generalization - a Case Study

swisstopo – The Customer

swisstopo is the competence center of the Swiss Confederation responsible for geographical reference data and all products derived from them. swisstopo’s National Map series enjoys international recognition.

Automated Generalization - examples

In all of the 1:10'000 and 1:25'000 examples here, German NAS data was imported into a German-specific AAA data model and automatically generalized. Text was placed automatically as a final step. In these examples, there was no manual intervention at any point. At this scale, building generalization, displacement and data thinning are especially important. Although the data and the model are specific to Germany, data in any model and scale can be automatically generalized.

axpand ng - New Generation Generalization

axpand ng is truly a new generation. Model and cartographic generalization have long been considered one of the most time-consuming tasks included in the map-making process. Cartographers have traditionally spent at least several months on this part of the process alone. Axes Systems has worked closely with universities and other research groups to find a pragmatic way to solve this problem.

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