Objects resulting from the sequential generalization of the buildings group in Gdańsk district - scale 1:10000 - Open Research Data - Bridge of Knowledge

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Objects resulting from the sequential generalization of the buildings group in Gdańsk district - scale 1:10000

Description

The process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].

The provided data are the result of the last stage of building groups sequential generalization process. During the process, objects with the highest average coefficient values were selected from three methods of data simplification (Chrobak’s method - GDA_OrthogonalizationChrobak, Sester’s method - GDA_OrthogonalizationSester and the Simplify Building tool - GDA_OrthogonalizationArcGIS) for a group of buildings with the same identifier, while eliminating those objects that had a value of -1 in one of four coefficients.

Literature

[1] Regulation of the Ministry of Administration and Digitization, W sprawie bazy danych obiektów topograficznych oraz bazy danych obiektów ogólnogeograficznych, a także standardowych opracowań kartograficznych [Regarding the database of topographic objects and the database of general geographic objects, as well as standard cartographic studies.]

Dataset file

GDA_GeneralizedGroupsOfBuildings.zip
2.5 MB, S3 ETag 66d3c591143425a9887149010fb42235-1, downloads: 71
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5
download file GDA_GeneralizedGroupsOfBuildings.zip

File details

License:
Creative Commons: by 4.0 open in new tab
CC BY
Attribution

Details

Year of publication:
2020
Verification date:
2020-12-28
Creation date:
2020
Dataset language:
English
Fields of science:
  • Civil engineering and transport (Engineering and Technology)
DOI:
DOI ID 10.34808/4r5y-c641 open in new tab
Series:
Verified by:
Gdańsk University of Technology

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