Usage code

Preface

This usage code

• is part of the GitHub repository building.map_1920. Check out the readme file to learn more about the corresponding datasets and how to use and re-use the underlying R Markdown file.

• supplements the paper “Data description of ‘Building age map of Vienna and its surroundings around 1920’”, which is currently under review in Data in Brief.

• is for users of the datasets who want to use and re-use the datasets.

1 Introduction figures

2 Scales of analog map sheets

Scales of building stock maps, which were used to retrieve the building footprints: 1:NA, 1:5000, 1:3500, 1:1440, 1:10000, 1:2880. Note: NA stands for “not available”, because the digitial city map is vectorized and therefore doesn’t have a scale.

3 Addresss changes

Address changes between ‘Address.2019’ and ‘Address.1920’. Scope: ‘Address_review’ = yes

address change	affected polygons	ratio [%]
yes	13,108	26
no	36,478	74

4 Area of building footprints

The “Area” records are summarized by “UD.1920” and “UD.2020”, respectively, and plotted in the next figure.

## Warning: Removed 2 rows containing missing values (geom_bar).

## Warning: Removed 2 rows containing missing values (geom_text).

5 Data sources to retrieve building footprints

The “Polygon.source_name” records were grouped by “UD.2020”, summarized by “Area” and plotted in the next figure.

• Number of unique maps sheets: 134. Retrieved from City map 2018, Historical urban district map, Historical fire brigade map, Historical cadaster, Analog building age map 1920, Analog building age map 1920 (digital raw data).
• Number of unique timestamps: 19.

6 Editors of vectorized building footprints

The “Editor” records were grouped by “UD.2020”, summarized by “Area” and plotted in the next figure.

• Number of unique editors: 10.

7 Temporal presence of building footprints

The “TP_pub.date_period” records were grouped by “UD.2020”, summarized by “Area” and plotted in the next figure.

• City-wide data grouped into 3 periods.

  TP_pub.date_period	sum_area_abs	sum_area_rel
  1906-1912	227	10
  1920-1923	1,679	74
  1927-1936	373	16

8 Period of constrution

The “PoC” records were grouped by two different types of timespan, summarized by “Area” and plotted in the next figure.

## [1] CD.bs   min     max     szbg_bp
## <0 Zeilen> (oder row.names mit Länge 0)

• Summary: Assignment of construction dates.

  Data field	N of assigments	Unique dates before h	Unique dates after h
  CD.abam	49,156	12	10
  CD.bs	3,125	238	12
  TP_pub.date_year	28,359	19	3

• Summary: Grouping PoC records.

  timespan	sum_area	sum_area_rel
  10-years period	1,428	63
  Before given year	851	37

• Number of construction date assignments.

  CD_multiple	count_CD_multiple	count_CD_multiple_rel
  1	28,359	35
  2	35,233	44
  3	17,048	21

9 Data sources to retrieve building construction dates

The “PoC.source_name” records were grouped by “UD.2020”, summarized by “Area” and plotted in the next figure.

• City-wide data:

  PoC.source_name	sum_area	sum_area_rel
  CD.abam_1920, ABAM_1920	1,665	73
  CD.bs, BS_1920s	94	4
  TP_pub.date_year, ABSM	520	23

10 Location of building footprints within city limits 1920

The “Location.city_limits_1920” records were grouped by “UD.2020”, summarized by “Area” and plotted in the next figure.

• City-wide data:

  Location.city_limit_1920	sum_area	sum_area_rel
  in	2,142	94
  out	137	6

11 Location of building footprints within scope of analog building age map 1920

The “Location.ABAM_1920” records were grouped by “UD.2020”, summarized by “Area” and plotted in the next figure.

• City-wide data:

  Location.abam_1920	sum_area	sum_area_rel
  in	1,767	78
  out	512	22

12 Building counts by urban district

13 Building footprint presence in 1920

• City-wide data:

  Presence.conf	sum_area	sum_area_rel
  inside built-up area of LSM 1912	68	3
  inside built-up area of USM 1918	127	6
  inside built-up areas of LSM 1912 and USM 1918	2,083	91
  outside built-up areas of LSM 1912	1	0

14 Construction years

• BS_1920s perspective: : The BS_1920s includes 2.5859^{4}(100%) entries with records in “YoC.1920”, “STR.1920s” and “BN.1920”. The latter two are needed to join the BS_1920s and BSM_1920. The workflow in this study captured 1.9631^{4} (76%) “YoC.1920s” records and assigned them to buildings in BSM_1920. In other words, the remaining potential for assignments is (24%).

• Statistical yearbook (SY_1929) perspective:

  data_source	count	ratio
  CD.bs_BSM_1920	19,631	45
  SY_1929	43,910	100
  YoC.1920s_BS_1920s	25,859	59

15 Construction periods

• Summary: The building footprint area is 2279 ha.

  PoC.source_name	sum_area	sum_area_rel
  CD.abam_1920, ABAM_1920	1,665	73
  CD.bs, BS_1920s	94	4
  TP_pub.date_year, ABSM	520	23

• Summary: The building footprint area is 2279 ha.

  category	sum_area	sum_area_real
  after	56	2
  ambiguous	17	1
  before	35	2
  included	746	33
  No ‘CD.bs’ record	1,425	63

• Summary: This table is based on data entries that have “PoC” and “CD.bs” records. In other words, blank “CD.bs” records are excluded. The building footprint area is 854 ha, which is 37% of the total area.

  CD.bs_fit	sum_area	sum_area_rel
  after	56	7
  ambiguous	17	2
  before	35	4
  included	746	87

Annnex

Write CSV file

Plotting figures

The figures are published in the corresponding paper.

## Warning: Removed 2 rows containing missing values (geom_bar).

## Warning: Removed 2 rows containing missing values (geom_text).