Paris Metropolitan, an evolution: Difference between revisions
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* '''open_date''' ''<date_format>'': this is the actual date of opening of the station, independently from the map it was retrieved. | * '''open_date''' ''<date_format>'': this is the actual date of opening of the station, independently from the map it was retrieved. | ||
* '''close_date''' ''<date_format>'': this is the actual date of closure of the station, if it occurred, and this independently from the map it was retrieved | * '''close_date''' ''<date_format>'': this is the actual date of closure of the station, if it occurred, and this independently from the map it was retrieved | ||
* '''ratp_id''' ''<int>'': this id corresponds to the identification number of the station according to the database provided by the [https://data.ratp.fr/explore RATP]. By adding this identification, we enable the project to be used in varied contexts and to be affiliated to the RATP itself.< | * '''ratp_id''' ''<int>'': this id corresponds to the identification number of the station according to the database provided by the [https://data.ratp.fr/explore RATP]. By adding this identification, we enable the project to be used in varied contexts and to be affiliated to the RATP itself.<br> | ||
Thanks to the software QGIS, we were able to store the data for each station when creating its correspondant geolocated point on the shapefile. The whole can be then exported in various format, such as GeoJSON and csv, two formats widely used in the case of databases containing geographic references. We thus decided to export the database of each shapefile in both GeoJSON and csv formats in order to enable various use of the data collected. As we had a set of three different databases, each corresponding to one of the three maps from which the data was extracted, we decided to manually group them in one single file and operate a few changes either manually or with the help of a short program created with Python. Indeed, there were important name changes for a few lines that occurred from 1908 to 1950, for example the line 2 Sud, which became line 5 in-between 1908 and 1915 and line 6 before 1950. As we did not want to manually recreate a point at each location of the stations on the line for each map, the entries corresponding to that line were duplicated and the corresponding '''start_map''' and '''end_map''' were corrected with a few lines of code in Python.< | Thanks to the software QGIS, we were able to store the data for each station when creating its correspondant geolocated point on the shapefile. The whole can be then exported in various format, such as GeoJSON and csv, two formats widely used in the case of databases containing geographic references. We thus decided to export the database of each shapefile in both GeoJSON and csv formats in order to enable various use of the data collected. As we had a set of three different databases, each corresponding to one of the three maps from which the data was extracted, we decided to manually group them in one single file and operate a few changes either manually or with the help of a short program created with Python. Indeed, there were important name changes for a few lines that occurred from 1908 to 1950, for example the line 2 Sud, which became line 5 in-between 1908 and 1915 and line 6 before 1950. As we did not want to manually recreate a point at each location of the stations on the line for each map, the entries corresponding to that line were duplicated and the corresponding '''start_map''' and '''end_map''' were corrected with a few lines of code in Python.<br> | ||
As a result, we obtain two databases, one for the stations and one for the lines, which is implemented in the same way, and which exist in either a GeoJSON or a csv format. The database works as following: | |||
Each station was given a ""stop_id"" when first appearing on a map. The ""start_map"" corresponds to the year of the map the information was retrieved and the ""end_map"", the year of the last map the information was seen. Each station is affiliated to a unique line which name is stored under ""stop_line"". If multiple lines pass through a station, then there is a new entry for each lines. We can thus say that the "stop_id" corresponds to one of the platforms of a station. | |||
== Quantitive analysis of the performances of extraction == | == Quantitive analysis of the performances of extraction == |
Revision as of 13:54, 25 November 2018
Definition of the project
The group first selected a range of different maps showing the Paris Metropolitan at different years. In total, we collected from Gallica a set of two maps of the planning of the metro, from the definition of the routes to the addition of stations, a first map from 1908 of the actual metro after its construction in 1990, a second map from 1915, with already visible impacts of the first war, and a third map from 1950, a more contemporain look at the metro as we know it today. Our first idea was to analyse these maps in order to understand the evolution of the Paris Metropolitan, how different areas of major cultural attractions evolved around or hand in hand with the metro stations and how it was impacted by catastrophic events such as wars. However, as the goal of the project is to produce a working interface within a short amount of time, we decided to reduce the work of extraction of data to one map, which is the first map from 1908. Based on this map, we thus intend to build a superposition of a current map from Paris and the metro network extracted from the old map. From this visual display, will be able to see the evolution of the Paris Metropolitan from 1908 until nowadays and important historical explanations will be linked to corresponding stations. The result should take the form of a website page that displays the interactive map. The users would have the possibility to display the different layers, namely the layer of the old map, its metro network, with stations and lines, and this on top of a current map of Paris. Popup windows on each stations would display specific historical information about the station, which would be linked to the sources.
It is based on this prototype that the possibility to conduct similar data extractions on the other maps selected will be considered.
Main steps
- Download in high resolution the different maps
- Create a list of all stations from the first map of 1908
- Determine the main cultural attractions around these stations
- Georeferencing the map from 1908
- Create maps alignment with a contemporain map of Paris
- Extract paths and stations from the map
- Determine or extract coordinates of the different stations
- Create a Database with all the information gathered for each station from 1908
- Compare the first path and stations from 1908 with the actual built one
- Create a website in order to display the maps in an interactive way
- pop up windows on specific points, such as stations with strong historical backgrounds
- an overlay of maps in order to better see the evolution from 1908 to nowadays
Milestones
Week 9 (14.11 - 16.11):
- Georeference, alignment with contemporain map and extraction of the paths and stations
- Preparation of the structure of a GeoJSON database
- Preparation of the midterm presentation
- Finalisation of milestones
Week 10 (21.11 - 23.11):
- Analyse of the evolution of the Paris Metropolitan based on the information gathered
- Finish Database in GeoJSON
- Finish writing the description of the extraction methods
- Planning for the creation of a website
Week 11 (28.11 - 30.11):
- Creation of the website to display the data
- Implementation of an interactive map
Week 12 (5.12 - 7.12):
- Finalization of the project
- Finish writing the report (historical introduction to the map, analysis of the performance of extraction, motivation and description of the services)
Historical introduction to the map
The maps used for the project were all published by A. Taride. The publishing house was founded by Alphonse Taride in 1852 [1] in Paris and was one of the first to create road, tourist and school maps. The group grew in 1895 when, helped by the "Union vélocipédique de France" and engineers from "Les ponts et chaussées", they printed their first maps at the scale of 1/25 000 000 [2]. These maps were considered as a reference in Europe and North Africa until 1930 [3]. Among their collection of vélocipédiques maps, they also proposed a range of Paris metropolitan maps and touristic guide, translated in different languages [4] .
Unfortunatelly, the firm is on a wane after the second World War and reduce his work to Paris maps and globes. The firm is later redeemed by the last french producer of globes.
Based on the maps, we can see that the publishing house was first located at 18 and 20 Boulevard Saint Denis (described on the 1908 and 1915 maps) and then moved to 154 Boulevard Saint Germain, as we can see on the 1950 map. They are all printed in color and display the city of Paris overlaid by the metropolitan network. They all provide a legend with the definition of the different paths and stations. The map from 1908 is at a scale of 1/8000, the map from 1915 of 1/21 000 and the one from 1950, at a scale of 1/33 000.
All the maps chosen represent the path of the Metropolitan of Paris overlaid on the city map. The first line of the Metropolitan of Paris was built in 1900 for the Paris Exposition Universelle. However, the race to build a network of railway transports started way before, around 1845, as many capitals were considering the possibility to develop such transport systems, such as London, who built the world's first underground railway in 1890. However, it remained a subject of discussions during several years as the city of Paris wanted to build his own network for its inhabitants and the national railway services wanted to extend existing transports for people around the big metropole. The upcoming Exposition Universelle and the developments of such novative means of transports in big capitals finally weighted on the balance to create an underground railway network specifically for the city of Paris. The first line, from the Porte de Vincennes to the Porte Maillot, was built just in time in 1900 for the big event, and two more lines were added by 1914 [5].
Detailed description of the extraction methods
In order to extract information from the map, we decided to work with the open source software QGIS3.
This software is a powerful GIS platform which enables to georeference maps, draw points, lines and polygones in order to create new and interactive maps or to enhance and analyse existing ones. It benefits from a good community of users, with even a specific associative platform for Switzerland.
The extraction of the information from the Paris map of 1908 required different steps, from the georeferencing to the extraction of the metropolitan network itself.
Georeferencing
The first step of the work with the 1908 map consists of georeferencing it, namely register it with a coordinate system in order to map it with a location on the surface of the earth [6]. Indeed, the basic map of the Metropolitan of Paris is just an image file that does not contain any geographic information such as coordinates. In order to create these coordinates, we had to work with a shapefile of the buildings of the city of Paris. These ressources are easily found "online", as their are freely made available by the city of Paris [7]. This shapefile is first imported in the new project created in QGIS. Then, the CRS (Coordonate Reference System) we are working with in the context of the project has to be correctly set to the french CRS, called RGF93. After having synchronized the layers with this CRS, the plugin Géoréférenceur GDAL[8] is used. It consists of a window, from which our image, the Paris map of 1908, is imported as a raster and displayed. A raster is an image file to which is added georeferencing information [9]. In order to determine the right coordinates on the image of 1908, a tool from the plugin enables to find matching points from the image to the shapefile of the city of Paris. The work consists of selecting a point on the image and to then find its visual correspondance on the shapefile of the buildings of Paris. We chose these points according to recognizable buildings which exists on both maps. In the end, a total of 6 coordinate points in order to launch the georeferencing. The transformation we then performed was generated with a Polynomiale 1 and a .tiff file was created. This .tiff file contains both the image and the coordinate information of the raster and can be used as a foundation for the following steps of the project.
Overlaying the old map on a contemporain basemap
Now that we have our old map as a raster, its image can be easily placed on top of a contemporain map with the help of its coordinates. QGIS3 proposes a feature called XYZ Tiles and which enables to easily overlay the raster on a tile layer, a corresponding basemap, from the "openstreetmap website".
Extracting information
Based on the raster created, the extraction of information can be performed. In order to extract the different stations, a Shapefile has to be created. A Shapefile, already introduced previously for the georeferencing, is a set of different files, .shp, .dbf, .shx, .prj, which all contains information that enables to create a map, with a coordinate system and a visual display via points, vectors or polygons. When creating a new layer Shapefile with QGIS, the name has to specified as well as the type of geometry aforesaid that can either be points, lines or polygons. Then, a list of fields can be define. This list of field is later filled for each point created and can constitute a database.
Railway stations
For the layer containing information about the stations, the type of geometry used is the point. We also added different fields of information for a future database discussed below. Among others, a first string field called stop_name, in order to store the name of the station, and a second string field called stop_line, in order to store the name of the line the station belongs to. Then, each station visible on the old Metropolitan map from Paris was selected with a point and given a Name and a Ligne accordingly.
Railway lines
We then created a second layer of Shapefile for the lines of the metro. The geometry used for this purpose is the line and the string field name was created. In order to map the vectors of the line with the exact coordinate of the stations previously set and create a coherent path, the snapping feature of QGIS3 [10] was enabled. The snapping enables to select a perimeter of anchor of a point on a layer. When drawing a line, existing points are then working as magnets and attract the line in order to make it pass through it. Thus, the 6 different lines of the Metropolitan of Paris from 1908, namely line 1, 2 Nord and 2 Sud, 3, 4, 5, 6, were created and passing through the exact coordinates of the stations previously established.
Implementing a process for further maps
As the extraction method presented above is not an expensive process in terms of time, mainly due to the scale of the data, the information from the last two maps from 1915 and 1950 presented in Selected maps were also extracted. In order to create a coherent database and a reusable process for later maps, as discussed below, the new stations and lines of both maps were extracted in a chronological way. We thus first started with the map from 1915 and determined the new stations that were created in-between 1908 and 1915 thanks to the georeference of the map and the possibility to overlay the previous data extracted. The process consists of three steps :
- Create a new shapefile layer for the stations of the map (here we started with 1915)
- Look for the name changes or station mergers. Add the points of the new stations as well as the different fields of information already used for the first extractions. Same applies with new lines.
- Then, for each station which name changed in-between the current map and the previous georeferenced one (here in-between 1908 and 1915), a new point is added to the current shapefile layer with the information change in the corresponding fields of information.
Thus, each shapefile layer corresponding to each different map (and consequently to different years) contains both the geolocalisation of the newly built stations and the stations whose name changed compared to the last georeferenced map. Layer after layer, we can thus see the metropolitan network growing.
Creation of a database
A significant aspect of this project is to create a database in order to further work with the data extracted, such as creating interactive maps, and to set the foundation of a reusable tool for later maps and contemporain changes of the Paris Metropolitan. In order to create this database, we used the information added manually for each point entries in QGIS. It was therefore important to create from the beginning the required fields of information in preparation of the database. In order to create a coherent database that can handle the adding of new stations, name or line changes and stations merging, the following fields were created:
- stop_id <int>: this corresponds to the identification number of each station. When a station is created, a stop_id is given with the following format : YYYYE, YYYY being the year of the map, E the unique number of entry of the specific point in the shapefile. When the name of the station is changed, the station keeps its identification number.
- stop_name <string>: this corresponds to the name of the station as written on the map the station was extracted from. When the name changes on a new map, the entry corresponding to the station is duplicated, the stop_id remains the same and the stop_name field is changed to the corresponding information
- stop_line <string>: this corresponds to the name of the line to which the station is affiliated. If there are multiple line passing through a station, then an entry is created for each station, with a unique stop_id for each of them. With this system, we thus consider each platform as a different station.
- start_map <int>: this number is under the form YYYY and corresponds to the year of creation of the map from which the station was retrieved. If the station changed name, this field corresponds to the year of the map where the name changed occurred.
- end_map <int>: this number is under the form YYYY and corresponds to the year of the map where the station name disappears, either because of a merged or because of a name or a line change.
- open_date <date_format>: this is the actual date of opening of the station, independently from the map it was retrieved.
- close_date <date_format>: this is the actual date of closure of the station, if it occurred, and this independently from the map it was retrieved
- ratp_id <int>: this id corresponds to the identification number of the station according to the database provided by the RATP. By adding this identification, we enable the project to be used in varied contexts and to be affiliated to the RATP itself.
Thanks to the software QGIS, we were able to store the data for each station when creating its correspondant geolocated point on the shapefile. The whole can be then exported in various format, such as GeoJSON and csv, two formats widely used in the case of databases containing geographic references. We thus decided to export the database of each shapefile in both GeoJSON and csv formats in order to enable various use of the data collected. As we had a set of three different databases, each corresponding to one of the three maps from which the data was extracted, we decided to manually group them in one single file and operate a few changes either manually or with the help of a short program created with Python. Indeed, there were important name changes for a few lines that occurred from 1908 to 1950, for example the line 2 Sud, which became line 5 in-between 1908 and 1915 and line 6 before 1950. As we did not want to manually recreate a point at each location of the stations on the line for each map, the entries corresponding to that line were duplicated and the corresponding start_map and end_map were corrected with a few lines of code in Python.
As a result, we obtain two databases, one for the stations and one for the lines, which is implemented in the same way, and which exist in either a GeoJSON or a csv format. The database works as following:
Each station was given a ""stop_id"" when first appearing on a map. The ""start_map"" corresponds to the year of the map the information was retrieved and the ""end_map"", the year of the last map the information was seen. Each station is affiliated to a unique line which name is stored under ""stop_line"". If multiple lines pass through a station, then there is a new entry for each lines. We can thus say that the "stop_id" corresponds to one of the platforms of a station.
Quantitive analysis of the performances of extraction
Motivation and description of the services
Selected maps
The different maps selected for the project are the following:
References
- ↑ Babelio, Taride Babelio, last accessed on 2018-11-13
- ↑ Corpus Cartographique Etampois, Alphonde Taride, Carte routière de l'Etampois en 1914, last accessed on 2018-11-13
- ↑ Corpus Cartographique Etampois, Alphonde Taride, Carte routière de l'Etampois en 1914, last accessed on 2018-11-13
- ↑ Babelio, Taride Babelio, last accessed on 2018-11-13
- ↑ Peter Hall, Underground as City Maker: London Versus Paris, 1863–2013, 2013, pp. 177-183, last accessed on 2018-11-13
- ↑ GIS Ressources, What is Georeferencing?, last accessed on 2018-11-05
- ↑ Open Data "Open Data | Volumes bâtis - Données géographiques", last accessed on 2018-11-05
- ↑ QGIS 2.14 documentation "Extension de géoréférencement", last accessed on 2018-11-05
- ↑ EMSE "Glossaire des SIG - Raster (Format)", last accessed on 2018-11-05
- ↑ QGIS 2.18 Documentation "Editing", last accessed on 2018-11-05