M5. COLOURING GERMANY - colouring-cities/manual GitHub Wiki
Academic institution/department or academic consortium
Research Area Spatial Information and Modelling, Leibniz Institute of Ecological Urban and Regional Development, Dresden
Host link
Research Organization Registry (ROR)
ROR 02t26g637
City/Cities selected for initial testing
Dresden
Demonstration platform link and website
- Colouring Dresden platform
- Colouring Dresden website
- IOER Research Centre and Colouring Dresden
- Zenodo open documentation system
- Newsletter sign up link
Blogposts
- https://www.citizenscience-wettbewerb.de/blog
- https://www.citizenscience-wettbewerb.de/blog/wie-laeufts-wissenschaftliche-ausrichtung-und-ziele
- https://www.citizenscience-wettbewerb.de/blog/colouring-dresden-wie-kam-es-dazu
- https://www.citizenscience-wettbewerb.de/blog/colouring-dresden-der-start-ist-nicht-der-anfang
- https://www.citizenscience-wettbewerb.de/blog/colouring-dresden-was-steckt-dahinter
Social media and key weblinks
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Twitter: https://twitter.com/colouringdd
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Instagram: https://www.instagram.com/colouringdd/
Articles, publications links
For Colouring Dresden publications please see the CCRP Publication page
CCRP membership start date
Involved in Colouring London since 2018. Membership 2021
Anticipated launch date
- Demonstration model: Colouring Dresden. March 6th 2023
- National rollout: tbc
Academic Team (please record all significant contributions adding to/from dates where applicable)
Principal Investigators:
- Dr. Robert Hecht – senior researcher
- Dr. Hendrik Herold – senior researcher
Project co-ordinator/researcher
- Tabea Danke – researcher
Other team members:
- Dr. Martin Behnisch – senior researcher
- Theodor Rieche – researcher/PhD candidate
Multidisciplinary expertise
- Cartographic Visualization
- Citizen Science/Participatory Mapping
- Data Quality Aspects and Data Quality Control
- Geospatial Analysis using AI/ML (building classification, data fusion, change detection etc.)
- Extraction of information from historical maps using AI
- Building stock analysis in the context of environmental research
Key Collaborators
To be completed
Additional partners
To be completed
Funding
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Grant 2: BuTeGe Project phase: 10/2023-05/2025
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Grant 1: Competition phase: 08/2022-10/2022 Project phase: 11/2022-09/2023
Open building footprint source
dataset: Virtual 3D city model of the city of Dresden
- desription: https://www.dresden.de/de/leben/stadtportrait/statistik/geoinformationen/3-d-modell.php?pk_campaign=Shortcut&pk_kwd=3D
- data (LoD1 or LoD2): https://opendata.dresden.de/informationsportal/#app/mainpage//3D%20Stadtmodell//
Primary research interest/s in reproduction of platform code
- The building stock is a city's most important socio-cultural and economic resource. Buildings are where we spend most of our time and invest most of our money. They hold enormous potential for CO2 savings. In order to be able to initiate innovation-oriented, transformative measures and experiments towards climate neutrality in the building sector, comprehensive information is required on its composition and dynamics as well as the resulting CO2 emissions.
- However, in many countries, including Germany, it is difficult to collect relevant building data and use it for strategy development towards climate neutrality, as it is often highly fragmented, limited, non-existent or only available in aggregated form.
- There is a lack of both a conceptually sound set of criteria and indicators for collecting, monitoring and reflecting on progress towards climate-neutral cities in the building sector, as well as the information and data required for this.
- Colouring Dresden initially serves as a demonstrator and is to be further developed into Colouring Saxony in perspective.
- Testing the use of the Colouring Cities Platform in urban transition processes
- The first and at the same time most important milestone is the collection of basic information about the building stock, especially about the use of the buildings, their age, their typology, their construction system, the number of floors and the condition of the building.
The most useful aspects of the project for us are:
- Collection of data for the building stock, particularly building age, number of storeys, building type, material
- Support research on building stock analysis, climate change adaption, circular economy, etc.
- To raise awareness among citizens of the value of the building stock and to involve them in the process of data collection
- Openly share the collected data
Secondary research interest/s for reproduction of platform code
- Secondary research interest is the further development and testing of AI-based approaches to attribute filling. The IOER already has a great deal of expertise in the automatic analysis of historical maps and the extraction of relevant information. The information obtained via crowdsourcing could help to train and evaluate the recognition algorithms.
- Improve our ML-algorithms for extracting and classifying LU and buildings using training data
- Testing the use of the Colouring Cities Platform in urban transition processes
Greatest challenges anticipated during platform set up e.g. open footprint access, engineering support funding etc?
- Develop building typology that is understood and agreed by different domains.
- Develop a compelling narrative to motivate citizens
- Data quality analyses and data quality assurance
New feature/areas you would like to experiment with(e.g improve UI, new data categories, joint papers, joint funding applications etc., integrartion of 3D/4D etc)
- Joint research and fund applications for the development of common features and exchanging knowledge
- Sharing knowledge from experience when adapting to German city
- Testing the interplay of AI and crowdsourcing
Key Collaborators
- Chair of Spatial Development and Transformation, Faculty of Environmental Sciences, Technische Universität Dresden (Germany)
- ScaDS.AI (Center for Scalable Data Analytics and Artificial Intelligence), Dresden/Leipzig (Germany)
Milestones 2022-23
- Setting up a first functional prototype with building floor plans
- Explore potential uses of coloring cities to support the transition to climate neutrality in cities.
- Offer a regular digital "Stammtisch" for consultations and exchange.
- Provide a contact (hub) for German Colouring Cities initiatives. IOER provides the code for Colouring Germany and shares experiences with the first German platform Colouring Dresden through an open documentation of the Code and the citizen science actions Zenodo
Planned work 2023-4
The Colouring Dresden Platform is now part of the IOER-Research Data Center (IOER-RDC) and IOER will continue its role developing a support hub for Germany Colouring Cities initiatives. It is currently in discussion with The Alan Turing Institute regarding leading the CCRP's European global region hub.
Relevant papers published by the research group
Hecht, Robert, Danke, Tabea, Rieche, Theodor, Gruhler, Karin, Kriesten, Tim Felix, & Schinke, Reinhard Dokumentation des „Workshops zur Ausarbeitung der Gebäudemerkmale und deren Erfassung“ im Rahmen des Citizen Science Projektes „Colouring Dresden“ (1.0). Zenodo. (2023) https://doi.org/10.5281/ZENODO.7624511
Hecht, Robert & Rieche, Theodor Mit einer Citizen-Science-Plattform Gebäudewissen kartieren, erforschen und vermitteln und dabei klimagerechte Architektur unterstützen. gis.Business, 1, 34–36. (2023) https://doi.org/10.26084/pgvc-tx74
Hecht, Robert, Danke, Tabea, Herold, Hendrik, Hudson, Polly, Munke, Martin, & Rieche, Theodor Colouring Cities: A Citizen Science Platform for Knowledge Production on the Building Stock - Potentials for Urban and Architectural History. In S. Münster, A. Pattee, C. Kröber, & F. Niebling (Hrsg.), Research and Education in Urban History in the Age of Digital Libraries. Springer Nature Switzerland. (2023) 1853: 145–164 https://doi.org/10.1007/978-3-031-38871-2_9
Harig, Oliver; Hecht, Robert; Burghardt, Dirk; Meinel, Gotthard Automatic Delineation of Urban Growth Boundaries Based on Topographic Data Using Germany as a Case Study In: ISPRS International Journal of Geo-Information 10 (2021) 5: 353 https://doi.org/10.3390/ijgi10050353
Herold, Hendrik; Behnisch, Martin; Hecht, Robert; Leyk, Stefan Geospatial Modeling Approaches to Historical Settlement and Landscape Analysis In: ISPRS International Journal of Geo-Information 11 (2022) 2: 75 https://doi.org/10.3390/ijgi11020075
Jehling, Mathias; Hecht, Robert Do land policies make a difference? A data driven approach to trace effects on urban form in France and Germany In: Environment and Planning B: Urban Analytics and City Science 49 (2022) 1, S.114-130 https://doi.org/10.1177/2399808321995818
Schorcht, Martin; Hecht, Robert; Meinel, Gotthard Comparative Study on Matching Methods for the Distinction of Building Modifications and Replacements Based on Multi-Temporal Building Footprint Data In: ISPRS International Journal of Geo-Information 11 (2022) 2: 91 https://doi.org/10.3390/ijgi11020091
Herold, Hendrik Big Historical Geodata for Urban and Environmental Research In: Werner, Martin; Chiang, Yao-Yi (eds.) : Handbook of Big Geospatial Data. Cham : Springer, 2021, S.475-486 https://doi.org/10.1007/978-3-030-55462-0_18
Hecht, Robert; Behnisch, Martin; Herold, Hendrik Innovative approaches, tools and visualization techniques for analysing land use structures and dynamics of cities and regions (Editorial) In: Journal of Geovisualization and Spatial Analysis 4 (2020) 19, S. 1-4 http://doi.org/10.1007/s41651-020-00060-9
Behnisch, Martin; Hecht, Robert; Herold, Hendrik; Jiang, Bin Urban big data analytics and morphology (Editorial) In: Environment and Planning B: Urban Analytics and City Science 46 (2019) 7, S. 1203-1205 https://doi.org/10.1177/2399808319870016
Hecht, Robert; Herold, Hendrik; Behnisch, Martin; Jehling, Mathias Mapping long-term dynamics of population and dwellings based on a multi-temporal analysis of urban morphologies In: ISPRS International Journal of Geo-Information 8 (2019) 1, Nr. 2, S. 1-21 https://doi.org/10.3390/ijgi8010002
Sikder, Sujit Kumar; Behnisch, Martin; Herold, Hendrik; Koetter, Theo Geospatial analysis of building structures in Megacity Dhaka: the use of spatial statistics for promoting data-driven decision-making In: Journal of Geovisualization and Spatial Analysis 3 (2019) 1, Art. 7, S. 1-14 https://doi.org/10.1007/s41651-019-0029-y
Hecht, Robert; Kalla, Matthias; Krüger, Tobias Crowd-sourced data collection to support automatic classification of building footprint data In: Proceedings of the International Cartographic Association 54 (2018) 1, S. 1-7 https://doi.org/10.5194/ica-proc-1-54-2018
Hecht, Robert; Wendt, Tim; Behnisch, Martin Crowd-sourced information on building façades - A comparative study on the use of commercial and non-commercial crowdsourcing platforms In: VGI-ALIVE Workshop at AGILE, 12th June 2018. Lund, Sweden , 2018, S. 1-6 http://www.cs.nuim.ie/~pmooney/vgi-alive2018/papers/2.3.pdf
Herold, Hendrik; Hecht, Robert 3D reconstruction of urban history based on old maps In: Münster S., Friedrichs K., Niebling F., Seidel-Grzesinska A. (eds) : 5th Conference, DECH 2017, and First Workshop, UHDL 2017, March 30-31, 2017, Dresden, Germany. Cham : Springer, 2018, (Communications in Computer and Information Science; 817), S. 63-79 https://doi.org/10.1007/978-3-319-76992-9_5
Herold, Hendrik Geoinformation from the past – computational retrieval and retrospective monitoring of historical land use Wiesbaden : Springer Spektrum, 2017, S. 1-192 http://dx.doi.org/10.1007/978-3-658-20570-6 (Copyright 2018)
Herold, Hendrik; Hecht, Robert; Meinel, Gotthard Reconstruction of the land-use development with old maps In: Proceedings of the 28th International Cartographic Conference (ICC2017), July 1-8th, Washington DC, USA, 2017, S. 1-4 http://www.eventscribe.com//2017/ICC/assets/handouts/511694.pdf
Hartmann, André; Meinel, Gotthard; Hecht, Robert; Behnisch, Martin A workflow for automatic quantification of structure and dynamic of the German building stock using official spatial data In: ISPRS International Journal of Geo-Information 5 (2016) 8, Nr. 142, S. 1-30 http://dx.doi.org/10.3390/ijgi5080142
Muhs, Sebastian; Herold, Hendrik; Meinel, Gotthard; Burkhardt, Dirk; Kretschmer, Odette Automatic delineation of built-up area at urban block level from topographic maps In: Computers, Environment and Urban Systems 58 (2016), S. 71-84 http://dx.doi.org/10.1016/j.compenvurbsys.2016.04.001
Hecht, Robert; Meinel, Gotthard; Buchroithner, Manfred F. Automatic identification of building types based on topographic databases - A comparison of different data sources In: International Journal of Cartography 1 (2015) 1, S.18-31 http://dx.doi.org/10.1080/23729333.2015.1055644
Kunze, Carola; Hecht, Robert Semantic enrichment of building data with volunteered geographic information to improve mappings of dwelling units and population In: Computers, Environment and Urban Systems 53 (2015), S. 4-18 http://dx.doi.org/10.1016/j.compenvurbsys.2015.04.002
Hecht, Robert; Kunze, Carola; Hahmann, Stefan Measuring Completeness of Building Footprints in OpenStreetMap over Space and Time In: ISPRS International Journal of Geo-Information 2 (2013) 4, S.1066-1091 http://dx.doi.org/10.3390/ijgi2041066
Schinke, Ulrike; Herold, Hendrik; Meinel, Gotthard; Prechtel, Nikolas Analysis of European Topographic Maps for Automatic Acquisition of Urban Land Use Information In: Proceedings of the 26th ICA International Cartographic Conference, August 25-30, 2013, Dresden. Dresden, 2013 http://www.icc2013.org/_contxt/_medien/_upload/_proceeding/233_proceeding.pdf
Herold, Hendrik; Meinel, Gotthard; Hecht, Robert; Csaplovics, Elmar A GEOBIA Approach to Map Interpretation - Multitemporal Building Footprint Retrieval for High Resolution Monitoring of Spatial Urban Dynamics In: International Conference on Geographic Object-Based Image Analysis, 2012, Rio de Janeiro, Brazil. Proceedings of the 4th GEOBIA. São José dos Campos : INPE, 2012, S.252-256
Herold, Hendrik; Röhm, Patric; Hecht, Robert; Meinel, Gotthard Automatically Georeferenced Maps as a Source for High Resolution Urban Growth Analyses In: Proceedings of the ICA 25th International Cartographic Conference, July 3 - 8, Paris, France. Paris, 2011, S.1-5
Meinel, Gotthard; Hecht, Robert; Herold, Hendrik Analyzing Building Stock using Topographic Maps and GIS In: Building Research & Information 37 (2009) 5-6, S.468-482