Innovative approaches to data synthesis - Big Data in Land Management

Dr.-Ing. Matthias Soot

Improving data quality

Decisions in the context of land management require a sound database. The aim of this work is the development of new methods to improve the data basis on the basis of linking already existing data. A wide variety of data is available from a wide variety of public sources. However, an essential characteristic of these data is that in many sources the data can only be collected with gaps. By suitable modeling of already existing data of other sources these data gaps are to be closed. For this purpose, other existing (geo)data are used to derive approximate values in a model-like manner. Parametric and non-parametric modeling methods are used for this purpose. For example, living areas can be derived from abstract (LOD2) building models. Likewise, images of buildings can be used to automatically derive statements about the quality and age of the buildings using artificial intelligence (AI) methods.

Linking inhomogeneous data

In addition to improving the individual data sets, different data are to be linked, for example, using multisensor fusion methods. For this purpose, it is first necessary to create standards for storing and exchanging data in the context of land management, or to examine existing standards for their suitability. Likewise, suitable methods must be investigated or developed that can deal with the very inhomogeneous scatter in the data as well as the systematic deviations to "true values". Furthermore, in the context of linking data, dependencies on external influences (e.g. socio-economic or ecological aspects) must be investigated more closely in order to develop optimal models and uncover correlations.

Detection of climate aspects in land management

The collected and linked data will be examined in more detail for the application field of climate aspects in land management. For this purpose, in particular the value influences of energetic refurbishments will be investigated on the basis of large-scale collected data. The aim is to measure the increase in value and, in the case of possible subsidy programs, e.g. within the framework of urban development subsidies, to limit the subsidy amount to the costs of the renovation measure minus the increase in value caused by it. The data collected will also be used to observe the effects of urban overheating on urban development measures and the influences on property values.

Publication:

Articles (Peer-Reviewed):

• Soot, M., Zaddach, S., Teuber, A., Homes, M., Schweden, C., & Weitkamp, A. (Angenommen/Im Druck). Standards für die Bereitstellung von amtlichen Wertermittlungsdaten – eine Analyse mit Handlungsempfehlungen. zfv - Zeitschrift für Geodäsie, Geoinformation und Landmanagement, 148(5).
• Ortner, A., Soot, M., Krause, N., & Weitkamp, A. (2023). Lage! Lage. Lage? – Weiterentwicklung der Operationalisierung räumlicher Lagen im Landmanagement. in S. Henn, B. Braunschweig, & T. Zimmermann (Hrsg.), Stadtregionales Flächenmanagement (S. 1-22). SPRINGER VS/SPRINGER FACHMEDIEN. https://doi.org/10.1007/978-3-662-63295-6_33-1
• Soot, M., Dingerdissen, U., Eltner, A., Fast, H., Flatt, H., Loges, S., Paffenholz, J-A., & Weitkamp, A. (2022). Vorstudie zu wertbeeinflussenden Parametern hinsichtlich der Klimaeffizienz von Wohngebäuden. Allgemeine Vermessungs-Nachrichten : AVN ; Zeitschrift für alle Bereiche der Geodäsie und Geoinformation, 129(5), 163-180. https://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa2-816071

Presentations:

• Matthias Soot (Redner:in), Sabine Horvath (Beteiligte Person), Hans-Berndt Neuner (Beteiligte Person), Alexandra Weitkamp (Beteiligte Person) (2023). Benefits and limitations of machine learning methods in the inhomogeneous real estate market of mixed-use asset class 2023, European Real Estate Society (ERES): 29th Annual Conference 12 Juli 2023 → 15 Juli 2023, London, Großbritannien/Vereinigtes Königreich
• Matthias Soot (Redner:in), Alexandra Weitkamp (Beteiligte Person) (2022). Climate change mitigation in building sector – a case study on potential. EALD Symposium 2022: Symposium of European Academy of Land Use and Development: Ecological, Social and Spatial Justice, 1. September → 3. September 2022, Frankfurt am Main.
• Matthias Soot (Redner:in), Alexandra Weitkamp (Beteiligte Person) (2022). Deriving Real Estate Meta Data from CityGML LOD2 Modells, 25 Juni 2022, European Real Estate Society (ERES): 28th Annual Conference 22 Juni 2022 → 25 Juni 2022, Mailand, Italien

Further Publications:

• Paffenholz, J-A., Eltner, A., Dingerdissen, U., Flatt, H., Fast, H., Loges, S., Ostrau, S., Soot, M., & Weitkamp, A. (2022). 3D-Punktwolkenbasierte Umgebungserfassung für die Detektion klimarelevanter Immobilienparameter. in Terrestrisches Laserscanning 2022 (TLS 2022): Beiträge zum 214. DVW-Seminar am 8. und 9. Dezember 2022 in Fulda (Band 104, S. 187-197). DVW e.V. – Gesellschaft für Geodäsie, Geoinformation und Landmanagement. https://geodaesie.info/images/schriftenreihe/downloads/DVW_104_2022_TLS_2022_FINAL_221122.pdf