Logo des Repositoriums

Auflistung nach Autor:in "Kolbe, Thomas H."

1 - 4 von 4
  • Konferenzbeitrag
    Landmodell: Ein semantisches 3D + t Datenmodell als Integrationsplattform zur Analyse der Agrarlandschaft und ihrer raumzeitlichen Veränderungsprozesse
    (Informatik in der Land-, Forst- und Ernährungswirtschaft 2015, 2015) Machl, Thomas; Donaubauer, Andreas; Kolbe, Thomas H.
    Der landwirtschaftliche Strukturwandel und nicht zuletzt auch die Ausweitung des Anbaus nachwachsender Rohstoffe für die energetische Nutzung haben in den vergangenen Jahrzehnten zu einer deutlichen Veränderung der Agrarlandschaft beigetragen und diese nachhaltig geprägt. Vor diesem Hintergrund beschäftigt sich die Forschungslinie '3D + t Landmodellierung' am Lehrstuhl für Geoinformatik der TU München mit der Entwicklung eines umfassenden und zu- nächst anwendungsneutralen Informationsmodells zur Abbildung der Agrarlandschaft als komplexes System interagierender und sich verändernder Elemente. Ne- ben grundlegenden Objekten der Agrarlandschaft und deren Eigenschaften beschreibt das semantische Datenmodell auch Konzepte zur vollständigen Abbildung raum-zeitlicher Aspekte. Durch Kopplung des semantischen Datenmodells mit komplexen Analysemethoden dient das Datenmodell als interdisziplinäre Integrationsplattform zur umfassenden und tiefgreifenden Analyse der Agrarlandschaft.
  • Konferenzbeitrag
    Smart Rural Areas Data Infrastructure (SRADI) – an information logistics framework for digital agriculture based on open standards
    (41. GIL-Jahrestagung, Informations- und Kommunikationstechnologie in kritischen Zeiten, 2021) Gackstetter, David; Moshrefzadeh, Mandana; Machl, Thomas; Kolbe, Thomas H.
    Agricultural research is embedded in a complex system of dynamically changing and interacting elements and subsystems. This includes stakeholders and data from various disciplines and institutions, and consequently a highly distributed nature of data resources. To solve the challenges coming along within this ecosystem, we introduce an interdisciplinary cooperation and information logistics framework named ”Smart Rural Area Data Infrastructure” (SRADI) for research topics in agricultural sciences. This framework interconnects resources between different stakeholders and platforms, while supplying a basis for integrating both pre-existing, historical and real-time information for physical things. By this, SRADI provides both a quantitative and qualitative enhancement of data foundations for agricultural research.
  • Konferenzbeitrag
    Spatial Data Infrastructure Techniques for Flexible Noise Mapping Strategies
    (Managing Environmental Knowledge, 2006) Czerwinski, Angela; Kolbe, Thomas H.; Plümer, Lutz; Stöcker-Meier, Elke
    The implementation of the EU Environmental Noise Directive puts high demands on the access, availability and integration of numerous thematic and geographical information. Till now, high expenses in time and finances arise for noise mapping because of several technical problems in thematic and geometric data generation and integration. To evaluate the status quo of noise mapping in North Rhine-Westphalia, a state of Germany, a feasibility study was conducted by the Institute for Cartography and Geoinformation of the University of Bonn on behalf of the State Ministry of Environment, Nature Conservation, Agriculture and Consumer Protection of North Rhine-Westphalia. An important result of this study is, that substantial financial savings in the context of environmental noise mapping can be made by the sustainable use of geoinformation in the context of Spatial Data Infrastructures (SDI), especially as a flexible use of geodata for decentralised and centralised noise mapping tasks as well as for small and large-sized areas is required. Applications of web mapping services and international standards of Open Geospatial Consortium and ISO already are in common use in many thematic fields. New challenges are the implementation of web services for 3D building models and cadastral information, which both are required for the environmental noise mapping. In this paper we will discuss how different strategies for environmental noise mapping are facilitated by the consequent application of Spatial Data Infrastructure techniques.
  • Konferenzbeitrag
    Towards a common understanding of digital transformation in agriculture
    (41. GIL-Jahrestagung, Informations- und Kommunikationstechnologie in kritischen Zeiten, 2021) Hannus, Veronika; Kolbe, Thomas H.
    This article presents a literature-based approach to delimitate the topic of ‘digital transformation in agriculture’. We elaborate a Scopus search string and find six clusters that form and describe this new field of research. Most prominent topic clusters are remote sensing, geographic information systems, internet-of-things and image processing, with the last two being most topical. Social science topics seem to be underrepresented or to have not yet established a direct link in this new research area via key terms. Further, European publications reflect the full range of worldwide research, although there is a slightly stronger focus on environmental issues