Prof. Dr. rer. nat. habil. Roland Pesch

Mitglied Institutsvorstand
Professur Grundlagen und Anwendungen von Geoinformationssystemen

mail:
tel: +49 (0) 441 - 7708 - 3248
room: ZSG 106

Books and Papers

Pesch, R.; Schröder, W. (2006): Statistical and geoinformatical instruments for the optimisation of the German moss-monitoring network.. Tochtermann, K.; Scharl, A. (eds.): Managing environmental knowledge. Proceedings 20th International Conference on Informatics for Environmental Protection, September 6-8, 2006 Graz, Austria: pp. 191 - 198

Presentations

Pesch, R. ; Pehlke, H. ; Schröder, W. : Marine Habitat Mapping within the German EEZ by Means of GIS, Geostatistics and Classification and Regression Trees. Meeting of the Working Group on Marine Habitat Mapping (WGMHM), Alfred-Wegener-Institut Bremerhaven, Juni 2005

Projects

funded by: Europäische Union (EU)
Given the EU Biodiversity Strategy 2030, Protect Baltic aims to evaluate and optimise the existing network of marine protected areas in the Baltic Sea and thus makes a positive contribution to biodiversity and the protection of marine ecosystems. Tog... more
funded by: Niedersächsisches Vorab
Transformation and structural change in rural areas mean changes in space and time. Such spatiotemporal data is to be managed and processed by our “Geo-Toolbox”. It uses digital technologies such as databases and geographic information systems &#... more

Bachelor & Master Theses


Erkennung eulitoraler Muschelbänke im Niedersächsischen Wattenmeer: Ein Vergleich von Deep-Learning-Modellen zur semantischen Segmentierung von Luftbildern (2025/10)
GIS-basiertes Flächenscreening für ökologische Solarparks unter Berücksichtigung von Biotopverbundstrukturen in Niedersachsen (2025/10)
Analyse benthischer Lebensgemeinschaften und ihrer räumlichen Muster im Elbe- Urstromtal der Nordsee mittels maschineller Lernverfahren (2025/10)
Application of Geographic Information Systems to Analyse Landscape-Ecological Effects of Virtual Fencing in Grassland Ecosystems (2025/9)
supervisors

Prof. Dr. Roland Pesch

Dr. Matthew Hiron

Ensemble Machine Learning Ansätze zur Prädiktion benthischer Arten in der Ostsee (2025/9)