Books and Papers

Gutow, L.; Günther, C.-P.; Ebbe, B.; Schückel, S.; Schuchardt, B.; Dannheim, J.; Darr, A.; Pesch, R. (2020): Structure and distribution of a threatened muddy biotope in the south-eastern North Sea. Journal of Environmental Management, Volume 255, 1 February 2020, 109876 , doi: 10.1016/j.jenvman.2019.109876 , Weblink
Burgues, MF; Lenzi, J.; Machín, E; Genta, L; Teixeira de Mello, F (2020): Temporal variation of Kelp Gull's (Larus dominicanus) diet on a coastal island of the Rio de la Plata Estuary, Uruguay: refuse as an alternative food source. Waterbirds 43(1): 65-74 , doi: https://doi.org/10.1675/063.043.0107 , Weblink
Lanz, P.; Marino, A.; Brinkhoff, T.; Köster, F.; Möller, M. (2020): The InflateSAR Campaign: Evaluating SAR Identification Capabilities of Distressed Refugee Boats. Remote Sensing 2020, Vol. 12, 3516 , doi: 10.3390/rs12213516
Chizhova, M.; Popovas, D.; Gorkovchuk, D.; Gorkovchuk, J.; Hess, M.; Luhmann, T. (2020): Virtual terrestrial laser scanner simulator for digitalization of teaching environment: Concept and first results. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 91–97 , doi: 10.5194/isprs-archives-XLIII-B5-2020-91-2020 , Weblink
Werner, T.; Brinkhoff, T. (2020): Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles. AGILE GIScience Ser., 1, 21 , doi: 10.5194/agile-giss-1-21-2020

Presentations

Pesch, R. ; Breckling, B. ; Schmidt, B. : Transformation und Strukturwandel im ländlichen Raum Nordwestdeutschlands - Reallabore in Marsch, Moor, Geest und Mee(h): Vorstellung des 4N-Verbundprojektes. Klimamarkt auf dem Jasperhof, Westerstede, August 2023
Elbeshausen, M. : GeoVisual Analytics zur intuitiven Szenarioplanung im Kontext der geodatenbasierten Wärmeleitplanung. GI_Salzburg23, Juli 2023
Koch, S. ; Elbeshausen, M. : Wärmeleitplanung Nordwest am Beispiel von Edewecht. OLEC Energy Week 2023: wärme:tauscher - Kommunale Wärmeplanung gemeinsam vorantreiben!, Juni 2023
Lanz, P. : Automatic Refugee Inflatable Detection with Polarimetric SAR.. PolINSAR 2023, Toulouse, Juni 2023 Weblink
Pesch, R. ; Rothe, M. ; Bildstein, T. ; Heinicke, K. : Spatial Modelling of Soft Bottom Biotopes for the German Exclusive Economic Zone of the North Sea by Machine Learning Algorithms. 26th AGILE conference on Geographic Information Science, Delft, Netherlands, 13-16 June 2023, Juni 2023

Projects

funded by: Bundesministerium für Bildung und Forschung
Over 70% of German households are supplied with heat through fossil fuels (natural gas, oil). Therefore, some federal states have legally regulated Municipal Heat Planning (MHP). Additionally, a federal law on heat planning came into ... more
funded by: zukunft.niedersachsen
There are hundreds of thousands of artefacts in German museums that were brought to Europe during the colonial era as a result of wars, looting or trade. The history of these objects - where they came from, what they were used for and who once owned ... more
funded by: Bill & Melinda Gates Foundation
The WorldPop project aims to produce grid-based population estimates up to 2030 broken down by sex and age groups. The overall project is led by Prof. Andy Tatem of the University of Southampton. With this framework, IAPG is responsible for the devel... more

Bachelor & Master Theses


Untersuchung der Genauigkeit und Wirtschaftlichkeit der „Visuellen Positionierungstechnologie“ des GNSS Rovers Leica GS 18 I bei der Gebäudeeinmessung in der Kastasterverwaltung (2022/)
supervisors

Prof. Harry Wirth

Janfred zu Jeddeloh

Auswirkung von Gebäudeabbruchkosten auf Immobilienkaufpreise (2022/)
supervisors

Prof. Dr.-Ing. Hero Weber

Dipl-Ing. Markus Bohling

Implementation of a potential area analysis for floating offshore wind turbines in Scotland using a Geographical Information System (GIS) and the Analytical Hierarchy Process (AHP) (2021/10)
supervisors

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

William Gibbs, M.Sc.

cooperation

Vattenfall

Explorativ statistische Analyse benthosbiologischer Eigenschaften sublitoraler Sandbänke in der Nordsee (2021/10)
Untersuchung zum Einsatz von Methoden des maschinellen Lernens auf Fernerkundungsdaten in Flurbereinigungsverfahren (2021/9)