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

Grundlagen und Anwendungen von Geoinformationssystemen
mail:
tel: +49 (0) 441 - 7708 - 3248
room: ZSG 106

Books and Papers

Pesch, R.; Schröder, W. (2006): Assessment of metal accumulation in mosses by combining metadata, statistics and GIS.. Nova Hedwigia 82 (3-4), pp. 447 - 466
Schröder, W.; Pesch, R.; Schmidt, G. (2006): Identifying and closing gaps in environmental monitoring by means of metadata, ecoregionalisation and geostatistics. The Unesco biosphere reserve Rhön (Germany) as an example.. Environmental Monitoring and Assessment 114 (1 - 3), pp. 461 - 488
Schröder, W.; Pesch, R.; Schmidt, G. (2006): Identifying and closing gaps in environmental monitoring by means of metadata, ecoregionalisation and geostatistics. The UNESCO biosphere reserve Rhön (Germany) as an example.. Environmental Monitoring and Assessment 114 (1-3), pp. 461 - 488
Pesch, R.; Schröder, W. (2006): Integrative exposure assessment through classification and regression trees on bioaccumulation of metals, related sampling site characteristics and ecoregions.. Ecological Informatics 1 (1), pp. 55 - 65
Pesch, R.; Schröder, W. (2006): Mosses as bioindicators for metal accumulation: Statistical aggregation of measurement data to exposure indices.. Ecological Indicators 6,pp. 137-152

Presentations

Pesch, R. ; Schröder, W. ; Englert, C. : Classification and Regression Trees Relating the Metal Accumulation in Mosses with Site Specific and Regional Land Characteristics. 19th Task Force Meeting UNECE ICP Vegetation, Caernarfon, UK, Januar 2006
Pesch, R. ; Schröder, W. : Marine Geo-Information System for Visualisation and Typology of the Sean Floor of the North Sea . "International Conference and Annual Meeting ""System Earth - Biosphere Coupling"" , Erlangen", September 2005
Pesch, R. ; Pehlke, H. ; Schröder, W. : Predictive Benthic Habitat Mapping in the North Sea Using GIS and Statistical Methods . Enviroinfo 2005, Masaryk University - Centre of Biostatics and Analyses, Brno, September 2005
Pesch, R. ; Schröder, W. ; Pehlke, H. ; Busch, M. : Predictive Marine Habitat Mapping by Means of GIS, Geostatistical Methods and Classification and Regression Trees. BMBF-Abschlussymposium Förderschwerpunkt Geotechnologien im Rahmen der GI-Tage 2005, Westfälische Wilhelms-Universität Münster, Juni 2005
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


Entwicklung eines webbasierten Geoinformationssystems über frühere und aktuelle ländliche Bodenordnungsverfahren für den Amtsbezirk Oldenburg (2021/8)
supervisors

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

Frederik Meiners, M.Sc.

Entwicklung einer GIS-basierten teilautomatisierten Datenüberprüfung zur Dokumentation des FTTH-Ausbaus der EWE NETZ für die Glasfaser NordWest (2021/8)
supervisors

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

Dipl-Ing. Alfred Wegener

cooperation

EWE NETZ GmbH

Prädiktive Modellierung des Vorkommens von Lanice conchilega im Schleswig-Holsteinischen Wattenmeer auf Basis von Sidescan-Mosaiken und maschinellen Lernverfahren (2021/8)
supervisors

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

Prof. Dr. Arbizu Pedro Martinez

Automatisierung der Glasfaserausbaulänge im Bereich der Neubaugebiete anhand des Programmtools ArcGIS (2021/8)
Feasibility study for (semi-)automatic detection of red deer from RGB aerial images using OpenCV without training data (2021/7)
supervisors

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

Dipl-Ing. Ulrich Franke