Logo des Repositoriums

Auflistung nach Autor:in "Pesch, Roland"

1 - 4 von 4
  • Konferenzbeitrag
    MarGIS Marine Geo-Information-System for Visualisation and Typology of Marine Geodata
    (Informatics for Environmental Protection - Networking Environmental Information, 2005) Jerosch, Kerstin; Schlüter, Michael; Pesch, Roland; Schröder, Winfried; Köberle, Andreas; Vetter, Lutz
    MarGIS intends the combination of Geo-Information-Systems (GIS), research data, and multivariate geostatistical techniques for characterization and identification of distinct provinces at the seafloor of the North Sea. Such a typological approach, the analysis of classification based on types, is one prerequisite for management issues related to coastal seafloor. It provides a frame work for improved application of large environmental data sets, allows enhanced visualization of multiple information layers, and supports modeling of temporal and spatial interrelations of coastal and ocean regions. To tackle the problem of presentation of large data sets MarGIS uses a web-based viewer which allows a clear visualisation of the information for the general public. The viewer allows a dynamic actualisation and access of metadata and additional information.
  • Konferenzbeitrag
    Predictive Benthic Habitat Mapping in the North Sea using GIS and Statistical Methods1
    (Informatics for Environmental Protection - Networking Environmental Information, 2005) Pesch, Roland; Pehlke, Hendrik; Schroeder, Winfried
    The goal of this article is to introduce a methodological concept suitable to identify ecological sea floor provinces in the North Sea. The approach consists of two main working steps: (1) geostatistical analysis of biotic and abiotic measurement data and (2) calculation of sea floor provinces by means of multivariate statistics and GIS-techniques. From bottom water measurement data on salinity, temperature, silicate and nutrients as well as on grain size surface maps are calculated via geostatistical methods. At first, the autocorrelation structure is examined and modelled by variogram analysis. The variogram models are then used to calculate raster maps by applying ordinary point kriging. These raster maps are then intersected with data on benthic communities available at 182 sites within and near the German Exclusive Economic Zone (EEZ). Further, Classification and Regression Trees (CART) is applied to derive a decision tree for the occurrence of these communities. This decision tree is applied on the geostatistically estimated raster data to predict benthic habitats within the study area.
  • Konferenzbeitrag
    Statistical and Geoinformatical Instruments for the Optimisation of the German Moss-Monitoring-Network
    (Managing Environmental Knowledge, 2006) Pesch, Roland; Schröder, Wilfried
  • Konferenzbeitrag
    Synthesis of Sampling Site and Metal Specific Bioaccumulation Data by Classification and Regression Trees
    (Informatics for Environmental Protection - Networking Environmental Information, 2005) Pesch, Roland; Schröder, Winfried
    The UNECE Heavy Metals in Mosses Surveys provide exposure data (PEC) for ecotoxicological risk assessments by measuring the accumulation of metals in mosses. The article focuses on the synthesis of data on the bioaccumulation of metals in the German campaign 2000 by Classification and Regression Trees (CART). Within the framework of the European Metals in Mosses Surveys, moss samples were taken at 1028 sites. At each of these sites the mosses were analysed with respect to 20 metal elements. The sampling, the ecological characteristics of the sampling sites, and the chemical analysis are documented in a metadata base. An ecoregionalisation of Germany was calculated with data on natural vegetation, altitude, soil texture and climate by means of CART. The ecoregions are intersected with site specific multi-metal bioaccumulation indices calculated from the measurement data in a GIS environment. These indices are calculated by means of percentile statistics and integrate the concentrations of Cr, Cu, Fe, Ni, Pb, Ti, V and Zn in terms of ordinal scaled indices for atmospheric metal accumulation. To synthesize metadata, multi-metal bioaccumulation indices and the ecoregionalisation CART-models are calculated for each campaign. The presented approach helps to assess the multivariate correlations of metal bioaccumulation with site specific and ecoregional characteristics in a comprehensive and holistic manner over space and metal species. This is of importance for the environmental reporting within the framework of the national and international environmental information systems.