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Teledectectie van estuariene getijdeplaten voor het karteren en modelleren van benthische ecologie
www.onderzoekinformatie.nl/nl/oi/nod/onderzoek/OND1305062

Engelstalige titel: Remote sensing of estuarine intertidal flats for mapping and modelling benthic ecology
Referentie nr.: PRS1263397
Periode: Januari 2004

Thesaurustermen: Benthos; Ecologie; Teledetectie; Wadden; Slikken
Geografische term: ANE, Nederland, Westerschelde [Marine Regions]
 Instituten 

Instituten (2)  Top 
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Aard- en Levenswetenschappen (NWO/ALW), meer, secretariaat
  • Koninklijk Nederlands Instituut voor Onderzoek der Zee; NIOZ Yerseke, meer

Abstract
Tidal flats have particular significance for estuarine ecosystems, as they accommodate a large and diverse biological community. This includes macrozoobenthos, which plays an important role in estuarine food webs, and is used as an indicator for estuarine ecosystem health. Mapping and monitoring benthic macrofauna distribution from insitu measurements is, however, hampered by high sampling costs, resulting in too few sample points. Our research in the Westerschelde has shown that the occurrence of macrozoobenthos can be predicted from a set of biophysical parameters (including sediment properties and benthic algal biomass). This, in turn, requires high resolution, synoptic information on these variables. In the proposed study, algorithms will be developed for mapping the spatio-temporal distribution of key parameters (i.e. median grain-size, silt content, surface roughness, benthic algal biomass and primary production) using spaceborne radar and optical remote sensing, airborne hyperspectral remote sensing, and ground truthing. A rigorous intercomparison of remote sensing techniques to extract the biophysical parameters will be carried out. The use of synergy of data and information derived from different sensors will be explored to optimise retrieval of the parameters. The results are related to an extensive macrozoobenthos data set using (geo)statistics, allowing the development of predictive (spatially-explicit) models for macrozoobenthos distribution.

This work is of interest to coastal zone managers, requiring information on macrofauna distribution, and techniques and algorithms to define their habitat (for e.g., ecological impact assessments), and for fisheries. In addition, sediment and surface roughness maps that will be produced can support wave and hydrodynamical modelling studies.

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