ePIC

Detection and quantification of marine vegetation by airborne hyperspectral remote sensing: case study Helgoland

Edit Item Edit Item

General Information:

Citation:
Bartsch, I. , Oppelt, N. , Bochow, M. , Schulze, F. , Geisler, T. , Eisenhardt, I. , Nehring, F. and Heege, T. (2011): Detection and quantification of marine vegetation by airborne hyperspectral remote sensing: case study Helgoland , The Future of Operational Oceanography, Hamburg, Germany, 25 October 2011 - 27 October 2011 .
Cite this page as:
Contact Email:
Download:

Supplementary Information:

Abstract:

Sublitoral marine forests are functionally diverse ecosystems along cold-temperate to polar coastal rocky shores world-wide. They provide habitat and shelter for marine animals and plants and are of great economical and recreational importance. Submarine forests provide a primary production comparable to terrestrial virgin forests and serve as indicators for environmental change (e.g. eutrophication, sedimentation) in international programs such as the European water frame work directive. As these ecosystems are endangered due to global change, the future recording of large-scale changes will be facilitated by operational satellite based monitoring. Within the frame-work of two research projects (KelpMAP and KlamMAS) the feasibility and limits of airborne and satellite borne hyperspectral remote sensing for classification and quantification of submarine forests is worked out in a case study around the North Sea island of Helgoland. While KlamMAS works on the small-scale (1-2m range) classification of diverse submarine species, KelpMAP operates on satellite scale (30 m) and intends to develop tools for the German hyperspectral sensor EnMAP to be launched in 2014. Both projects are developing semi-automatic techniques to enable a spatio-temporal monitoring of temperate submarine forests. Firstly the project KelpMAP focuses on the spectral mixture of macro-algae, the estimation of the coastline using bathymetric maps and spectral reflectance characteristics and the suitability of CHRIS-PROBA scenes for the detection and classification of kelps. In addition, the project KlamMAS deals with a water column correction processed by the module MIP (Modular Inversion Program) and a new classification attempt of sublitoral algal communities at Helgoland. Data basis are several hyperspectral scenes taken with the sensor AISA Eagle (400-970 nm, 3nm band resolution) during summer 2010 and 2011 accompanied by extensive ground-truth campaigns and scenes of the satellite borne sensor CHRIS-PROBA. Target is the entire submarine forest at Helgoland approx. covering 2000 ha. We expect to develop practical algorithms for algae and kelp estimation and will present first project results.

Further Details:

Imprint
AWI
Policies:
read more
OAI 2.0:
http://epic.awi.de/cgi/oai2
ePIC is powered by:
EPrints 3