Julia Reschke 1 & Christian Hüttich 2

1. Mapping Coastal Mediterranean Wetlands using Sub-pixel Spectral Signatures and Multi-temporal Landsat Data Julia Reschke1 & Christian Hüttich2 Motivation Methods – Fuzzy approaches for complex landscapes Wetland ecosystems are affected by short periodic changes in vegetation dynamics and hydrological patterns due to alterations in the local and regional climate. Mediterranean wetlands are affected by distinct land use pressures in recent decades caused by agriculture intensification, urban growth, and increasing tourism infrastructure. This requires a frequent monitoring. Landsat data is widely used for this purpose, freely available, but for mapping highly heterogeneous wetland systems, it is often considered to be insufficient in terms of spatial resolution. Sub-pixel signatures of RAMSAR wetland types in the Menderes Delta and Lake Bafa test sites in Turkey were extracted based on in-situ data and Landsat time series imagery, and major RAMSAR wetland classes were mapped. The study region is focused on the southern part of Aegean coast in the west of Turkey. The landscape is dominated by agricultural fields, forests and semi natural areas. Different wetland types can be found in plains, attached to inland water bodies or in coastal deltas, such as the Great Menderes Delta National Park, characterized by seasonally inundated mudflats with halophytes, reed beds and shrublands. • Multi-temporal Landsat acquisitions capture the seasonal cycling of different wetland types. • Training data were collected on Landsat sub-pixel level to integrate fractional land cover information in the model training process. • Wetland potential maps were generated for each wetland class using Random Forest regression. • Google Earth screenshot (SPOT-5, river with adjacent agricultural land and a built dam). • High resolution manually digitized class-shape on Landsat ETM+ (5-4-3). • Class raster with percentage class membership of the wetland class Rivers & Channels (black 100% across medium grey 50% to light grey 0%, white: other land cover). Results – From likeliness maps to RAMSAR-based wetland maps • Regression-based layers of the occurring RAMSAR-defined wetland classes enable the most realistic description of the spatial distribution of the wetland components. • Mudflats • Marsh-land • Water bodies • Rivers & Channels Continuous map of RAMSAR wetland types in the Menderes Delta. Overall accuracy = 79.02 % Discussion – Towards a multi-scale concept in wetland mapping • Applying the regression models on Landsat time series imagery enables the transfer of local scale sub-pixel training data information to a minimum mapping unit of 30 m to finally retrieve fractional land cover information in a continuous field land cover map. • The use of probability-based maps of wetland type distribution accounts for a realistic spatial representation of the heterogeneous landscape structure and an appropriate cartographic representation of spatio-temporally dynamic land cover types. • Operational monitoring of wetlands has to go beyond the “classic” concept of land cover mapping as it has been done in recent wetland monitoring projects. The application of the multi-scale mapping concept from very high resolution model training to high resolution mapping with a continuous legend is critical for complex wetland ecosystems. 1Remote Sensing Unit University of Wuerzburg Department ofGeography julia.reschke@gmx.net 2 Friedrich-Schiller-University Jena Jena, Germany christian.huettich@uni-jena.de Contact