Application of PALSAR data to classify vegetation in an anthropogenically affected wetland area in Central Spain (Las Tablas de Daimiel)

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Rhodes, Greece, Application of PALSAR data to classify vegetation in an anthropogenically affected wetland area in Central Spain (Las Tablas de Daimiel) Thomas Schmid 1, Magaly Koch 2, Jesús Solana 3 and Jose Gumuzzio 4 1 CIEMAT, Av. Complutense 22, 28040, Madrid, Spain. 2 Centre for Remote Sensing, Boston University, Boston, MA, USA. 3 Universidad Complutense de Madrid, Faculty of Geography and History, 28040 Madrid, Spain. 4 Universidad Autónoma de Madrid, Science Faculty, Madrid, Spain. thomas.schmid@ciemat.es Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas

Presentation overview Problem statement Wetland project Objectives Study area Methodology Data aquisition Preliminary results Conclusion

Problem statement Wetlands in semi-arid regions are complex and vulnerable ecosystems and are especially important in maintaining and controlling the environmental quality and biodiversity. These areas are threatened mainly by human-induced activities causing rapid processes of degradation with loss of wetland surface. Las Tablas de Daimiel is a National Park included in the UNESCO Man and Biosphere Reserve, Special Protection Area for Birds and Ramsar Convention lists. This wetland is a refuge for endemic and threatened species of flora and fauna, but human induced changes leads to loss of characteristic vegetation and large colonies of aquatic birds. Degradation indicators include the presence of nitrophilous and invasive species; reduction in the surface area of Great Fen-Sedge; increase of halophytic vegetation and eutrophic conditions in the surface water.

Wetland Project This wetland project is within the framework of the Spanish National project Multidisciplinar analysis of geoindicators of degradation in protected wetlands Las Tablas de Daimiel National Park (CGL22005-06458-C02-02/HID). Climate and human control on the degradation of protected wetlands (Las Tablas de Daimiel National Park) PI: Dr. Rosa Mª Mediavilla López Geoindicators of wetland degradation processes in Mediterranean environments of Spain: Multisensor Remote Sensing approach. PI: Dr. Jose Gumuzzio. Applications of ALOS in Arid/Semiarid Land Studies: Land Degradation, Natural Hazards and Water Resources. Japan Aerospace Exploration Agency (JAXA) as part of the ALOS user agreement (ALOS-RA-81). PI: Dr. Magaly Koch Remote sensing of climate change effects on ecology and biogeochemistry of macrophyte communities in Las Tablas de Daimiel National Park: designing adaptative strategies and monitoring programs for environmental conservation. PI: Dr. Salvador Sánchez Carrillo.

Integrated approach Field sampling Laboratory Field classification Field spectroradiometry Regional study

Multisensor Remote Sensing Optical and microvave sensors Satélite EO-1 NASA ALI Hyperion Proba1/ CHRIS ALOS AVNIR2 PALSAR Landsat 5 Landsat 7 RADARSAT-2 ASTER

Objective The aim of this work is to investigate the capability of ALOS PALSAR in characterizing and monitoring dynamic ecosystems by utilizing a wetland area in Central Spain for which ample information already exists. Specific objectives within the wetland area: Detection of wetland plant communities and invasive vegetation species. Mapping of open water lamina and flooded vegetated areas. Assessing the capacity of PALSAR data to determine the spatial distribution of these different components.

Study area Madrid W N S E Las Tablas de Daimiel 434 0000 Cigüela River 433 0000 Guadiana River Daimiel 0 5 km 43 0000 44 0000 45 0000

Las Tablas de Daimiel National Park Rhodes, Greece Climate: Temperate-cold continental The area is in a depressed basin filled with Tertiary sediments, mainly of limestone and calcareous clays. Water sources: (1) Guadiana River (freshwater) and Cigüela River (brackish) (2) Upwelling groundwater from underlying karstic aquifer. Diminishing water level. Areas with temporal flooding. Crop cultivation with intensive irrigation surrounding wetlands. Salt efflorescence.

Wetland vegetation 2005 2007 Cladium mariscus Phragmatis communis Rush communities Quercus ilex Other tree species Annual vegetation Vegetation free Saline areas Island areas

Methodology Data acquisition SAR, Hyperspectral and multispectral Wet (spring) and dry (autumn) season Calibration procedures System, atmospheric, radiometric and geometric Surface caracterisation Hyperspectral (endmember) SAR (polarimetric) Data processing Unsupervised classification Supervised Ground-truth data Field campaigns (spectral library) Surface sample analyses (sediment, soil, water) Monitoring SAR Multispectral (ASTER, ETM+) Database management Georeferenced (field data, EO data) Thematic maps

PALSAR and AVNIR2 data acquisition PALSAR Quad pol 3 May 2007 PALSAR Dual pol 11 June 2007 AVNIR2 5 November 2007

Preliminary results Sinclair decomposition Vegetation index classification W N S E W N S E NDVI Max. 4335 000 4335 000 Min. 43 30 000 0 5 km 43 30 000 0 5 km 435 000 4 40 000 435 000 4 40 000

Preliminary results W N S E W N S E 4335 000 4335 000 HH HV 43 30 000 0 5 km 43 30 000 0 5 km 435 000 4 40 000 435 000 4 40 000 W N S E W N S E 4335 000 4335 000 43 30 000 VH VV 0 5 km 43 30 000 0 5 km 435 000 4 40 000 435 000 4 40 000

Conclusions PALSAR offers several technical advantages to better discriminate wetland features (vegetation structure and wetland conditions). Due to dry conditions at present in the wetlands, it has not been possible to study the effect of shallow water bodies or aquatic plants. Data availability during wet and dry periods. Limitations with the PALSAR mode 1.5 data. Mode 1.1 would improve the possibility to discriminate wetland features. Geocoding and mode 1.1 necessity This work is ongoing and further application of PALSAR and AVNIR2 will be carried out together with data obtained from other sensors. Monitoring the wetland by integrating ALOS data to historical EO data.

Acknowledgements Many thanks go to the Jaxa team for the data management and organisation of the ALOS Palsar and AVNIR2 data. Further thanks go to Dr. Santos Cirujano for the identification and distribution of the vegetation. Funding of the National Project (CGL22005-06458-C02-02/HID) by the Spanish Ministry of Education and Science.