The LADAMER project is to provide an assessment of the degradation status of Mediterranean lands on small scales, and the identification of Hot Spot areas subject to high desertification and land degradation risk. LADAMER aims at supplying products relevant to national and international institutional end-users. The approach is based on an integration of expertise in landscape ecology and soil science, remote sensing, spatial analysis and integrated land use modelling. Different models and techniques that have already proven their validity on local to sub-regional scale will be modified to permit their application on regional scales. The project will use existing data on European land-use, soils and terrain elevation, climatic recordings used for agro-climatic modelling on European scale, remote sensing data archives from the SPOT-VEGETATION and AVHRR systems, and regionalised socio-economic data.
[b]Objectives of LADAMER[/b]
The prime objectives of the project are :
* A first objective of the project is to assemble in a consistent and well-documented database the base data required for the LADAMER project. These data largely exist but are scattered across various European and international institutions.
A second objective is to produce a regional assessment of the land degradation status in Mediterranean Europe, which is based on an existing theoretical framework where the remotely sensed vegetation density is compared to a model-determined reference density.
Regional change maps of vegetation density and land-use classes over time will be derived from remote sensing approaches to evaluate their performance for early warning and monitoring purposes.
The last objective is to couple the existing data, information, knowledge and models into an integrated assessment model capable of integrating the different process domains with respect to early warning and environmental surveillance. The derived products will be validated.[/c]
[b]Description of the work[/b]
The project encompasses two separate phases which are imposed by the overall GMES requirements and timing of activities.
The first phase will start with the procurement and processing of considerable volumes of geoscientific, socio-economic and remotely sensed data covering the Mediterranean basin. The establishment of this unified database will provide the basis for the forthcoming analysis and the production of a regional land degradation map for the Mediterranean member states of the European Communities, to be provided after 12 months at the end of the first phase. The analysis of the remote sensing data archives will produce a continuous mid-term vegetation density map, and the first version of maps showing multi-annual trends in vegetation dynamics and discrete land-use-change classes. Together with the processed geodata layers and spatialised socio-economic variables this information will flow into the concept model to produce the land degradation assessment supplied at the end of the first phase. This product will be thoroughly documented. Its instrumental, conceptual and data induced shortcomings will be specified and submitted as part of a report with recommendations relative to the GMES objectives and work programme.
The second phase will be devoted to a more in-depth validation, the integration of additional or improved data layers, and the evaluation of advanced methodological options to upgrade the quality and information content of the first-phase-models and -products. The accuracy analysis of maps and ecological model components will involve error propagation analysis and ground verification in specific areas; the model development will see the evaluation of more sophisticated versions of the constrained cellular automata approach capable of supporting environmental monitoring, hot spot detection, and early warning. Last but not least the project will, together with the presentation of its second generation products and reports, take care of an adequate dissemination within national and international institutions.
The work in the LADAMER project is carried out by a consortium consisting of: Remote Sensing Department
Of the University of Trier, ), Directorate General Joint Research Centre (JRC), Departamento de Geografia e Planeamento Regional da Universidade Nova de Lisboa, and RIKS.