Characterizing Land Use Change in a Complex Semi-arid Landscape by Combined Assessment of Land Transformations and Modifications

摘要

Mapping land use and land cover is one of the most frequently addressed topics in remote sensing, owing to the importance of such information for a wide range of applications that range from local land management to global climate models. Local to regional scale data, such as those acquired by the Landsat sensors, provide long-term monitoring capacities along with a scale that is consistent with sub-national land management. These data allow mapping land use and landing cover for a sequence of dates and comparing results both in terms of overall rates as well as in a spatially explicit manner. Yet, it is now accepted that for many environmental applications, the modification of ecosystems - even if in categorical terms they remain stable - may prove equally important than transformation from one land use type to another. Consequently, adapted data processing and mapping strategies are need to consider both types of change. Also, "translating" the derived information is essential to comply with assessment frameworks such as "ecosystem services and functions", which may eventually form the basis for assessing trade-offs associated with land-use decisions. In this study, we report first steps towards this goal and present a combined approach for enhanced land use and land cover mapping based on a rigorous radiometric data processing scheme It incorporates a hybrid unsupervised classification approach using available reference data for histogram based class assignment, and a multi-date spectral unmixing approach to further differentiate natural and semi-natural vegetation classes. Results are discussed against the background of major socio-economic trends and physical processes that are typical for many countries of the European Mediterranean.