No abstract

No abstract

No abstract

No abstract

The aim of this work is the analysis of the dynamics in cultural landscapes, focused on the spatial distribution of changes in land cover and landscape patterns, and their possible linkages. These dynamics have been analyzed for the years 1957 and 2000 in a sector of the north of Galicia (NW Spain) characterized with diverse landscapes. Afforestation processes linked to agriculture abandonment and forestry specialization were the main processes observed in the study area, with the exception of the southern mountainous sector that was dominated by ploughing of scrubland for conversion into grassland, reflecting a specialization in livestock production. The structural changes that have taken place in most of the study area were related to the heterogeneity aspects, although the mountainous sectors were characterized by changes in heterogeneity and fragmentation. According to the tests performed, the comparison of the spatial distribution of both dynamics showed a certain statistical significance, reflecting the interrelationship between patterns and processes. This approach could be useful for the identification of areas with similar characteristics in terms of spatial dynamics so as to define more effective and targeted landscape planning and management strategies.

Monitoring of landscape and vegetation dynamics needs cost-effective methods for the analysis and management of large multitemporal datasets. Medium resolution satellite imagery temporal series such as Landsat or Spot, offer attractive possibilities for automatic temporal change detection in broad areas. In the present work we used such datasets for the identification of land cover changes, particularly those involving environmental impacts, during the period 1991-2003 in a Natura 2000 site in the Northern Mountains of Galicia (NW Iberian Peninsula). We targeted changes related to new industrial and intensive agricultural activities that affect natural and semi natural valuable ecosystems as well as dynamics of traditional agricultural systems. We tested different methods, involving the generation of change images from PCA, selective PCA and NDVI differencing on multitemporal compositions of Landsat TM images. The effects of different image radiometric corrections on methods based on NDVI were also assessed. Object oriented classification was used for the classification of continuous change images in change/no change thematic categories. The use of PCA on high dimensionality Landsat Tm bands composition outperformed the rest of the methods and also allowed the removal of atmospheric effects not related to effective land cover changes. Radiometric corrections had low impact on the accuracy of methods based on multitemporal NDVI compositions.