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.
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