Vegetation Fraction Images Research Articles

Retrospective studies of grazing-induced land degradation: A case study in central Crete, Greece

Although it is well known that livestock husbandry has become more prevalent in Crete, Greece, during the last two decades, it is not well understood how grazing pressure differs spatially and how it influences grazed rangelands over time. To enhance the understanding of spatio-temporal degradation processes, a 20-year time series of Landsat Thematic Mapper and Multi-Spectral Scanner data is analysed. A set of vegetation fraction images is derived, based on a rigorous pre-processing scheme and linear spectral unmixing. Patterns of vegetation degradation, stability and regeneration are subsequently mapped by means of a trend analysis. It can be concluded that about 40% of the central Cretan rangelands show a declining trend in vegetation cover between 1977 and 1996. A deeper understanding of the underlying driving forces can be achieved through integrating remote sensing-derived information with other geoinformation sources. A comparison between local stress factors and vegetation development reveals that degradation processes are most evident when boundary conditions are favourable. It is, hence, assumed that increased grazing pressure is a major driving force for decreasing vegetation cover in the long term.

NOAA-AVHRR data processing for the mapping of vegetation cover

The NOAA-AVHRR images have been widely used for global studies due to their low cost, suitable wavebands and high temporal resolution. Data from the AVHRR sensor (Bands 1 and 2) transformed to the Normalized Difference Vegetation Index (NDVI) are the most common product used in global land cover studies. The purpose of this Letter is to present the vegetation, soil, and shade fraction images derived from AVHRR, in addition to NDVI, to monitor land cover. Six AVHRR images from the period of 21 to 26 June 1993 were composed and used to obtain the above mentioned products over Sa o Paulo State, in the south-east of Brazil. Vegetation fraction component values were strongly correlated with NDVI values ( r 0.95; n 60). Also, the fraction image presented a good agreement with the available global vegetation map of Sao Paulo State derived from Landsat TM images.