Publication Date:
2000-06-01
Description:
Mediterrranean regions are characterized by high spatiotemporal heterogeneity of vegetation patterns. Understanding the dynamic nature of these environments requires detailed data for wide regions regarding changes in their phyto-ecology, biomass and productivity. This article assesses the current status of satellite remote sensing in this field of application. Mapping the five main life-forms (physiognomic classes) in Mediterranean regions (forests, woodlands, scrub, dwarf shrubs and herbaceous growth) has attracted major attention in recent years. Methodologies developed for this purpose are based on the spectral, temporal and spatial (textural) information domains provided by satellite data. Wide regional vegetation mapping was achieved using phenological classification of vegetation indices derived mainly from NOAA AVHRR images. More detailed mapping was conducted with multispectral techniques in local areas using mainly Landsat TM images. Assessments of multispectral and multi-temporal categories have shown limitations in their applicability over wide regions due mainly to the heterogeneity of Mediterranean regions. This heterogeneity cannot be regarded as a simple mixing of life-forms over large areas but, rather, the formation of transitional zones of varying mixtures resulting from disturbance and recovery cycles. Productivity and biomass monitoring has been found to be an active methodological development due to the introduction of new off-nadir viewing sensors in the visible and infrared spectral bands, and because of the development of methodologies for the retrieval of biophysical information from Synthetic Aperature Radar (SAR) data. Studies of ecosystem evolution using satellite data were conducted mainly in the fields of fire disturbance and desertification. Further progress in the remote sensing of Mediterranean vegetation ecology requires a better synergy of sensors, methods and ancillary data.
Print ISSN:
0309-1333
Electronic ISSN:
1477-0296
Topics:
Geography
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