Sorry, you need to enable JavaScript to visit this website.

Satellite estimate of grass biomass in a mountainous range in central Italy

TitleSatellite estimate of grass biomass in a mountainous range in central Italy
Publication TypeArticolo su Rivista peer-reviewed
Year of Publication2003
AuthorsSchino, Gabriele, Borfecchia Flavio, De Cecco L., Dibari C., Iannetta Massimo, Martini S., and Pedrotti F.
JournalAgroforestry Systems
Pagination157 - 162
Date Published2003///
KeywordsLandsat, Range management, Remote sensing, Vegetation indexes, Vegetation mapping

One of the main problems in managing ranges used for extensive pastoralism is the difficulty of obtaining reliable estimates of grass biomass over very large areas. Estimates of grass biomass are useful as an indicator of both available forage and risk of soil erosion. Nevertheless, large scale field measurements are expensive and time-consuming. The use of satellite images may provide a complementary means of estimating grass biomass over very large areas at a reasonable cost. The aim of this study was to test the use of Landsat satellite data for estimating grass biomass in a mountainous range in central Italy used primarily for sheep breeding. During each of four ground campaigns carried out over two years, grass was cut and its biomass measured in 60-90 test plots. Four Landsat images taken simultaneously to the ground campaigns were processed to obtain several vegetation indexes calculated for each ground test plot. The vegetation indexes showed significant correlations with measured grass biomass. The Normalized Difference Vegetation Index (NDVI) provided the most accurate estimate of grass biomass. When data for each of the four ground campaigns were analyzed separately, correlations for early summer campaigns were higher than correlations for late summer campaigns, indicating that when the ratio of dry/green biomass increases, satellite estimate becomes less accurate. Overall, our results show that satellite data can provide a useful source of biomass information for the management of large ranges.


Cited By (since 1996): 14Export Date: 26 August 2010Source: Scopus

Citation Key377