Merging unmixed Landsat TM data in a semi-empirical SAR model for the assessment of herbaceous vegetation biomass in a heterogeneous environment

Details Merging unmixed Landsat TM data in a semi-empirical SAR model for the assessment of herbaceous vegetation biomass in a heterogeneous environment Merging unmixed Landsat TM data in a semi-empirical SAR model for the assessment of herbaceous vegetation biomass in a heterogeneous environment

Jan 2002

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002esasp.475...81s&link_type=abstract

In: Proceedings of the Third International Symposium on Retrieval of Bio- and Geophysical Parameters from SAR Data for Land Appl

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Agriculture, Land Cover

Scientific paper

In this paper we suggest a remote sensing methodology for herbaceous Areal Aboveground Biomass (AAB) estimations in the heterogeneous Mediterranean system. The methodology developed is based on a modification of the water-cloud model to the conditions of mixed environments including shrub, dwarf shrub and herb formations. The use of the Green leaf biomass Volumetric Density (GVD) as a canopy descriptor and the use of soil and vegetation fractions from Lansat TM data facilitated improvements in the application of the water-cloud model to the study area and enabled successful reproduction of the backscatter from the Mediterranean vegetation formations and the derivation of AAB values of herbaceous vegetation. The model was applied to the entire image domain and the AAB layers achieved probe capable of representing spatio-temporal patterns of changing AAB. Based on these results, the methodology provided in this paper lays a basis for the derivation of important and more advanced ecological and range management parameters, such as primary production, carrying capacity and dominance in the areal domain. The use of satellite images for quantitative mapping of these parameters may contribute significantly to our understanding of Mediterranean to semi-arid ecosystems and could provide an efficient tool for rangeland plannars and decision makers.

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