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

T. Svoray, M. Shoshany

Research output: Contribution to journalConference articlepeer-review

Abstract

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 Landsat 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 prove 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 planners and decision makers.

Original languageEnglish
Pages (from-to)81-86
Number of pages6
JournalEuropean Space Agency, (Special Publication) ESA SP
Issue number475
StatePublished - 1 Jan 2002
Event3th International Symposiumon Retrieval of Bio- and Geophysical Parameters from SAR Data for Land Applications - Sheffield, United Kingdom
Duration: 11 Sep 200114 Sep 2001

Fingerprint

Dive into the research topics of 'Merging unmixed Landsat TM data in a semi-empirical SAR model for the assessment of herbaceous vegetation biomass in a heterogeneous environment'. Together they form a unique fingerprint.

Cite this