Herbaceous biomass retrieval in habitats of complex composition: A model merging SAR images with unmixed landsat TM data

Tal Svoray, Maxim Shoshany

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

A remote sensing methodology for herbaceous areal above-ground biomass (AAB) estimation in a heterogeneous Mediterranean environment is presented. The methodology is based on an adaptation of the semiempirical water-cloud backscatter model to complex vegetation canopies combined with shrubs, dwarf shrubs, and herbaceous plants. The model included usage of the green leaf biomass volumetric density as a canopy descriptor and of cover fractions derived from unmixing Landsat Thematic Mapper image data for the three vegetation formations. The inclusion of the unmixed cover fractions improves modeling synthetic aperture radar backscatter, as it allows separation between the different radiation interaction mechanisms. The method was first assessed with reference to the reproduction of the backscatter from the vegetation formations. In the next phase, the accuracy of AAB retrievals from the backscatter data was evaluated. Results of testing the methodology in a region of climatic gradient in central Israel have shown a good correspondence between observed and predicted AAB values (R2 = 0.82). This indicates that the methodology developed may lay a basis for mapping important and more advanced ecological information such as primary production and contribute to better understanding of processes in Mediterranean and semiarid regions.

Original languageEnglish
Pages (from-to)1592-1601
Number of pages10
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume41
Issue number7 PART I
DOIs
StatePublished - 1 Jul 2003

Keywords

  • Biomass monitoring
  • Remote sensing
  • Sensors synergy
  • Unmixing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences (all)

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