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Spectral Mixture Analysis for Ground-Cover Mapping

  • Michael SchmidtEmail author
  • Peter Scarth
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Monitoring of ground-cover is an important task for land management since it has been linked to indicators of soil loss, biodiversity, and pasture production. Ground-cover is an indicator adopted by Queensland natural resource and catchment management groups. However, accurate spatial estimation of ground-cover is confounded by varying cover types, cover greenness and soil colour.

This research reports on ground-cover mapping based on spectral mixture analysis (SMA) of LANDSAT satellite imagery. Estimates of green and senescent vegetation and soil fractions are derived from iterative SMA. Correlations with field data are form SMA iterations are discussed with r2 values of 0.78 and 0.69 respectively for bare ground estimates over black soils.

Keywords

Normalize Difference Vegetation Index Ground Cover Black Soil Green Vegetation Landsat Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors would like to thank Jeff Milne (formerly with NRW, Indooroopilly), Gorge Bourne and Cameron Dougall (NRW, Emerald) for their help and useful comment during the fieldwork and thereafter.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Natural Resources and WaterIndooroopillyAustralia
  2. 2.Queensland Department of Natural Resources and Water, Remote Sensing CentreBrisbaneAustralia

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