Joint processing of Landsat ETM+ and ALOS-PALSAR data for species richness and forest biodiversity monitoring

Sara Attarchi; Richard Gloaguen

doi:10.1117/12.2029328

17 October 2013 Joint processing of Landsat ETM+ and ALOS-PALSAR data for species richness and forest biodiversity monitoring

Sara Attarchi, Richard Gloaguen

Author Affiliations +

Proceedings Volume 8892, Image and Signal Processing for Remote Sensing XIX; 88920Y (2013) https://doi.org/10.1117/12.2029328
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

Optical remote sensing data is commonly used for estimating biophysical characteristics of forest like tree biodiversity and species richness. Recent advances in radar remote sensing technology raise significant interest to take advantage of the complementary nature of optical and radar data. This paper proposes an approach combining Landsat ETM+ and Advanced Land-Observing Satellite- Phased Array L-band Synthetic Aperture Radar (ALOS/PALSAR) data for forest biodiversity and species richness monitoring. Inventory data from one part of the Hyrcanian forest in north of Iran is used as field data. Visible and infrared ETM+ bands, indices and textures information as well as HH, HV backscattering, polarimetric features (alpha angle, entropy and anisotropy) and SAR texture are extracted. We use the multiple linear regression model to find the best components to describe the biodiversity indices in the study area. We show how tree biodiversity is related to information derived from ETM+ and ALOS/PALSAR data at 95% confidence level (R!=0.63, root mean square error (RMSE) =1.70). Also, the effects of each component on the variation of biodiversity are shown. ETM+ reflectance, polarimetric features and texture from ALOS/PALSAR can describe approximately 63% of biodiversity. The results of multi source monitoring of tree biodiversity and species richness are promising and worth further investigation.

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Sara Attarchi and Richard Gloaguen "Joint processing of Landsat ETM+ and ALOS-PALSAR data for species richness and forest biodiversity monitoring", Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 88920Y (17 October 2013); https://doi.org/10.1117/12.2029328

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