Measuring mangrove biomass via remote sensing subpixel analysis

Minhe Ji; Jia Hu; Jing Feng

doi:10.1117/12.860304

12 August 2010 Measuring mangrove biomass via remote sensing subpixel analysis

Minhe Ji, Jia Hu, Jing Feng

Proceedings Volume 7809, Remote Sensing and Modeling of Ecosystems for Sustainability VII; 780907 (2010) https://doi.org/10.1117/12.860304
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

Abstract

The method of "subpixel analysis" is explored to decompose mixed pixels of mangrove for biomass quantification. The basic idea is to treat the non-mangrove spectra of a mixed pixel as the background noise and iteratively remove them from further processing, so that the residual radiance can be matched to the characteristics of, and labeled as, the sampled mangrove spectra. This method requires spectral training only on the targeted cover type (i.e. mangrove in this study), thus it may drastically reduce the amount of human interference and minimize subjective bias in the analytic process. In addition, it can deal with complex and diverse spectra of the same target for better results. A DigitalGlobe's Quickbird multispectral image of Beilun Estuary was used as a test dataset to demonstrate this approach, with mangrove cover of the region being quantified into eight standardized biomass levels. The verification of the model results was performed using Quickbird panchromatic data from the same acquisition. An overall accuracy of 86.1% (Kappa=0.844) was reached, demonstrating the application potential of the subpixel analysis method in the forest ecosystem research and management.

Citation Download Citation

Minhe Ji, Jia Hu, and Jing Feng "Measuring mangrove biomass via remote sensing subpixel analysis", Proc. SPIE 7809, Remote Sensing and Modeling of Ecosystems for Sustainability VII, 780907 (12 August 2010); https://doi.org/10.1117/12.860304

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