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Assessing relationships between Radarsat-2 C-band and structural parameters of a degraded mangrove forest

Authors :
Chunhua Zhang
Francisco Flores-Verdugo
JohnM. Kovacs
Francisco Flores-de-Santiago
Xianfeng Jiao
Source :
International Journal of Remote Sensing. 34:7002-7019
Publication Year :
2013
Publisher :
Informa UK Limited, 2013.

Abstract

When dead stands are included, the strongest overall relationships between the ultra-fine backscatter incidence angle of ∼32° and the various structural parameters were found using the horizontal-horizontal HH polarization/horizontal-vertical HV polarization ratio. However, if the dead stands are not included, then significant relationships with the ultra-fine data were only calculated with the HH data. Similar results were observed using the corresponding incidence angle ∼33° of the fine beam data. When a shallower incidence angle was considered ∼39°, fewer and weaker relationships were calculated. Moreover, no significant relationships were observed if the dead stands were excluded from the sample at this incidence angle. The highest correlation coefficients using the steepest incidence ∼27° were found with the co-polarized HH, vertical-vertical VV polarization modes. Several polarimetric parameters entropy, pedestal height, surface roughness, alpha angle based on the decomposition of the scattering matrix of the fine beam mode at this incidence angle were also found to be significantly correlated to mangrove structural data. The highest correlation R = 0.71 was recorded for entropy and LAI. When the dead stands were excluded, volume scattering was found to be the most significant polarimetric parameter. Finally, multiple regression models, based on texture measures derived from both the grey level co-occurrence matrix GLCM and the sum and difference histogram SADH of the ultra-fine data, were developed to estimate mangrove parameters. The results indicate that only models derived from the HH data are significant and that several of these were strong predictors of all but stem density.

Details

ISSN :
13665901 and 01431161
Volume :
34
Database :
OpenAIRE
Journal :
International Journal of Remote Sensing
Accession number :
edsair.doi...........ab80d55967af5621e4eaa1b40f506633
Full Text :
https://doi.org/10.1080/01431161.2013.813090