Spatio-temporal wavelet statistics of SAR backscatter for the characterization of forest degradation in Cameroon

Elsa Carla De Grandi; Edward Mitchard; Iain Woodhouse

Spatio-temporal wavelet statistics of SAR backscatter for the characterization of forest degradation in Cameroon

Elsa Carla De Grandi, Edward Mitchard, Iain Woodhouse

School of Geosciences

Research output: Contribution to conference › Other › peer-review

Abstract / Description of output

Spatio-temporal analysis of ENVISAT SAR backscatter statistics was undertaken to characterise different landcover types including grassland, forest/agriculture mosaic, degraded forest and intact forest in Eastern Cameroon, Central Africa. The spatial statistics analysis was based on texture measures including wavelet variance and spectra. While, temporal analysis called into play multi-temporal features (swing and linear regression parameters) of pixel trajectories along image acquisitions for tracking landcover changes between 2003 and 2009.

Original language	English
Publication status	Published - Jul 2014

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@conference{1e811ac29085475195caee5b91d2ce03,

title = "Spatio-temporal wavelet statistics of SAR backscatter for the characterization of forest degradation in Cameroon",

abstract = "Spatio-temporal analysis of ENVISAT SAR backscatter statistics was undertaken to characterise different landcover types including grassland, forest/agriculture mosaic, degraded forest and intact forest in Eastern Cameroon, Central Africa. The spatial statistics analysis was based on texture measures including wavelet variance and spectra. While, temporal analysis called into play multi-temporal features (swing and linear regression parameters) of pixel trajectories along image acquisitions for tracking landcover changes between 2003 and 2009.",

author = "{De Grandi}, {Elsa Carla} and Edward Mitchard and Iain Woodhouse",

year = "2014",

month = jul,

language = "English",

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TY - CONF

T1 - Spatio-temporal wavelet statistics of SAR backscatter for the characterization of forest degradation in Cameroon

AU - De Grandi, Elsa Carla

AU - Mitchard, Edward

AU - Woodhouse, Iain

PY - 2014/7

Y1 - 2014/7

N2 - Spatio-temporal analysis of ENVISAT SAR backscatter statistics was undertaken to characterise different landcover types including grassland, forest/agriculture mosaic, degraded forest and intact forest in Eastern Cameroon, Central Africa. The spatial statistics analysis was based on texture measures including wavelet variance and spectra. While, temporal analysis called into play multi-temporal features (swing and linear regression parameters) of pixel trajectories along image acquisitions for tracking landcover changes between 2003 and 2009.

AB - Spatio-temporal analysis of ENVISAT SAR backscatter statistics was undertaken to characterise different landcover types including grassland, forest/agriculture mosaic, degraded forest and intact forest in Eastern Cameroon, Central Africa. The spatial statistics analysis was based on texture measures including wavelet variance and spectra. While, temporal analysis called into play multi-temporal features (swing and linear regression parameters) of pixel trajectories along image acquisitions for tracking landcover changes between 2003 and 2009.

M3 - Other

ER -

Spatio-temporal wavelet statistics of SAR backscatter for the characterization of forest degradation in Cameroon

Abstract / Description of output

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