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

Author

De Grandi, Elsa Carla ; Mitchard, Edward ; Woodhouse, Iain

Author_Institution

Sch. of Geosci., Univ. of Edinburgh, Edinburgh, UK

fYear

2014

fDate

13-18 July 2014

Firstpage

2321

Lastpage

2323

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.

Keywords

geophysical image processing; image segmentation; image texture; land cover; radar imaging; spatiotemporal phenomena; statistical analysis; synthetic aperture radar; vegetation mapping; wavelet transforms; AD 2003 to 2009; ENVISAT SAR backscatter statistics; SAR backscatter; agriculture mosaic; central Africa; degraded forest; eastern Cameroon; forest degradation characterization; forest mosaic; grassland; image acquisitions; landcover changes; landcover types; multitemporal features; spatiotemporal wavelet statistics; temporal analysis; texture measures; wavelet spectra; wavelet variance; Backscatter; Correlation; Degradation; Discrete wavelet transforms; Extraterrestrial measurements; Trajectory; Wavelet analysis; ENVISAT ASAR; degraded forest; multi-temporal features; spatio-temporal statistics; wavelet variance;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International

Conference_Location

Quebec City, QC

Type

conf

DOI

10.1109/IGARSS.2014.6946935

Filename

6946935