@article{fdi:010065253,
  title = {{C}hange detection matrix for multitemporal filtering and change analysis of {SAR} and {P}ol{SAR} image time series},
  author = {{L}e, {T}. {T}. and {A}tto, {A}. {M}. and {T}rouve, {E}. and {S}olikhin, {A}. and {P}inel, {V}irginie},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his paper presents a method for analyzing {S}ynthetic {A}perture {R}adar ({SAR}) and polarimetric {SAR} ({P}ol{SAR}) image time series based on change detection matrices ({CDM}) containing information on changed and unchanged pixels. {T}hese matrices are constructed for each spatial position over the time series by implementing similarity cross tests. {T}he proposed matrix is then exploited for adaptive temporal filtering, analysis of change dynamics and multitemporal change detection. {T}he proposed approach is illustrated on the three following data sets: 25 ascending {T}erra{SAR}-{X} images and 7 descending {RADARSAT} 2 full polarization images over {C}hamonix-{M}ont{B}lanc, {F}rance, where the seasonal evolution of glaciers and mountains can be observed, and a time series of 11 ascending {ALOS}-{PALSAR} dual polarization images over {M}erapi volcano, {I}ndonesia during a period including the 2010 eruption. {P}ublished by {E}lsevier {B}.{V}. on behalf of {I}nternational {S}ociety for {P}hotogrammetry and {R}emote {S}ensing, {I}nc. ({ISPRS}).},
  keywords = {{C}hange detection matrix ; {C}hange analysis ; {SAR} ; {P}ol{SAR} image time series ; {M}ultitemporal filtering ; {I}ndex of change dynamics},
  booktitle = {},
  journal = {{ISPRS} {J}ournal of {P}hotogrammetry and {R}emote {S}ensing},
  volume = {107},
  numero = {},
  pages = {64--76},
  ISSN = {0924-2716},
  year = {2015},
  DOI = {10.1016/j.isprsjprs.2015.02.008},
  URL = {https://www.documentation.ird.fr/hor/fdi:010065253},
}