The　Bodélé　Depression　(BD)　in　northern　Chad,　recognized　as　the　world＇s　largest　source　of　aerosol　dust,　hosts　the　fastest　migrating　Barchan　dunes,　which　primarily　move　in　a　southwesterly　direction.　Despite　its　significance,　capturing　the　short-term,　weekly　dynamics　of　dune　migration　in　BD　has　been　hindered　by　the　limitations　of　traditional　monitoring　methods,　which　often　suffer　from　short　temporal　baselines　and　geolocation　inaccuracies.　This　study　addresses　these　challenges　by　enhancing　the　optical　image　matching　and　inversion　approach　by　integrating　Landsat-8　(L-8)　and　Sentinel-2　(S-2)　datasets.　Specifically,　we　refine　the　selection　and　processing　algorithms　to　enable　improved　monitoring　of　dune　migration　over　an　8-year　period　for　L-8　and　6　years　for　S-2.　Rather　than　directly　matching　images　from　different　sensors,　prone　to　inconsistencies,　we　first　generate,　and　fuse　offset　maps　from　L-8　and　S-2　into　unified　networks　before　performing　inversion.　This　fusion　strategy　condenses　the　temporal　sampling,　mitigates　gaps　caused　by　cloud　cover　or　dust　interference,　and　significantly　improves　data　continuity　over　long　time　spans.　As　a　result,　we　are　able　to　monitor　dune　migration　at　a　weekly　temporal　resolution.　The　observed　migration　patterns　reveal　seasonal　and　interannual　variability,　with　notably　reduced　migration　rates　during　summer.　We　quantify　these　fluctuations　using　the　Seasonal　Sliding　Coefficient　(SSC),　which　compares　dune　velocities　across　seasons.　The　highest　SSC　values　(~2　between　winter　and　summer)　underscore　the　pronounced　seasonal　contrast.　Our　findings　demonstrate　that　the　refined　inversion　framework,　when　coupled　with　sensor　fusion,　offers　dense　spatiotemporal　insights　into　dune　dynamics　while　minimizing　uncertainties　and　enhancing　temporal　coverage.　©　2025　IEEE.