To　study　seismo-ionospheric　coupling,　the　singular　spectrum　analysis　(SSA)　method　was　introduced　to　detect　ionospheric　anomalies　preceding　great　earthquakes.　The　SSA　method　was　used　to　decompose　the　total　electronic　content　(TEC)　series,　and　the　reconstructed　components　(RCs)　were　combined　to　obtain　the　TEC　principal　components　using　w-correlation.　The　background　TEC　value　during　the　quiet　solar-terrestrial　environment　period　was　used　to　calculate　the　standard　deviation,　which　was　subsequently　used　to　determine　the　upper　and　lower　bounds　of　the　background　values.　The　root-mean-square　error　of　the　global　ionosphere　map　(GIM)　published　by　the　International　GNSS　Service　(IGS)　near　the　earthquake　epicenter　was　extracted　and　averaged　to　obtain　the　threshold,　which　was　then　used　to　suppress　the　systematic　error　effect　during　the　detection　of　pre-earthquake　TEC　anomalies　process.　This　new　method　was　used　to　detect　ionospheric　anomalies　prior　to　the　occurrence　of　the　Mw7.8　Kaikoura　earthquake　in　New　Zealand　on　13　November　2016　and　the　Mw6.9　Fukushima　earthquake　in　Japan　on　21　November　2016.　The　TEC　data　were　further　analysed　with　the　sliding　interquartile　range　(IQR)　method　to　verify　the　reliability　and　feasibility　of　the　SSA.　The　results　showed　that　the　TEC　anomalies　over　these　two　epicenters　were　clearly　detected　on　25　and　28　October　and　10　November.　Our　results　showed　that　compared　with　IQR,　SSA　could　detect　TEC　anomalies　with　a　larger　magnitude,　making　TEC　anomalies　caused　by　external　factors　more　visible.　Furthermore,　based　on　the　analysis　of　the　solar-terrestrial　environment　using　the　data　of　F10.7,　Dst　and　Kp　indices,　it　is　found　that　magnetic　storms　occurred　during　these　three　days.　To　identify　and　extract　potential　precursor　information　on　seismo-ionospheric　anomalies,　the　global　distribution　of　TEC　anomalous　areas　with　SSA　and　IQR　was　also　analysed.　The　results　indicated　the　presence　ofobvious　anomalous　characteristics　of　the　seismic-ionospheric　coupling　effect　in　the　preparation　zones　detected　by　SSA.　In　addition,　the　relation　between　TEC　anomaly　and　Dst　index　detected　by　the　cross-wavelet　analysis　indicated　that　ionospheric　anomalies　outside　the　preparation　zones　detected　by　IQR　were　caused　by　magnetic　storms.　In　contrast,　the　ranges　and　amplitudes　of　TEC　anomalies　detected　by　SSA　in　these　zones　were　much　smaller　than　those　with　IQR.　Overall,　these　findings　demonstrate　that　SSA　can　effectively　eliminate　the　effect　of　solar-geomagnetic　activity　and　extract　seismic-ionospheric　coupling　anomalies.　©　2019　Elsevier　Ltd