Distributed　acoustic　sensing　(DAS)　enables　high-density　sampling　of　seismic　wavefields　at　low　cost　compared　to　conventional　geophones.　This　capability　facilitates　structural　detection　of　a　municipal　solid　waste　(MSW)　landfill,　which　is　important　for　protecting　the　surrounding　ecosystem.　However,　processing　the　vast　amount　of　data　from　DAS　array　for　ambient　noise　imaging　can　be　computationally　intensive.　To　address　this,　we　employed　the　common-midpoint　two-station　(CMP-TS)　analysis　to　enhance　the　efficiency　of　ambient　noise　imaging　in　the　MSW　landfill.　CMP-TS　analysis　involves　selecting　pairs　of　traces　at　equal　distances　on　both　sides　with　the　subarray　midpoint　as　symmetry,　which　reduces　the　number　of　DAS　array　recordings　for　cross-correlation　calculations.　After　positioning　the　DAS　arrays　linearly　on　top　of　the　MSW　landfill　to　automatically　collect　ambient　noise,　we　used　the　CMP-TS　analysis　in　the　cross-correlation　calculations　to　speed　up　the　measurement　of　dispersion.　The　S-wave　velocity　structure　of　the　study　region　was　obtained　quickly　by　inverting　the　extracted　dispersion　curves　using　the　gradient　optimization　method.　Ambient　noise　imaging　based　on　CMP-TS　analysis　with　DAS　was　applied　to　a　test　of　an　area-type　MSW　landfill.　The　resulting　S-wave　velocity　section　revealed　a　discontinuous　low-velocity　zone,　validated　by　the　high-density　resistivity　method.　This　low-velocity　zone　was　interpreted　as　containing　leachate　from　waste　decomposition,　and　its　discontinuity　may　be　caused　by　excessive　differences　in　the　waste　residues　settling　rates　under　compaction.　Employing　CMP-TS　analysis　in　ambient　noise　data　collected　by　DAS　offers　more　cost-effective　monitoring　and　a　reliable　basis　for　environmental　pollution　prevention　and　control.