Increasing　human　activities　have　caused　significant　global　ecosystem　disturbances　at　various　scales.　There　is　an　increasing　need　for　effective　techniques　to　quantify　and　detect　ecological　changes.　Remote　sensing　can　serve　as　a　measurement　surrogate　of　spatial　changes　in　ecological　conditions.　This　study　has　improved　a　newly-proposed　remote　sensing　based　ecological　index　(RSEI)　with　a　sharpened　land　surface　temperature　image　and　then　used　the　improved　index　to　produce　the　time　series　of　ecological-status　images.　The　Mann-Kendall　test　and　Theil-Sen　estimator　were　employed　to　evaluate　the　significance　of　the　trend　of　the　RSEI　time　series　and　the　direction　of　change.　The　change　vector　analysis　(CVA)　was　employed　to　detect　ecological　changes　based　on　the　image　series.　This　RSEI-CVA　approach　was　applied　to　Fujian　province,　China　to　quantify　and　detect　the　ecological　changes　of　the　province　in　a　period　from　2002　to　2017　using　Moderate　Resolution　Imaging　Spectroradiometer　(MODIS)　data.　The　result　shows　that　the　RSEI-CVA　method　can　effectively　quantify　and　detect　spatiotemporal　changes　in　ecological　conditions　of　the　province,　which　reveals　an　ecological　improvement　in　the　province　during　the　study　period.　This　is　indicated　by　the　rise　of　mean　RSEI　scores　from　0.794　to　0.852　due　to　an　increase　in　forest　area　by　7078　km2.　Nevertheless,　CVA-based　change　detection　has　detected　ecological　declines　in　the　eastern　coastal　areas　of　the　province.　This　study　shows　that　the　RSEI-CVA　approach　would　serve　as　a　prototype　method　to　quantify　and　detect　ecological　changes　and　hence　promote　ecological　change　detection　at　various　scales.　©　2019　by　the　authors.