Land　degradation　has　a　major　impact　on　environmental　and　socio-economic　sustainability.　Scientific　methods　are　necessary　to　monitor　the　risk　of　land　degradation.　In　this　study,　the　environmental　sensitive　area　index　(ESAI)　was　utilized　to　assess　land　degradation　sensitivity　and　convergence　analysis　in　Korla,　a　typical　oasis　city　in　Xinjiang　of　China,　which　is　located　on　the　northeast　border　of　the　Tarim　Basin.　A　total　of　18　indicators　depicting　soil,　climate,　vegetation,　and　management　qualities　were　used　to　illustrate　spatial-temporal　patterns　of　land　degradation　sensitivity　from　1994　to　2018.　We　investigated　the　causes　of　spatial　convergence　and　divergence　based　on　the　Ordinary　Least　Squares　(OLS)　and　Geographically　Weighted　Regression　(GWR)　models.　The　results　show　that　the　branch　of　the　Tianshan　Mountains　and　oasis　plain　had　a　low　sensitivity　to　land　degradation,　while　the　Tarim　Basin　had　a　high　risk　of　land　degradation.　More　than　two-thirds　of　the　study　area　can　be　categorized　as　＂critical＂　sensitivity　classes.　The　largest　percentage　(32.6%)　of　fragile　classes　was　observed　for　2006.　There　was　no　significant　change　in　insensitive　or　low-sensitivity　areas,　which　accounted　for　less　than　0.4%　of　the　entire　observation　period.　The　ESAI　of　the　four　time　periods　(1994-1998,　1998-2006,　2006-2010,　and　2010-2018)　formed　a　series　of　convergence　patterns.　The　convergence　patterns　of　1994-1998　and　1998-2006　can　be　explained　by　the　government＇s　efforts　to　＂Returning　Farmland　to　Forests＂　and　other　governance　projects.　In　2006-2010,　the　construction　of　afforested　work　intensified,　but　industrial　development　and　human　activities　affected　the　convergence　pattern.　The　pattern　of　convergence　in　most　regions　between　2010　and　2018　can　be　attributed　to　the　government＇s　implementation　of　a　series　of　key　ecological　protection　projects,　which　led　to　a　decrease　in　sensitivity　to　land　degradation.　The　results　of　this　study　altogether　suggest　that　the　ESAI　convergence　analysis　is　an　effective　early　warning　method　for　land　degradation　sensitivity.