In　recent　decades,　the　area　and　proportion　of　planted　forests　have　increased;　thus,　understanding　the　responses　of　planted　and　natural　forests　to　drought　are　crucial　because　it　forms　the　basis　for　forest　risk　assessments　and　management　strategies.　In　this　study,　we　combined　the　moderate-resolution　imaging　spectroradiometer　(MODIS)　enhanced　vegetation　index　(EVI),　meteorological　aridity　indices,　and　standardized　precipitation　evapotranspiration　indices　(SPEI)　to　identify　the　drought　responses　of　planted　and　natural　forests.　In　particular,　we　used　the　EVI　standard　anomaly　(ESA)　as　a　physiological　drought　indicator　and　analyzed　the　applicability　of　SPEIs　at　time　scales　of　1-30　months,　thereby　determining　the　optimal　time　scale　for　the　SPEI　(SPEIopt),　i.e.,　the　SPEI　that　best　represents　the　drought　responses　of　forests　in　Yunnan.　Next,　we　employed　the　optimal　SPEI　and　the　ESA　as　indices　to　statistically　analyze　the　response　characteristics　of　planted　and　natural　forests　under　different　drought　intensities.　The　results　indicated　the　following:　(1)　The　SPEI　in　June　and　a　time　scale　of　five　months　(i.e.,　SPEIJun,5)　comprise　the　optimal　meteorological　aridity　indicator　for　forests　in　Yunnan　Province,　which　had　the　strongest　correlation　with　the　EVI　standard　anomaly　(ESAJun).　(2)　All　forest　types　were　affected　by　drought　in　Yunnan,　but　their　responses　varied　according　to　the　forest　type,　elevation,　and　drought　intensity.　In　general,　natural　forests　are　more　vulnerable　and　sensitive　to　drought　than　planted　forests,　especially　natural　coniferous　forests　at　low　(0-2000　m)　and　moderate　(2000-4000　m)　altitudes,　and　natural　mixed　forest　at　low　altitudes　(0-2000　m).　(3)　The　remote　sensing-based　ESA　(ESAJun)　is　sensitive　to　the　intensity　of　water　stress,　which　makes　it　a　good　indicator　for　drought　monitoring.　In　addition,　the　forests＇　inventory　survey　revealed　that　8.05%　of　forests　were　affected　by　drought;　thus,　we　used　this　as　a　guide　to　estimate　an　approximate　threshold　to　map　forest　responses　to　drought　across　the　region.　Below　this　approximate　threshold　(i.e.,　ESAJun　©　2016　by　the　authors.