Current　research　on　the　relationship　between　drought　and　vegetation　has　focused　on　two　aspects.　One　is　the　correlation　analysis　between　climate　factors　and　spatiotemporal　variation　of　vegetation,　and　the　other　is　the　response　of　vegetation　to　climate　change.　Methods　for　large-scale　plant　stress　resistance　monitoring　are　still　lacking.　This　study　used　Normalized　Difference　Vegetation　Index　(NDVI),　Gross　Primary　Productivity　(GPP),　Modified　Anthocyanin　Content　Index　(mACI),　and　Shortwave　Infrared　Water　Stress　Index　(SIWSI)　to　monitor　vegetation　changes　under　drought　stress.　A　comprehensive　monitoring　method　for　plant　stress　resistance　was　constructed.　This　method　comprehensively　considered　the　stress　resistance　process　of　plants　and　established　four　indicators.　Correlation　analysis　was　carried　out　using　the　comprehensive　score　of　crop　stress　resistance　and　the　harvestless　rate　of　each　province.　There　was　a　negative　relationship　between　crop　stress　resistance　and　harvestless　rate.　This　method　was　applied　to　evaluate　the　resistance　of　different　types　of　vegetation　to　drought　stress　in　China.　The　results　showed　that:　(1)　Plant　stress　resistance　varied　greatly　in　different　seasons.　It　was　weakest　in　summer　and　strongest　in　winter.　The　spatial　heterogeneity　of　plant　stress　resistance　in　China　was　significant.　In　spring,　the　regions　with　comprehensive　scores　lower　than　70　were　mainly　located　in　Shanxi　and　northern　Shaanxi.　The　regions　with　comprehensive　scores　higher　than　90　were　mainly　concentrated　in　northeastern　Inner　Mongolia　and　the　southern　part　of　Yunnan;　(2)　There　were　obvious　differences　in　the　stress　resistance　of　different　types　of　vegetation.　In　summer,　deciduous　coniferous　forest　had　the　strongest　stress　resistance　and　the　smallest　intra-class　differences.　In　spring　and　fall,　grassland　had　the　strongest　stress　resistance　and　the　greatest　intra-class　differences.　The　comprehensive　monitoring　method　of　plant　stress　resistance　is　helpful　to　explore　the　law　of　plant　stress　resistance　under　drought　stress,　which　provides　references　for　helping　reduce　disaster　risks.　©　2022,　Science　Press.　All　right　reserved.