The north-south transect of tastern China (NSTEC) was a typical ecologcal region which was mostly driven by heat and varied with its vegetation along with latitude.In-depth knowing of the NSTEC will enhance our unders...The north-south transect of tastern China (NSTEC) was a typical ecologcal region which was mostly driven by heat and varied with its vegetation along with latitude.In-depth knowing of the NSTEC will enhance our understanding of global change along with global warming.In this paper,NOAA-AVHRR data was used to get the vegetation index across the NSTEC.Then a regression model was built to get the Net Primary Productivity (NPP) from it.Since the research area covered from 118°E to 128°E,40°N to 50°N,and from 108°E to 118°E,17.5°N to 40°N,to precisely acquire the NPP distribution pattern of the whole area,different vegetation indices were compared according to different land surface.Then three regression models were deduced for NPP.Finally,a NPP adjusting scheme was used to get a general NPP distribution map from the three regression results.The achievements well reflect the distribution character of NPP along the NSTEC and would support further analysis and simulation in land ecology system study and global change research.展开更多
探讨了植被指数的几种主要形式（IDV、NDVI、Tasseled Cap Greenness）及其在退耕还林（草）初期（2000-2002年）效能监测中的应用。运用遥感数据处理、GIS（ARC／INFO）AML编程统计出青藏-黄土高原结合部复杂地形条件下退耕还林（草）...探讨了植被指数的几种主要形式（IDV、NDVI、Tasseled Cap Greenness）及其在退耕还林（草）初期（2000-2002年）效能监测中的应用。运用遥感数据处理、GIS（ARC／INFO）AML编程统计出青藏-黄土高原结合部复杂地形条件下退耕还林（草）各类型地块的3期平均植被指数，及两年间相应的植被指数变化，对比分析了各类型植被指数与其它属性数据间的关系，发现7～9月份积温和湿润度条件对植被指数的影响主要表现为累积效应。研究认为，通过更详实的地表植被状态的适时调查，建立并应用遥感成像前期地表水热因子与各类型的植被指数向量之间的映照关系，上述方法将有更实际的意义。展开更多
文摘The north-south transect of tastern China (NSTEC) was a typical ecologcal region which was mostly driven by heat and varied with its vegetation along with latitude.In-depth knowing of the NSTEC will enhance our understanding of global change along with global warming.In this paper,NOAA-AVHRR data was used to get the vegetation index across the NSTEC.Then a regression model was built to get the Net Primary Productivity (NPP) from it.Since the research area covered from 118°E to 128°E,40°N to 50°N,and from 108°E to 118°E,17.5°N to 40°N,to precisely acquire the NPP distribution pattern of the whole area,different vegetation indices were compared according to different land surface.Then three regression models were deduced for NPP.Finally,a NPP adjusting scheme was used to get a general NPP distribution map from the three regression results.The achievements well reflect the distribution character of NPP along the NSTEC and would support further analysis and simulation in land ecology system study and global change research.
文摘探讨了植被指数的几种主要形式（IDV、NDVI、Tasseled Cap Greenness）及其在退耕还林（草）初期（2000-2002年）效能监测中的应用。运用遥感数据处理、GIS（ARC／INFO）AML编程统计出青藏-黄土高原结合部复杂地形条件下退耕还林（草）各类型地块的3期平均植被指数，及两年间相应的植被指数变化，对比分析了各类型植被指数与其它属性数据间的关系，发现7～9月份积温和湿润度条件对植被指数的影响主要表现为累积效应。研究认为，通过更详实的地表植被状态的适时调查，建立并应用遥感成像前期地表水热因子与各类型的植被指数向量之间的映照关系，上述方法将有更实际的意义。
