中文摘要：

用监督分类方法提取出Landsat TM影像中的刺槐林区域,将归一化植被指数NDVI、归一化水分指数NDWI、土壤调节植被指数SAVI、修正的土壤调节植被指数MSAVI和K-T变换应用于刺槐林影像,用聚类分析将刺槐林分成4个等级的树冠活力。实测结果表明,通过树冠活力来分类,NDWI分类精度最高,达到82.5%。

英文摘要：

Some of Robinia Pseudoacacia Forest have been dead or dieback in the Yellow River Delta since 1990s.The area of Robinia was extracted using Landsat TM images with supervised classification.NDVI,NDWI,SAVI,MSAVI and TCT transforms were used,and then cluster analysis was used to separate the Robinias into four classes of tree vigor.We evaluated 376 trees at 40 sites across the study area using the USFS crown condition rating guide,and separate Robinia Pseudoacacia into four levels of tree vigor.The field data were used to measure the accuracy of various Vegetation Index classification techniques.The normalized difference water index（NDWI） transform provided the best overall accuracy,82.5%,for classifying Robinia Pseudoacacia according to tree vigor.Health detection result and relative environment factor analysis showed that high soil salinity and low groundwater depth were found to be significantly correlative with the health of Robinia Pseudoacacia.