遥感估算植被覆盖度的关键在于:一是植被指数的选择,二是植被指数转换方法。针对中国南方多山的特点,论文提出了能较好地削弱影像中山体阴影、土壤背景、岩石、建筑用地等地物对植被覆盖度信息干扰的复合植被指数V BSI;在植被指数转换方法上,采用混合像元法,对福建省长汀县1994年和2003年的遥感影像进行了植被覆盖度的估算。研究结果表明:采用VBSI进行植被覆盖度的估算,影像阴影信息的干扰作用可以被削减为NDV I的50%,基于VBSI的混合像元法估算植被覆盖度的总体精度达到80%以上;动态监测表明,从1994至2003年研究区高植被覆盖面积增加了150.47km2,占国土面积的比例提高了4.9个百分点,据调查,这与近年来长汀县加大水土流失治理力度有着重要关系。
Vegetation index(VI)and the transformation method of VI are two key factors in estimating vegetation fraction by Remote Sensing.Based on the common VI and the FCD(Forest Canopy Density)Model principle put forward by ITTO(International Tropical Timber Organization),VBSI vegetation index was proposed in this paper that can decrease the interferences from mountain shadows,soil background,rocks and building.It is expressed as VBSI=f(VI,BI,SI)=VI+n·BI+SI which is suitable for estimating vegetation coverage in mountainous areas.Furthermore,mixed pixel model is one of the good transformation methods from VI to vegetation fraction,which can apply to images from different phases.The expression is:fc=(S-Snon)/(Sveg-Snon).Vegetation fraction estimation in 1994-2003 was processed with ERDAS software system aimed at Chang-ting County,Fujian Province,China.The results show that(1)With VBSI,the error of vegetation fraction resulted from the area of image shadow can be decreased,and the error is 50% of that from Normalized Difference Vegetation Index(NDVI).The overall accuracy from the vegetation fraction estimation based on VBSI and mixed pixel model is more than 80%,which meets the requirements for vegetation fraction dynamic monitoring in region.(2)The coverage of high vegetation in the study area increased by 150.47km2,or an increase of 4.9% of the total land area from 1994 to 2003.This is correlative with the work of soil and water conservation in recent years in Changting County.
