古尔班通古特沙漠梭梭林地NDVI的时间效应-基于物候变化和MODIS图像的研究

遥感图像信息提取研究是遥感研究中的一个关键问题,也是遥感研究的热点和难点之一。使用2000~2010年MODIS-NDVI 16 d合成数据和物候记录,借助GIS空间分析和统计分析方法,重构了古尔班通古特沙漠梭梭林地Mean NDVI时间序列特征曲线。分析物候与Mean NDVI时间序列表明,梭梭林地内的短命植物生长期早于梭梭。研究梭梭林地Mean NDVI时间序列曲线发现,曲线中存在一个明显区别于其他地物的特征点,该点可以作为梭梭林地信息“诊断点”。根据“诊断点”特征构建了梭梭林地特征指数模型(HFFI),进而反演了古尔班通古特沙漠梭梭林地信息,并利用地面实际观测资料进行验证,结果表明分类精度达到83%。

The NDVI Time Effect of Haloxylon Aammodendron Forest in Gurbantunggut Desert:Based on Phenological Changes and the Image of MODIS

Remote sensing image information extraction research is one of the key problems of remote sensing research,it is also one of the hot and difficult points in remote sensing research.With the aid of the GIS spatial analysis and statistical analysis method,the Haloxylon Aammodendron forest Mean NDVI time series characteristic curve were reconstructed in the Gurbantunggut Desert by using the NASA/ MODIS-NDVI16 days synthetic data (from 2000 to 2010) and phenology record.Analysis of phenological and Mean NDVI time series,the result showed that the Ephemeral plants (or short-lived plants) under the Haloxylon Aammodendron forest growth period is earlier than Haloxylon Aammodendron.Research of Mean NDVI time series curve,showed that there is a feature point that obviously different from other features in the curve,which can be used as the “diagnosis point” of Haloxylon Aammodendron.A model of Haloxylon Aammodendron forest features index(HFFI) was developed based on the “diagnosis point” characteristics.Retrieved the information of Haloxylon Aammodendron forest in the Gurbantunggut Desert from HFFI.And utilizing the data of the ground practical observation validation,the results indicate that the classification accuracy reached 83%.