论文部分内容阅读
增强植被指数(EVI)是植被生长状态及植被覆盖度的指示因子,其时序数据也已成为基于物候特征开展大区域植被和土地覆盖分类的基本手段。利用Savitzky-Golay滤波对MODIS EVI16d合成时间序列数据进行重建,并利用2006～2010年重建得到的时序数据建立棉花理想时序EVI曲线,通过比较待分类像元与理想曲线欧氏距离的方法,提取新疆博乐市棉花种植分布。使用2011年实地调查的棉花地块为感兴趣区,利用混淆矩阵对2011年棉花种植分布的提取结果进行精度检验,总体精度为82.31%。结果表明:利用多年数据建立的理想时序EVI曲线提取棉花种植分布有效可行。
Enhanced Vegetation Index (EVI) is an indicator of vegetation status and vegetation coverage. Its time-series data have also become the basic means of classification of vegetation and land cover based on phenological characteristics in large areas. The Savitzky-Golay filter is used to reconstruct the MODIS EVI16d synthetic time series data, and the cotton ideal time series EVI curve is constructed based on the time series data reconstructed from 2006 to 2010. By comparing the Euclidean distance between pixels and ideal curve, Bole City, cotton planting and distribution. Using the field survey of cotton plots in 2011 as the region of interest, the confusion matrix was used to test the accuracy of the extraction results of the cotton planting distribution in 2011 with an overall accuracy of 82.31%. The results show that it is feasible and effective to extract the cotton planting distribution by using the ideal time series EVI curve established by years of data.