【摘要】 为研究GF-1时间序列影像的识别技术对大尺度葡萄信息识别提取的可行性,探索大尺度葡萄快速精确提取的新思路。基于GF-1/WFV时间序列影像数据分析试验区主要植被类型的归一化植被指数(Normalized difference vegetation index,NDVI)、增强型植被指数(Enhanced vegetation index,EVI)的时序变化特征,结合葡萄物候期构建决策树,提取宁夏贺兰山东麓葡萄的空间分布信息。结果表明,该方法可以有效提取贺兰山东麓葡萄分布信息,分类总体精度为95%,Kappa系数为0.91。葡萄提取的生产精度为93%,用户精度为96%。在时间序列数据中,葡萄提取的窗口期为3—5月掩埋期和7—9月生长旺盛期。NDVI时间序列能够较好地区分作物和防护林,EVI时间序列能够区分葡萄地和防护林。更多还原

【Abstract】 In order to study the feasibility of GF-1 time series image recognition technology for large-scale grape information recognition and extraction,a new idea for rapid and accurate extraction of large-scale grape was explored.Based on GF-1/WFV time series image data,the time sequence change characteristics of normalized difference vegetation index(NDVI) and enhanced vegetation index(EVI) of the main vegetation types in the experimental area was analyzed,and the spatial distribution information of grape in the eastern foot of Helan mountain in Ningxia province was extracted by combining the establishment of decision trees in grape phenology.The results showed that this method could effectively extract the information of grape planting distribution in the eastern foot of Helan mountain,with a total classification accuracy of 95% and a Kappa coefficient of 0.91.The production precision of grape extraction was 93%,and the user precision was 96%.In the time series data,the window period of grape extraction was grape burial period which from March to May and vigorous growth period which from July to September.NDVI time series could distinguish crop and protection forest,and EVI time series could distinguish grape and protection forest.更多还原