基于HJ卫星混合像元分解法的湖北省四湖地区夏收作物种植信息提取

混合像元是造成中低空间分辨率遥感数据计算机解译不准确的主要原因，通过收集2013年四湖地区夏收作物生长期内的不用生育时期的三景HJ卫星CCD数据，生成一个15波段的“类高光谱”数据；在采用阀门技术结合夏收作物NDVI指数变化特点，提取所有夏收作物（小麦与油菜）在四湖地区的空间分布的基础上，成功运用改进的逐步回归法计算出小麦与油菜在混合像元中的丰度值，高精度地取得了四湖地区小麦、油菜种植区的空间分布；将部分结果与同期资源三号卫星融合数据作为标准进行比较，证明基于改进的逐步回归法计算混合像元的丰度值是比较准确的，为运用HJ卫星CCD数据高精度提取农作物种植信息提供了一种可行的方法

EXTRACTING PLANTING INFORMATION OF SUMMER HARVESTING CROPS IN SHIHU REGION FROM HJ CCD DATA USING UNMIXING ALGORITHM DATA

Mixed pixel is a mainly factor that causes inaccurate classification results. In this paper we extracted the planting information of summer harvesting crops (mainly wheat and rape) in Shigu region of Hubei Province from HJ CCD data using the linear mixed model with an improved stepwise regression method. The detail process was as follow: preprocessing (radiometric correction and geometric correction) three HJ CCD remote sensing dates (spatial resolution is 30 m) in 2013, and created hyperspectral like images with 15 bands using the layer stacking technique. Extracted four spectral characteristics curves of wheat rape water and uncovered land in hyperspectral like images using EARMSE (end member average root mean square error) methods combined with pure pixels index and GPS survey. According to time series characteristics of crop phenology, we extracted spatial distribution of summer harvest crop fields using NDVI threshold. Finally according to four types of end member spectral characteristics curves and hyperspectral like images with 15 bands that only include summer harvest crop, we used the Linear Mixture Spectrum Analysis method that replace multiple regression with improved wise step, and calculated abundance value of four types of end member in each mixed pixel. The calculated values was compared to ground truth data that were derived from ZY03 image (spatial resolution is 21 m) using maximum likelihood classification method in subarea that area is 522 square kilometer. The result shows that the error rate of rape area is 67% and that of wheat is 95%, indicating that this reversing method is accurate in Shuhu region. The paper provids a new method with high precision to extract crop planting information with low spatial resolution data, especially in southern part of China where most of pixels are mixed pixels