【摘要】 提出利用时序NDVI数据提取作物生长过程方法。遥感数据在采集过程中受云、大气因子的影响 ,以及混合像元问题 ,造成时序植被指数值变得没有规律 ,对比性不强。采用基于最小二次方拟合的谐函数分析方法 ,依据作物轮作规律和生长周期性特征 ,用主要频率的正弦、余弦谐函数重建时序图像 ,去除了影像中云污染的影响。以中国的旱地为例 ,考虑到像元内旱地对NDVI值的贡献率 ,计算区域内旱地像元加权平均值来反映其作物生长过程。同时与区域所有像元的平均值、旱地平均值等统计方法的结果进行对比分析 ,表明区域内旱地的加权平均值能够削弱旱地比例和地域间的差异 ,突出耕地上作物的生长过程特征。通过与地面实测数据分析 ,平滑前后的作物生长过程与叶面积指数相关性增加 5 %— 11% ,采用区域加权平均的方法得到的作物生长过程 ,比旱地平均和NDVI平均的结果与叶面积指数的相关性增加 14 %— 17%。更多还原

【Abstract】 Time series of NDVI data have extensive applications in crop condition monitoring and yield prediction.The NDVI data are polluted by cloud even with precise correction and 10 days composition. And due to its 1 km resolution, the data of one pixel contains information more than crops themselves. In this paper,we present a method to extract crop growth profile using time series of SPOT-VGT NDVI and land cover data. In order to remove cloud pollution and extract the characteristics of the vegetation dynamics,the Harmonic Analysis of Time Series (HANTS) algorithm is performed on the time series of NDVI data.HANTS can analyze the time signal for each individual pixel and use the series of harmonic sine and cosine waves to reconstructe waves fitting into the total period.Results show that the cloud polluted data are recognized and replaced successfully by reconstruction of seasonal NDVI profiles. In order to monitor the crop condition and indicate yield level, the time series of NDVI should contain as much crop information as possible,from which the extraced indicators should be related to crop yield performances. Land cover data is used to mask non-arable land,and the NDVI are calculated only for arable land pixel.For a regional, like a county or a province, the pixels within a region are used only for those that NDVI is higher than 0.15. The weight average method is used to calculate the regional NDVI which can indicate the crop information, better than other methods. The weight is the proportion of arable land within a pixel. By comparing the profiles of whole country,a region,a province and a county, we can conclude that the profile is affected by the crop calendar and the cultivation structure. If a region has same crop calendar and pure crop structure, the crop profile is a good indicator for crop condition and yield. The yield stratification zone and county level are proposed to calculate regional NDVI profile. The profiles are validated by using field measuring LAI.It shows that HANS can increase the relative coefficient of NDVI and LAI by 5%—11% than raw data. The weight average method can increase the relative coefficient of NDVI and LAI by 14%—17% than other methods.更多还原