基于小波变换的华北平原耕地复种指数提取

    New method for extracting multiple cropping index of North China Plain based on wavelet transform

    • 摘要: 该文以中国华北平原为研究区域,提出了基于小波变换的耕地复种指数遥感提取方法。首先,利用小波变换对2007年36景SPOT VGT/NDVI(SPOT VEGETATIONVGT数据归一化植被指数)遥感数据进行去噪处理,重建耕地农作物生长NDVI(归一化植被指数)曲线;然后,结合地面样点数据、农时数据和农业统计数据,采用二次差分法提取了华北平原2007年耕地复种指数和空间分布特征。研究结果表明,华北平原5省市耕地复种空间分布存在明显的地域特性,河南省耕地复种指数最大,达到179.4%,山东省次之,北京市最小。该研究结果与统计数据和其他遥感监测比较结果表明,基于小波变换去噪时序遥感数据提取耕地复种指数的技术方法与统计数据和其他遥感监测结果总体上具有较好的一致性,复种指数空间分布变化趋同。

       

      Abstract: This study chose the North China Plain as study area and proposed a new method of multiple cropping extraction from remote sensing data based on wavelet transform. Firstly, using wavelet transform to de-noise time-series SPOT VGT/NDVI(SPOT VEGETATION/normalized difference vegetation index) remote sensing data and reconstructing NDVI curve of main crops in North China Plain. Then, combining with ground samples data, farming season data and agricultural statistics data, this study extracted the multiple cropping index and spatial distribution of the North China Plain based on the double difference method. The results show that the multiple cropping index in Henan province is the largest, up to 179.4%, followed by Shandong province, which in Beijing is the smallest among the five provinces in the area, and the spatial distribution of the multiple cropping index has obvious geographical characteristics. Comparing with statistical data and other results based on remote sensing technologies, the results have the better consistency and the spatial distribution has convergence.

       

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