基于时序Sentinel-2影像物候特征的江汉平原耕地“非粮化”监测

Monitoring Non-grain Use of Croplands on the Jianghan Plain Based on Sentinel-2 Vegetation Phenology

  • 摘要: 利用遥感技术对耕地“非粮化”现象进行监测对于维护国家粮食安全、助力乡村振兴具有重要的现实意义。利用时间序列Sentinel-2遥感影像,在分析不同种植类型物候特征的基础上,选择若干个关键物候期来概括各生长阶段的物候特征,得到同种种植类型的相似性物候特征及不同种植类型的差异性物候特征。基于由简及繁、分层分类的思路,构建耕地“非粮化”提取模型。在此基础上提取江汉平原潜在“非粮化”(含“非食物化”)区域,包括蔬菜、苗木或撂荒、坑塘养殖等。提取结果总体精度达到92.69%,Kappa系数为0.89。实验结果表明,基于物候特征挖掘和分层分类的方法可以进行区域尺度的“非粮化”监测。该方法在一定程度上可为耕地“非粮化”监测提供有效的技术手段,为进行农田利用方式监测、制定农业政策提供基础数据和科学依据。

     

    Abstract:
    Objectives Monitoring the non-grain use of cropland using remote sensing technology is of great significance for national food security and rural revitalization.
    Methods Through analyzing the phenology of different crop patterns by using time series Sentinel-2 remote sensing images, several key phenological stages were selected to summarize the phenological characteristics of each stage, and the phenology similarity of the same crop pattern and the phenology difference of different crop pattern were obtained. A model was built to extract the non-grain use of cropland on the Jianghan Plain, including vegetables planting, abandoned land or trees planting and aquaculture pond, etc.
    Results The method realized the mapping of non-grain use of cropland on the Jianghan Plain successfully by using hierarchical classification method according to the rule of from simple to complex. The overall accuracy of the results is 92.69%, and the Kappa coefficient is 0.89.
    Conclusions The experiment results demonstrated that the method based on time-series Sentinel-2 remote sensing images and crop phenology can be used to monitor non-grain use of cropland at regional scale. The proposed method can provide effective technology for monitoring the non-grain use of cropland, and provide basic data for agricultural departments to formulate agricultural policies.

     

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