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中国农学通报 ›› 2014, Vol. 30 ›› Issue (29): 294-300.doi: 10.11924/j.issn.1000-6850.2014-1593

所属专题: 水稻

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基于环境卫星数据和实测地物光谱数据估算中稻面积

万君,粱益同   

  1. 武汉区域气候中心,武汉区域气候中心
  • 收稿日期:2014-06-05 修回日期:2014-06-05 接受日期:2014-07-17 出版日期:2014-10-31 发布日期:2014-10-31
  • 通讯作者: 万君
  • 基金资助:
    项目来源“基于雷达和光学遥感数据结合的水稻长势监测和估产技术研究”(2012Z02)。

Estimation of the Mid-season Rice Areas Based on HJ-1A/B Satellite Image and Measured Spectral Data

  • Received:2014-06-05 Revised:2014-06-05 Accepted:2014-07-17 Online:2014-10-31 Published:2014-10-31

摘要: 为准确获取水稻种植面积,提高遥感监测精度,利用环境卫星数据,在农作物掩膜的基础上,结合野外实测地物光谱确定端元组分,采用线性光谱混合模型提取湖北省监利县中稻种植面积,将其结果分别与统计数据和实地调查数据相比较。结果表明:采用确定端元选取的方法是可行的,其混合像元分解方法提取作物面积总量精度为93.68%;样本精度为83.67%。因此,利用HJ卫星影像数据开展平原地区水稻遥感监测可为政府决策部门提供信息服务。

关键词: 对策, 对策

Abstract: Aim at getting the accurate rice planting area and improving the precision of remote sensing monitoring, based on the HJ-1A/B satellite data and crops mask and combined with the measured spectral data, this paper determined the end-members and used linear spectral mixture model (LSMM) for Spectral Unmixing, and obtained the abundance image of mid-season rice and RMS error image in Jianli. After evaluating the mid- season rice planting areas, the result was compared with agricultural statistics and survey data. According to the total accuracy evaluation method, the classification accuracy of rice planting areas reached 93.68%, and according to the sampling accuracy evaluation method, the classification accuracy of rice planting areas reached 83.67%. The results indicated that: the method to determine the end-member selection was feasible, it could be applied to monitor paddy rice information in the plains with HJ-1A/B satellite data and provide information services for the government.