频率直方图与植被指数结合的冬小麦遥感产量估测
S126; 基于机器学习方法建立的作物产量估测模型常因过拟合等问题导致泛化性能偏低,产量估测精度不高.该研究以河南省为研究区,分别对不同波段地表反射率数据采用均值法和频率直方图法构造样本特征集作为输入变量,结合随机森林(Random Forest,RF)算法建立冬小麦遥感估产模型.研究结果表明,频率直方图法预测效果优于均值法,平均绝对误差和均方根误差分别为660和860 kg/hm2,决定系数最高达到0.83,达极显著水平(P<0.01);7个地表反射率波段中,近红外1波段表现最好;单个合成指数中,归一化水分指数的表现要优于归一化植被指数;波段组合中,归一化植被指数和归一化水分指数的组合...
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| Published in | 农业工程学报 Vol. 37; no. 23; pp. 145 - 152 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国农业大学土地科学与技术学院,北京 100083%中国农业大学信息与电气工程学院,北京 100083
01.12.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.2021.23.017 |
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| Abstract | S126; 基于机器学习方法建立的作物产量估测模型常因过拟合等问题导致泛化性能偏低,产量估测精度不高.该研究以河南省为研究区,分别对不同波段地表反射率数据采用均值法和频率直方图法构造样本特征集作为输入变量,结合随机森林(Random Forest,RF)算法建立冬小麦遥感估产模型.研究结果表明,频率直方图法预测效果优于均值法,平均绝对误差和均方根误差分别为660和860 kg/hm2,决定系数最高达到0.83,达极显著水平(P<0.01);7个地表反射率波段中,近红外1波段表现最好;单个合成指数中,归一化水分指数的表现要优于归一化植被指数;波段组合中,归一化植被指数和归一化水分指数的组合验证效果最优,平均绝对误差和均方根误差分别为444和527 kg/hm2,决定系数为0.89,达极显著水平(P<0.01),其组合预测效果在4月15日至22日时段内表现最佳,该时段对冬小麦产量的影响最大.该研究通过采用基于频率直方图法构建样本特征结合随机森林算法建立冬小麦遥感估产模型,可为县域冬小麦遥感估产提供一种有效的解决方案. |
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| AbstractList | S126; 基于机器学习方法建立的作物产量估测模型常因过拟合等问题导致泛化性能偏低,产量估测精度不高.该研究以河南省为研究区,分别对不同波段地表反射率数据采用均值法和频率直方图法构造样本特征集作为输入变量,结合随机森林(Random Forest,RF)算法建立冬小麦遥感估产模型.研究结果表明,频率直方图法预测效果优于均值法,平均绝对误差和均方根误差分别为660和860 kg/hm2,决定系数最高达到0.83,达极显著水平(P<0.01);7个地表反射率波段中,近红外1波段表现最好;单个合成指数中,归一化水分指数的表现要优于归一化植被指数;波段组合中,归一化植被指数和归一化水分指数的组合验证效果最优,平均绝对误差和均方根误差分别为444和527 kg/hm2,决定系数为0.89,达极显著水平(P<0.01),其组合预测效果在4月15日至22日时段内表现最佳,该时段对冬小麦产量的影响最大.该研究通过采用基于频率直方图法构建样本特征结合随机森林算法建立冬小麦遥感估产模型,可为县域冬小麦遥感估产提供一种有效的解决方案. |
| Author | 王鹏新 刘峻明 周舟 黄健熙 和晓彤 |
| AuthorAffiliation | 中国农业大学土地科学与技术学院,北京 100083%中国农业大学信息与电气工程学院,北京 100083 |
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| Author_FL | Zhou Zhou Huang Jianxi Wang Pengxin Liu Junming He Xiaotong |
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| DocumentTitle_FL | Estimating winter wheat yield under frequency histogram and vegetation index using remote sensing |
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| Keywords | 遥感;作物;随机森林;冬小麦;产量;频率直方图 |
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| Publisher | 中国农业大学土地科学与技术学院,北京 100083%中国农业大学信息与电气工程学院,北京 100083 |
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| Title | 频率直方图与植被指数结合的冬小麦遥感产量估测 |
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