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基于HY-1C/CZI数据的冬小麦早期识别研究
引用本文:王利民,刘佳,高建孟,姚保民,杨福刚,邹金秋.基于HY-1C/CZI数据的冬小麦早期识别研究[J].中国农学通报,2019,35(33):151-157.
作者姓名:王利民  刘佳  高建孟  姚保民  杨福刚  邹金秋
作者单位:中国农业科学院农业资源与农业区划研究所
基金项目:高分辨率对地观测系统重大专项(民用部分)(09-Y20A05-9001-17/18)。
摘    要:目的]为充分发掘海洋一号C星(HY-1C)CZI数据的农业应用潜力,方法]该文以HY-1C/CZI数据为基础数据源,结合土地利用现状数据、目视解译结果数据,以河南省商丘市及其附近区域作为研究区,对早播冬小麦、晚播冬小麦、裸地及建筑、森林、水体五类地物的光谱特征进行了分析,并在光谱分析的基础上基于决策树分类方法对冬小麦区域进行了提取。结果]冬小麦面积提取结果表明,2018年研究区内冬小麦总播种面积69.42万公顷。以目视解译获得的地面验证点数据对提取结果进行精度验证,结果表明,冬小麦提取结果的总体精度为91.80%,Kappa系数为0.84,冬小麦用户精度和制图精度分别为91.88%和92.91%。 结论] 基于HY-1C/CZI数据可以实现对冬小麦的早期识别和提取,提取精度较高,达到了其他相似数据源相近的识别精度,表明基于海洋一号卫星CZI数据具有一定的农业应用潜力。

关 键 词:大豆  大豆  脱落酸  干旱  硝酸还原酶  谷氨酰胺合成酶  谷氨酸合成酶  籽粒产量  
收稿时间:2019/6/4 0:00:00
修稿时间:2019/10/31 0:00:00

Winter Wheat Early Identification Based on HY-1C/CZI Data
Abstract:To fully explore the agricultural application potential of HY-1C/CZI data, we analyzed the spectral signatures of 5 different ground objects of early sowing winter wheat, late sowing winter wheat, bare land and buildings, forests, and water in Shangqiu, Henan and its adjacent area, by taking HY-1C/CZI data as basic data source, combining with land utilization status data and visual interpretation data; and extracted the winter wheat area based on the decision tree classification method on the basis of spectral analysis. The extraction results ofwinterwheatareashowedthat:thetotalsowingareaofwinterwheatinthestudyareain 2018was69.42×104 hm2; the accuracy of extraction result was verified with the ground validation points obtained by visual interpretation, indicating that the overall accuracy of winter wheat extraction result was 91.80%, with Kappa coefficient of 0.84, and the user accuracy and the mapping accuracy of winter wheat were 91.88% and 92.91%, respectively. Data based on HY-1C/CZI is capable to identify and extract the winter wheat at an early age with a comparative extraction accuracy as other similar data sources, indicating that HY-1C/CZI data has certain agricultural application potential.
Keywords:HY-1C  CZI  winter wheat  early detection  decision tree
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