摘要
利用遥感技术反演大范围玉米叶面积指数,对于田间肥水管理、长势监测乃至产量预测具有重要意义。在野外实测样本的支持下,获取玉米抽雄期的Landsat-8多光谱影像,引进Beer-Lambert定律,利用最小二乘法分析玉米冠层结构的消光系数,构建玉米叶面积指数遥感反演模型,最后采用交叉验证法评价模型精度。结果表明:玉米抽雄期NDVI、LAI呈较明显的正相关关系;基于Beer-Lambert定律的玉米叶面积指数遥感反演模型决定系数可达0.97,LAI空间分布状况与当地农业技术推广部门掌握的玉米实际生长状况基本一致,说明利用Beer-Lambert消光定律方法可以有效地反映玉米群体结构对光照的影响,据此开展玉米叶面积指数遥感反演具有较高的可行性。
Using remote sensing technology to retrieve a large area of maize leaf area index is of important significance for field fertilizer and water management,growth monitoring and even yield forecasting.In the support of field survey samples,this paper obtained the Landsat-8multispectral images of maize tasseled during the tasseling stage, introduced Beer-Lambert law,analyzed the extinction coefficient of corn canopy structure by least square method,and constructed a remote sensing inversion model of maize leaf area index.Finally,the cross validation method was used to evaluate the accuracy of the model.The results showed that there was a significant positive correlation between NDVI and LAI in maize tasseling stage.Based on the Beer-Lambert law,the determination coefficient of maize leaf area index was 0.97.The spatial distribution of LAI was basically consistent with the actual maize growth situation mastered by local agricultural extension department,indicating that using the Beer-Lambert extinction law could effectively reflect the effect of population structure of maize on illumination.Hereby,it was highly feasible to carry out remote sensing retrieval of maize leaf area index.
作者
王双喜
束美艳
顾晓鹤
杨贵军
张继超
韩东
郭伟
WANG Shuangxi;SHU Meiyan;GU Xiaohe;YANG Guijun;ZHANG Jichao;HAN Dong;GUO Wei(School of Surveying and Geography,Liaoning Technical University,LiaoningFuxin 123000;Beijing Research Center for Information Technology in Agriculture,Beijing 100097;College of Geomrties,Shandong University of Science and Technology Shandong Qingdao 266590;College of Geomaties,Xian University of Science and Technology,Xiau 710054;College of Information and Management Science,Henan Agrieultural University,Zhengzhou 450002,China)
出处
《中国农业科技导报》
CAS
CSCD
北大核心
2018年第12期67-73,共7页
Journal of Agricultural Science and Technology
基金
国家重点研发计划项目(2016YFD0300609)
国家自然科学基金项目(41571323
41501481)
北京市农林科学院科技创新能力建设专项(KJCX20170705)资助.
关键词
玉米
叶面积指数
归一化植被指数
遥感反演
corn
leaf area index
normalized vegetation index
remote sensing inversion