摘要
鉴于不同植被物候遥感提取方法在冬小麦物候提取中的对比研究鲜有报道,利用4种常用的植被物候遥感提取方法——动态阈值法、延后滑动平均法、导数法和Logistic函数拟合法,以及一种基于累积植被指数提取植被物候提取的方法iNDVI-Logistic,提取华北平原冬小麦返青期和成熟期,并从空间格局分析和地面观测数据验证2个方面对5种方法提取结果进行对比。结果表明,5种方法监测的冬小麦物候期在空间格局上较为一致,从南向北逐渐推迟;利用地面观测数据进行验证,动态阈值法和iNDVI-Logistic方法监测冬小麦返青期精度相近,具有极显著相关关系,5种方法获得的冬小麦成熟期精度较高,与真实值的偏差都在0.1之内,且都通过极显著关系检验,其中iNDVI-Logistic方法提取结果精度最好,相关系数达到0.578。总体来看,综合作物生长累积模型和函数拟合法的iNDVI-Logistic法在华北平原冬小麦物候研究中可以获得较好的精度。多种方法的比较可以弄清每种方法在华北平原冬小麦物候提取中的优缺点和适宜性,为以后相关研究提供参考。
High precision of phenology is one of the key parameters in the study of crop condition and estimating crop yield.However,studies on comparison of different methods for phenology extraction of winter wheat are rare.In this study,satellite derived Start of Season(SOS)and End of Season(EOS)dates of winter wheat in North China Plain were obtained from the SPOT VGT NDVI dataset by five methods,namely,dynamic threshold method,delayed moving average method(DMA),derivative method,logistic analysis and iNDVI logistic method.The results showed that the spatial patterns of SOS and EOS from these five methods generally presented a similar performance in North China Plain,generally delayed from south to north,but regional differences occurred between them.Compared with station data,accuracy of SOS agreed well between dynamic threshold method and iNDVI logistic method.Bias between satellite derived EOS using five methods and observation values was less than0.1,and highly significant correlations were also got.Accuracy of EOS from iNDVI Logistic method was the highest(r=0.578,RMSE=6.02days bias=-0.02).This comparative study can help users to understand the advantages and limitations of each phenology extraction method,and choose the appropriate method to reduce the errors and improve the accuracy in their applications.
作者
侯学会
隋学艳
梁守真
王猛
董敏
HOU Xuehui;SUI Xueyan;LIANG Shouzhen;WANG Meng;DONG Min(Institute of Agriculture Sustainable Development,Shandong Academy of Agriculture Sciences,Jinan 250100,China;Key Laboratory of East China Urban Agriculture,Ministry of Agriculture,Jinan 250100,China;Changyi Seismic Station,Weifang,Shandong 261300,China)
出处
《遥感信息》
CSCD
北大核心
2017年第6期65-70,共6页
Remote Sensing Information
基金
山东省自然科学基金(ZR2014YL016)
国家自然科学基金(41401407)
山东省科技厅重点产业关键技术项目(2016CYJS03A01-1)
关键词
返青期
成熟期
冬小麦
归一化植被指数
华北平原
green up
maturity
winter wheat
normalized difference vegetation index
North China Plain
