摘要
多源数据与其技术方法逐渐被应用于植被物候的研究当中,但基于多源数据物候识别方法间的差异性比较及定量化评估工作还有待加强。以山东禹城农田生态系统为例,探讨了基于多源数据,NDVI、EVI、数字相机图片、碳通量数据(NEE)以及人工实测数据获取的冬小麦主要生育日期的结果进行差异比较及定量化评估。结果表明:(1)通过碳通量数据获取的主要生育日期的计算结果与人工实测结果最接近,各阶段差异均<3d;通过数字相机图片获取的结果仅次于通过碳通量数据获取的结果,而通过遥感数据NDVI、EVI获取的结果与人工实测结果差距最大;(2)通过NDVI、EVI两种数据获取的冬小麦主要生育期结果具有极显著的相关性,最高达到R2=0.857(P<0.001);(3)基于多源数据获取的冬小麦主要生育期的计算结果,均显示出禹城站冬小麦返青期提前,蜡熟期推迟,生长季长度变长的年际变化特征。
Multi-source data and various technological methods are used in the study of vegetation phenolo- gy.But the differences of various phenological methods based on multi-source data still need to be explored. We initiated research on winter wheat field ecosystem northern China in Yucheng City of Shandong Prov- ince. Here we explored the differences of the main phenological phases of winter wheat obtained from multi-source data : normalized difference vegetation index, enhanced vegetation index, digital camera, carbon flux data and field-measured data.The main phenological phases of winter wheat are the date of green-up, maturity,and the length of growing season. We found the phenological phases of winter wheat obtained from carbon flux data are the nearest to the result of field-measured, and the differences of various periods are less than 3d.The results obtained from the digital camera are poor than the carbon flux data,and the re- mote sensing data (NDVI and EVI) are the worst.The results of phenological phases of winter wheat ob- tained by NDVI and EVI have extremely significant correlation,and the period of green-up has the stron- gest correlation (R2 =0.857,P〈0.001).All the results of growth period of winter wheat based on multi- source data showed that the dates of green-up are advanced, maturity are delayed, and the lengths of grow- ing season are longer than before.
作者
冯艾琳
何洪林
刘利民
任小丽
张黎
葛蓉
赵凤华
Feng Ailin He Honglin Liu Limin Ren Xiaoli Zhang Li Ge Rong Zhao Fenghua(Liaoning Branch of China Meteorological Administration Training Centre ,Shenyang 110166,China Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences ,Beijing 100101 ,China University of Chinese Academy of Sciences ,Beijing 100049 ,China)
出处
《遥感技术与应用》
CSCD
北大核心
2016年第5期958-965,共8页
Remote Sensing Technology and Application
基金
中国科学院战略性先导科技专项(XDA05050600)
国家科技支撑计划项目(2013BAC03B00)
国家重大科学研究计划课题(2015CB954102)