资源简介

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<3 d;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。  关键词： 遥感;  数字相机;  净生态系统碳交换量(NEE);  冬小麦;  物候期     Abstract: Multi\|source data and various technological methods are used in the study of vegetation phenology.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 Province.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 remote sensing data (NDVI and EVI) are the worst.The results of phenological phases of winter wheat obtained by NDVI and EVI have extremely significant correlation,and the period of green-up has the strongest 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 growing season are longer than before.

相关资源

1. 水质遥感监测的关键要素叶绿素a的反演算法研究进展
2. 基于无人机遥感技术的森林参数获取研究进展
3. 基于无线传感器网络的森林生态系统观测试验平台构建
4. 基于无人机激光雷达的森林冠层高度分析
5. 多源时序国产卫星影像的森林火灾动态监测
6. 基于无人机遥感技术的台风灾害倒伏绿化树木检测

下载说明

·如果您发现该资源不能下载，请通知管理员.gissky@gmail.com

·为确保下载的资源能正常使用，请使用[WinRAR v3.8]或以上版本解压本站资源,缺省解压密码www.gissky.net ，如果是压缩文件为分卷多文件，请依次下载每一个文件，并按照顺序命名为1.rar,2.rar,3.rar...，然后鼠标右击1.rar解压.

·为了保证您快速的下载速度，我们推荐您使用[网际快车]等专业工具下载.

·站内提供的资源纯属学习交流之用,如侵犯您的版权请与我们联系.