摘要
MODIS-NDVI是广泛使用的植被指数之一,但是基于全球算法开发的植被指数产品依然有许多噪音。在多云多雨的东南亚地区,这些噪音严重影响了数据质量和数据的可用性。根据2010年Terra-MODIS和Aqua-MODIS两个16 d植被指数产品的数据噪音分布情况,研发了二颗卫星MODIS-NDVI再分析(加密、去噪音、数据重建)方法,即首先根据象元真实时间(Day of Year,DOY)和数据质量(QA)把两个16 d数据序列合并为一个8 d数据序列,然后利用象元质量信息(QA)和Timesat软件提供的时间序列重建模型(S-G),对低质量的象元进行了重建。最后获得东南亚地区2010年时间分辨率8d、月度空间分辨率为250m的MODIS-NDVI时间序列重建数据集。数据集由46个每8天重建数据文件包和12个每月重建数据文件包组成。数据采用.tif格式存储,数据量为47.68 GB(压缩为9.77 GB)。
MODIS-NDVI is one of the most widely used parameters for global change research, but the noises from various factors have gravely impaired its credibility. This happens especially in cloudy Southeast Asia. This reanalysis dataset ameliorate the noise problem in two steps. First, two 16-day time NDVI serials(Terra-and Terra-MODIS) were combined into 8-day serials by actual DOY(Day of the Year, 2010) and QA(Quality Assurance). Second, newly formed 8-day NDVI time serials were reanalyzed using S-G algorithm. By using QA as weight factor, good quality data were reserved, and poor data were rebuilt. Visual inspection showed that noises from residual clouds were greatly removed, and spatial patterns and temporal profiles became more informative. The 8-day/Monthly 250 m dataset are delivered in 58 files with.tif data format, the data size is 47.68 GB.
作者
王正兴
曹云锋
Wang, Z.X.;Cao, Y.F.(Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Sciences State Key Lab of Resources and Environmental Information System,Beijing 100101,China;Beijing Forestry University,Beijing 100083,China)
出处
《全球变化数据学报（中英文）》
2017年第3期317-323,317-323,共14页
Journal of Global Change Data & Discovery
基金
中华人民共和国科学技术部(2016YFA0600201,2015DFA11360)
中国科学院(KZZD-EW-08-01-02-01,TSYJS04)
