过去几十年中，时空融合技术为实现长时间序列观测提供了一种经济高效的方法，但此类方法对结构信息的保留能力较弱，同时计算的效率也比较低。该研究对比分析主流时空融合方法与对象级(Object Level，OL)时空融合方法，在归一化植被指数(NDVI)和地表温度(LST)的融合效果和融合效率的差异。文章以大理地区作为研究区，使用 9 种时空融合方法对Landsat和MODIS数据做融合处理，通过目视判别和统计分析，评估其在时空模拟效果和计算效率上的差异。实验表明:1)OL-FSDAF2。0(Object Level-Flexible Spatiotemporal Data Fusion 2。0)相较于其他时空融合方法更好地恢复了地表真实信息和结构信息;2)对象级时空融合方法在计算效率方面比其余像素级时空融合方法提高20。70倍;3)对象级时空融合方法对地物时间动态特征细节的捕捉能力均比像素级时空融合方法高。总的来说，对象级时空融合方法具有较高的计算效率和更精确的融合效果，其中，OL-FSDAF2。0 在复杂地表区域与模拟地表覆盖动态变化中表现较好。
Application Analysis of Object-Level(OL)Spatio-Temporal Fusion Model in NDVI and LST——Taking Dali Area as an Example
In the past decades,spatio-temporal fusion technology has provided an economical and efficient method to realize long-time series observation,but this method has a weak ability to retain structural information and low computational efficiency.In this study,the difference of fusion effect and fusion efficiency between mainstream spatiotemporal fusion methods(including STARFM,ESTARFM,Fit-FC,FSDAF)and Object-level spatiotemporal fusion methods in normalized vegetation index(NDVI)and land surface temperature(LST)is compared and analyzed.In this paper,Dali area is taken as the research area,and nine spatio-temporal fusion methods are used to fuse Landsat and MODIS data,and the differences in spatio-temporal simulation effect and calculation efficiency are evaluated through visual discrimination and statistical analysis.Experiments show that:1)Compared with other spatio-temporal fusion methods,OL-FSDAF2.0 can better restore the real information and structural information of the surface;2)The computational efficiency of object-level spatiotemporal fusion method is 20.7081 times higher than other pixel-level spatiotemporal fusion methods;3)Object-level spatio-temporal fusion method has higher ability to capture the details of temporal dynamic features of ground objects than pixel-level spatio-temporal fusion method.Generally speaking,the object-level spatio-temporal fusion method has higher computational efficiency and more accurate fusion effect,among which OL-FSDAF2.0 performs well in complex surface areas and simulated dynamic changes of surface cover.
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