A novel framework to assess all-round performances of spatiotemporal fusion models

Xiaolin Zhu, Wenfeng Zhan, Junxiong Zhou, Xuehong Chen, Zicong Liang, Shuai Xu, Jin Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)


Spatiotemporal data fusion, as a feasible and low-cost solution for producing time-series satellite images with both high spatial and temporal resolution, has undergone rapid development over the past two decades with more than one hundred spatiotemporal fusion methods developed. Accuracy assessment of fused images is crucial for users to select appropriate methods for real-world applications. However, commonly used assessment metrics do not comprehensively cover multiple aspects of spatiotemporal fused image quality, contain redundant information, and are not comparable across different study areas. To address these problems, this study proposed a novel framework to assess all-round performances of spatiotemporal fusion methods. Four accuracy metrics, including RMSE, AD, Edge, and local binary patterns (LBP), were selected as the optimal set of assessment metrics according to the assessment criteria. These metrics not only quantify the spectral and spatial information in the fused images but also greatly alleviate information redundancy and feature computational simplicity. Furthermore, inspired by Taylor diagrams, we designed an all-round performance assessment (APA) diagram to provide a visual tool for a comprehensive assessment of the performance of spatiotemporal fusion methods, supporting cross-comparison of different spatiotemporal fusion methods by considering the effects of input data and land surface characteristics. The case study in three typical sites demonstrated that the proposed framework can better differentiate the performances of six spatiotemporal fusion methods. This new framework can promote the cross-comparison of different spatiotemporal fusion methods and guide users to select suitable methods for real-world applications, as well as facilitate the establishment of a standard accuracy assessment procedure for spatiotemporal fusion methods.

Original languageEnglish
Article number113002
JournalRemote Sensing of Environment
Publication statusPublished - 1 Jun 2022


  • Accuracy assessment
  • Inter-comparison
  • Model performance
  • Spatiotemporal fusion
  • Taylor diagram

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences


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