An Improved Image Fusion Approach Based on Enhanced Spatial and Temporal the Adaptive Reflectance Fusion Model

Remote Sensing

Dongjie Fu¹  Baozhang Chen¹  Juan Wang²  Xiaolin Zhu³ 

[1] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Beijing 100101, China;Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong 8520, China; E-Mail:;Department of Geography, The Ohio State University, Columbus, OH 43210, USA; E-Mail:

关键词: image fusion;    reflectance;    Landsat;    MODIS;   

DOI  :  10.3390/rs5126346

来源: mdpi

【 摘 要 】

High spatiotemporal resolution satellite imagery is useful for natural resource management and monitoring for land-use and land-cover change and ecosystem dynamics. However, acquisitions from a single satellite can be limited, due to trade-offs in either spatial or temporal resolution. The spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM (ESTARFM) were developed to produce new images with high spatial and high temporal resolution using images from multiple sources. Nonetheless, there were some shortcomings in these models, especially for the procedure of searching spectrally similar neighbor pixels in the models. In order to improve these models’ capacity and accuracy, we developed a modified version of ESTARFM (mESTARFM) and tested the performance of two approaches (ESTARFM and mESTARFM) in three study areas located in Canada and China at different time intervals. The results show that mESTARFM improved the accuracy of the simulated reflectance at fine resolution to some extent.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland