Abstract
It is challenging to acquire satellite sensor data with both fine spatial and fine temporal resolution, especially for monitoring at global scales. Among the widely used global monitoring satellite sensors, Landsat data have a coarse temporal resolution, but fine spatial resolution, while moderate resolution imaging spectroradiometer (MODIS) data have fine temporal resolution, but coarse spatial resolution. One solution to this problem is to blend the two types of data using spatio-temporal fusion, creating images with both fine temporal and fine spatial resolution. However, reliable geometric registration of images acquired by different sensors is a prerequisite of spatio-temporal fusion. Due to the potentially large differences between the spatial resolutions of the images to be fused, the geometric registration process always contains some degree of uncertainty. This article analyzes quantitatively the influence of geometric registration error on spatio-temporal fusion. The relationship between registration error and the accuracy of fusion was investigated under the influence of different temporal distances between images, different spatial patterns within the images and using different methods (i.e., spatial and temporal adaptive reflectance fusion model (STARFM), and Fit-FC; two typical spatio-temporal fusion methods). The results show that registration error has a significant impact on the accuracy of spatio-temporal fusion; as the registration error increased, the accuracy decreased monotonically. The effect of registration error in a heterogeneous region was greater than that in a homogeneous region. Moreover, the accuracy of fusion was not dependent on the temporal distance between images to be fused, but rather on their statistical correlation. Finally, the Fit-FC method was found to be more accurate than the STARFM method, under all registration error scenarios.
Highlights
I N RECENT years, remote sensing has developed rapidly and has been applied widely, for example, in land use and land cover change monitoring [1], vegetation monitoring [2], carbon sequestration monitoring [3], revealing ecosystem climate feedbacks [4], evaluating forest and ecological environments [5], and urban monitoring [6]
The results suggest that the registration error has a greater impact on the heterogeneous region than for the homogeneous region
The misregistration of images at different spatial resolutions is a critical issue in spatio-temporal fusion
Summary
I N RECENT years, remote sensing has developed rapidly and has been applied widely, for example, in land use and land cover change monitoring [1], vegetation monitoring [2], carbon sequestration monitoring [3], revealing ecosystem climate feedbacks [4], evaluating forest and ecological environments [5], and urban monitoring [6]. The basic principle of weighting function-based methods is to calculate the reflectance of the center fusion pixel through a weighting function which takes full account of the spectral, temporal, and spatial information in similar pixels. Gao et al [8] proposed the spatial and temporal adaptive reflectance fusion model (STARFM), which includes comprehensive consideration of the spectral difference between MODIS and Landsat ETM+ data, the temporal difference between MODIS data of the same pixel location, and the distance between the center pixel and similar pixels. A conversion coefficient was introduced to express this relationship quantitatively, which ensures more accurate prediction of the reflectance of
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
