Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/78685
Title: Assessment of spatiotemporal fusion algorithms for planet and worldview images
Authors: Kwan, C
Zhu, XL 
Gao, F
Chou, BY
Perez, D
Li, J
Shen, YZ
Koperski, K
Marchisio, G
Keywords: Image fusion
Planet
Worldview
Pansharpening
Forward prediction
Spatiotemporal
Issue Date: 2018
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Sensors (Switzerland), Apr. 2018, v. 18, no. 4, 1051 How to cite?
Journal: Sensors (Switzerland) 
Abstract: Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.
URI: http://hdl.handle.net/10397/78685
ISSN: 1424-8220
DOI: 10.3390/s18041051
Rights: Copyright © 2018 ZhonghuWu et al. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Kwan, C., Zhu, X., Gao, F., Chou, B., Perez, D., Li, J., . . . Marchisio, G. (2018). Assessment of spatiotemporal fusion algorithms for planet and worldview images. Sensors (Switzerland), 18(4), 1051 is available at https://doi.org/10.3390/s18041051
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Kwan_Assessment_Spatiotemporal_Fusion.pdf62.95 MBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents

SCOPUSTM   
Citations

6
Citations as of Mar 29, 2019

WEB OF SCIENCETM
Citations

4
Last Week
0
Last month
Citations as of Apr 6, 2019

Page view(s)

24
Citations as of May 21, 2019

Download(s)

20
Citations as of May 21, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.