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Title: A hybrid color mapping approach to fusing MODIS and landsat images for forward prediction
Authors: Kwan, C
Budavari, B
Gao, F
Zhu, XL 
Keywords: Landsat
Remote sensing
Hybrid color mapping
Data fusion
Issue Date: 2018
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Remote sensing, Apr. 2018, v. 10, no. 4, 520 How to cite?
Journal: Remote sensing 
Abstract: We present a simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution, whereas Landsat images are just the opposite. Similar to earlier approaches, our goal is to fuse MODIS and Landsat images to yield high spatial and high temporal resolution images. Our approach consists of two steps. First, a mapping is established between two MODIS images, where one is at an earlier time, t1, and the other one is at the time of prediction, tp. Second, this mapping is applied to map a known Landsat image at ti to generate a predicted Landsat image at tp. Similar to the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SpatioTemporal Image-Fusion Model (STI-FM), and the Flexible Spatiotemporal DAta Fusion (FSDAF) approaches, only one pair of MODIS and Landsat images is needed for prediction. Using seven performance metrics, experiments involving actual Landsat and MODIS images demonstrated that the proposed approach achieves comparable or better fusion performance than that of STARFM, STI-FM, and FSDAF.
EISSN: 2072-4292
DOI: 10.3390/rs10040520
Rights: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
The following publication Kwan, C., Budavari, B., Gao, F., & Zhu, X. (2018). A hybrid color mapping approach to fusing MODIS and landsat images for forward prediction. Remote Sensing, 10(4), 520 is available at
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