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Open AccessArticle

A Hybrid Color Mapping Approach to Fusing MODIS and Landsat Images for Forward Prediction

1
Signal Processing, Inc., Rockville, MD 20850, USA
2
Hydrology & Remote Sensing Lab, USDA ARS, Beltsville, MD20704 USA
3
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(4), 520; https://doi.org/10.3390/rs10040520
Received: 6 March 2018 / Revised: 22 March 2018 / Accepted: 24 March 2018 / Published: 26 March 2018
(This article belongs to the Section Remote Sensing Image Processing)
We present a new, 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 t1 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. View Full-Text
Keywords: Landsat; MODIS; remote sensing; hybrid color mapping; data fusion; super-resolution Landsat; MODIS; remote sensing; hybrid color mapping; data fusion; super-resolution
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MDPI and ACS Style

Kwan, C.; Budavari, B.; Gao, F.; Zhu, X. A Hybrid Color Mapping Approach to Fusing MODIS and Landsat Images for Forward Prediction. Remote Sens. 2018, 10, 520.

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