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Remote Sens. 2018, 10(5), 772; https://doi.org/10.3390/rs10050772

A Modified Spatiotemporal Fusion Algorithm Using Phenological Information for Predicting Reflectance of Paddy Rice in Southern China

School of Information Engineering, China University of Geosciences, Beijing 100083, China
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Received: 18 April 2018 / Revised: 8 May 2018 / Accepted: 14 May 2018 / Published: 17 May 2018
(This article belongs to the Special Issue Multisensor Data Fusion in Remote Sensing)
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Abstract

Satellite data for studying surface dynamics in heterogeneous landscapes are missing due to frequent cloud contamination, low temporal resolution, and technological difficulties in developing satellites. A modified spatiotemporal fusion algorithm for predicting the reflectance of paddy rice is presented in this paper. The algorithm uses phenological information extracted from a moderate-resolution imaging spectroradiometer enhanced vegetation index time series to improve the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). The algorithm is tested with satellite data on Yueyang City, China. The main contribution of the modified algorithm is the selection of similar neighborhood pixels by using phenological information to improve accuracy. Results show that the modified algorithm performs better than ESTARFM in visual inspection and quantitative metrics, especially for paddy rice. This modified algorithm provides not only new ideas for the improvement of spatiotemporal data fusion method, but also technical support for the generation of remote sensing data with high spatial and temporal resolution. View Full-Text
Keywords: spatiotemporal data fusion; phenological information; EVI time series; ESTARFM; paddy rice spatiotemporal data fusion; phenological information; EVI time series; ESTARFM; paddy rice
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liu, M.; Liu, X.; Wu, L.; Zou, X.; Jiang, T.; Zhao, B. A Modified Spatiotemporal Fusion Algorithm Using Phenological Information for Predicting Reflectance of Paddy Rice in Southern China. Remote Sens. 2018, 10, 772.

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