a modified spatiotemporal fusion algorithm using phenological information for predicting reflectance of paddy rice in southern china

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ID: 192975
2018
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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.
Reference Key
liu2018remotea Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Mengxue Liu;Xiangnan Liu;Ling Wu;Xinyu Zou;Tian Jiang;Bingyu Zhao
Journal Journal of pharmacological sciences
Year 2018
DOI
10.3390/rs10050772
URL
http://www.mdpi.com/2072-4292/10/5/772
Keywords Keywords not found

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