CLC number: S511
On-line Access: 2015-10-03
Received: 2015-04-15
Revision Accepted: 2015-09-14
Crosschecked: 2015-09-17
Cited: 6
Clicked: 4487
Jing Wang, Jing-feng Huang, Xiu-zhen Wang, Meng-ting Jin, Zhen Zhou, Qiao-ying Guo, Zhe-wen Zhao, Wei-jiao Huang, Yao Zhang, Xiao-dong Song. Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images[J]. Journal of Zhejiang University Science B, 2015, 16(10): 832-844.
@article{title="Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images",
author="Jing Wang, Jing-feng Huang, Xiu-zhen Wang, Meng-ting Jin, Zhen Zhou, Qiao-ying Guo, Zhe-wen Zhao, Wei-jiao Huang, Yao Zhang, Xiao-dong Song",
journal="Journal of Zhejiang University Science B",
volume="16",
number="10",
pages="832-844",
year="2015",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1500087"
}
%0 Journal Article
%T Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images
%A Jing Wang
%A Jing-feng Huang
%A Xiu-zhen Wang
%A Meng-ting Jin
%A Zhen Zhou
%A Qiao-ying Guo
%A Zhe-wen Zhao
%A Wei-jiao Huang
%A Yao Zhang
%A Xiao-dong Song
%J Journal of Zhejiang University SCIENCE B
%V 16
%N 10
%P 832-844
%@ 1673-1581
%D 2015
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1500087
TY - JOUR
T1 - Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images
A1 - Jing Wang
A1 - Jing-feng Huang
A1 - Xiu-zhen Wang
A1 - Meng-ting Jin
A1 - Zhen Zhou
A1 - Qiao-ying Guo
A1 - Zhe-wen Zhao
A1 - Wei-jiao Huang
A1 - Yao Zhang
A1 - Xiao-dong Song
J0 - Journal of Zhejiang University Science B
VL - 16
IS - 10
SP - 832
EP - 844
%@ 1673-1581
Y1 - 2015
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1500087
Abstract: Accurate estimation of rice phenology is of critical importance for agricultural practices and studies. However, the accuracy of phenological parameters extracted by remote sensing data cannot be guaranteed because of the influence of climate, e.g. the monsoon season, and limited available remote sensing data. In this study, we integrate the data of HJ-1 CCD and Landsat-8 operational land imager (OLI) by using the ordinary least-squares (OLS), and construct higher temporal resolution vegetation indices (VIs) time-series data to extract the phenological parameters of single-cropped rice. Two widely used VIs, namely the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2), were adopted to minimize the influence of environmental factors and the intrinsic difference between the two sensors. Savitzky-Golay (S-G) filters were applied to construct continuous VI profiles per pixel. The results showed that, compared with NDVI, EVI2 was more stable and comparable between the two sensors. Compared with the observed phenological data of the single-cropped rice, the integrated VI time-series had a relatively low root mean square error (RMSE), and EVI2 showed higher accuracy compared with NDVI. We also demonstrate the application of phenology extraction of the single-cropped rice in a spatial scale in the study area. While the work is of general value, it can also be extrapolated to other regions where qualified remote sensing data are the bottleneck but where complementary data are occasionally available.
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