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Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images 被引量:3
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作者 Jing WANG Jing-feng HUANG +7 位作者 Xiu-zhen WANG Meng-ting JIN Zhen ZHOU qiao-ying guo Zhe-wen ZHAO Wei-jiao HUANG Yao ZHANG Xiao-dong SONG 《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》 SCIE CAS CSCD 2015年第10期832-844,共13页
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... 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 H J-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 param- eters 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. 展开更多
关键词 Phenological parameters INTERCALIBRATION Vegetation index H J-1 CCD Landsat-80LI
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