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	Monitoring of winter wheat distribution and phenological phases based on modis time-series: a case study in the yellow river delta, china
	Chu Lin1,2; Liu Qing-sheng1; Huang Chong1; Liu Gao-huan1
刊名	Journal of integrative agriculture
	2016
卷号	15期号:10页码:2403-2416
关键词	Remote sensing monitoring Time-series Winter wheat discrimination Yellow river delta Phenology detection
ISSN号	2095-3119
DOI	10.1016/s2095-3119(15)61319-3
通讯作者	Liu gao-huan(liugh@lreis.ac.cn)
英文摘要	Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. here, we present mechanisms of winter wheat discrimination and phenological detection in the yellow river delta (yrd) region using moderate resolution imaging spectroradiometer (modis) time-series data. the normalized difference vegetation index (ndvi) was obtained by calculating the surface reflectance in red and infrared. we used the savitzky-golay filter to smooth time series ndvi curves. we adopted a two-step classification to identify winter wheat. the first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. we used the double gaussian model and the maximum curvature method to extract phenology. due to the characteristics of the time-series profiles for winter wheat, a double gaussian function method was selected to fit the temporal profile. a maximum curvature method was performed to extract phenological phases. phenological phases such as the green-up, heading and harvesting phases were detected when the ndvi curvature exhibited local maximum values. the extracted phenological dates then were validated with records of the ground observations. the spatial patterns of phenological phases were investigated. this study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. the phenological result was comparable to the ground observation at the municipal level. the average green-up date for the whole region occurred on march 5, the average heading date occurred on may 9, and the average harvesting date occurred on june 5. the spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. this study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.
WOS关键词	CENTRAL GREAT-PLAINS ; LAND-COVER ; VEGETATION INDEX ; ACREAGE ESTIMATION ; BRAZILIAN CERRADO ; SATELLITE IMAGERY ; CROP AREA ; NDVI DATA ; CLASSIFICATION ; RESOLUTION
WOS研究方向	Agriculture
WOS类目	Agriculture, Multidisciplinary
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000385470500023
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2374873
专题	中国科学院大学
通讯作者	Liu Gao-huan
作者单位	1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Chu Lin,Liu Qing-sheng,Huang Chong,et al. Monitoring of winter wheat distribution and phenological phases based on modis time-series: a case study in the yellow river delta, china[J]. Journal of integrative agriculture,2016,15(10):2403-2416.
APA	Chu Lin,Liu Qing-sheng,Huang Chong,&Liu Gao-huan.(2016).Monitoring of winter wheat distribution and phenological phases based on modis time-series: a case study in the yellow river delta, china.Journal of integrative agriculture,15(10),2403-2416.
MLA	Chu Lin,et al."Monitoring of winter wheat distribution and phenological phases based on modis time-series: a case study in the yellow river delta, china".Journal of integrative agriculture 15.10(2016):2403-2416.

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