Mapping winter wheat using phenological feature of peak before winter on the North China Plain based on time-series MODIS data
文献类型: 外文期刊
作者:
Tao Jian-bin
1
;
Wu Wen-bin
1
;
Zhou Yong
2
;
Wang Yu
2
;
Jiang Yan
2
;
作者机构: 1.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agriinformat, Minist Agr, Beijing 100081, Peoples R China
2.Cent China Normal Univ, Sch Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China
关键词: time-series MODIS data;phenological feature;peak before wintering;winter wheat mapping
期刊名称:JOURNAL OF INTEGRATIVE AGRICULTURE ( 影响因子:2.848; 五年影响因子:2.979 )
ISSN: 2095-3119
年卷期: 2017 年 16 卷 2 期
页码:
收录情况: SCI
摘要: By employing the unique phenological feature of winter wheat extracted from peak before winter (PBW) and the advantages of moderate resolution imaging spectroradiometer (MODIS) data with high temporal resolution and intermediate spatial resolution, a remote sensing-based model for mapping winter wheat on the North China Plain was built through integration with Landsat images and land-use data. First, a phenological window, PBW was drawn from time-series MODIS data. Next, feature extraction was performed for the PBW to reduce feature dimension and enhance its information. Finally, a regression model was built to model the relationship of the phenological feature and the sample data. The amount of information of the PBW was evaluated and compared with that of the main peak (MP). The relative precision of the mapping reached up to 92% in comparison to the Landsat sample data, and ranged between 87 and 96% in comparison to the statistical data. These results were sufficient to satisfy the accuracy requirements for winter wheat mapping at a large scale. Moreover, the proposed method has the ability to obtain the distribution information for winter wheat in an earlier period than previous studies. This study could throw light on the monitoring of winter wheat in China by using unique phenological feature of winter wheat.
- 相关文献
作者其他论文 更多>>
-
Selenium distribution and nitrate metabolism in hydroponic lettuce (Lactuca sativa L.): Effects of selenium forms and light spectra
作者:Bian Zhong-hua;Lei Bo;Cheng Rui-feng;Li Tao;Yang Qi-chang;Bian Zhong-hua;Wang Yu
关键词:selenium; light spectra; nitrates; nitrogen metabolism enzymes; LEDs; Lactuca sativa L.
-
Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information
作者:Xu Shi-wei;Wang Yu;Wang Sheng-wei;Xu Shi-wei;Wang Sheng-wei;Li Jian-zheng;Xu Shi-wei;Wang Yu;Li Jian-zheng;Xu Shi-wei;Wang Yu;Wang Sheng-wei;Li Jian-zheng
关键词:agricultural product information; monitoring and early warning; threshold; multi-temporal; real-time dynamics
-
Predominance of precipitation event controls ecosystem CO2 exchange in an Inner Mongolian desert grassland, China
作者:Wang Yuhui;Chen Jun;Song Jianmin;Wang Yuhui;Chen Jiquan;Zhou Guangsheng;Shao Changliang;Shao Changliang;Wang Yu
关键词:Extreme precipitation; Ecosystem CO2 exchange; Accumulative NEE; Nonlinear equation; Desert grassland
-
Spatio-temporal changes in rice area at the northern limits of the rice cropping system in China from 1984 to 2013
作者:Long Yu-qiao;Tang Peng-qin;Li Zheng-guo;Wu Wen-bin;Hu Ya-nan;Yang Peng;Tan Jie-yang
关键词:paddy rice;Landsat images;artificial neural network;Heilongjiang Province
-
Mapping regional cropping patterns by using GF-1 WFV sensor data
作者:Song Qian;Zhou Qing-bo;Wu Wen-bin;Hu Qiong;Lu Miao;Liu Shu-bin
关键词:crop mapping;GF-1;object-based;Random Forest
-
Comparative analysis of GF-1, HJ-1, and Landsat-8 data for estimating the leaf area index of winter wheat
作者:Li He;Chen Zhong-xin;Jiang Zhi-wei;Wu Wen-bin;Ren Jian-qiang;Liu Bin;Hasi, Tuya;Jiang Zhi-wei;Hasi, Tuya
关键词:GF-1 WFV;HJ-1 CCD;Landsat-8 OLI;leaf area index;PROSAIL;vegetation indices
-
Perspective of Chinese GF-1 high-resolution satellite data in agricultural remote sensing monitoring
作者:Zhou Qing-bo;Yu Qiang-yi;Liu Jia;Wu Wen-bin;Tang Hua-jun;Wu Wen-bin
关键词:GF-1;high resolution;agricultural monitoring;remote sensing;CHARMS



