Mapping winter wheat using phenological feature of peak before winter on the North China Plain based on time-series MODIS data

Abstract 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.

[1]  Wen-Bin Wu,et al.  Mapping Spatial and Temporal Variations of Leaf Area Index for Winter Wheat in North China , 2007 .

[2]  Wu Wenbin,et al.  Recent Progresses in Monitoring Crop Spatial Patterns by Using Remote Sensing Technologies , 2010 .

[3]  Damien Sulla-Menashe,et al.  Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index , 2012 .

[4]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[5]  B. Wardlow,et al.  Analysis of time-series MODIS 250 m vegetation index data for crop classification in the U.S. Central Great Plains , 2007 .

[6]  Per Jönsson,et al.  TIMESAT - a program for analyzing time-series of satellite sensor data , 2004, Comput. Geosci..

[7]  Shen Shuang-he,et al.  Crop classification by remote sensing based on spectral analysis , 2012 .

[8]  Hang Yang,et al.  Winter wheat planting area extraction based on MODIS EVI image time series , 2010 .

[9]  Liangyun Liu,et al.  Monitoring winter wheat GPP in Huabei Plain using remote sensing and flux tower , 2011 .

[10]  Lu Linlin,et al.  Extraction method of winter wheat phenology from time series of SPOT/VEGETATION data. , 2009 .

[11]  Huajun Tang,et al.  Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[12]  Huadong Guo,et al.  Detecting winter wheat phenology with SPOT-VEGETATION data in the North China Plain , 2014 .

[13]  Chen Zhongxin,et al.  Crop discrimination in Northern China with double cropping systems using Fourier analysis of time-series MODIS data , 2008 .

[14]  B. Wardlow,et al.  Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the U.S. Central Great Plains , 2008 .

[15]  Pan Yaozhong Crop area estimation based on MODIS-EVI time series according to distinct characteristics of key phenology phases:a case study of winter wheat area estimation in small-scale area , 2011 .

[16]  C. Justice,et al.  A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data , 2010 .

[17]  Li Qiangzi Review of Overseas Crop Monitoring Systems with Remote Sensing , 2010 .

[18]  Jiyuan Liu,et al.  Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s , 2014, Journal of Geographical Sciences.