Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring

	Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring
	Wu, Mingquan 1; Zhang, Xiaoyang 1; Huang, Wenjiang 1; Niu, Zheng 1; Wang, Changyao 1; Li, Wang 1; Hao, Pengyu 1
刊名	REMOTE SENSING
	2015
卷号	7 期号:12 页码:15583-15604
关键词	HJ CCD GF-1 WFV STDFA phenology time series high spatiotemporal resolution remote sensing
通讯作者	Wu, MQ (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718,Datun Rd, Beijing 100101, Peoples R China.
英文摘要	With the recent launch of new satellites and the developments of spatiotemporal data fusion methods, we are entering an era of high spatiotemporal resolution remote-sensing analysis. This study proposed a method to reconstruct daily 30 m remote-sensing data for monitoring crop types and phenology in two study areas located in Xinjiang Province, China. First, the Spatial and Temporal Data Fusion Approach (STDFA) was used to reconstruct the time series high spatiotemporal resolution data from the Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field-of-view camera (GF-1 WFV), Landsat, and Moderate Resolution Imaging Spectroradiometer (MODIS) data. Then, the reconstructed time series were applied to extract crop phenology using a Hybrid Piecewise Logistic Model (HPLM). In addition, the onset date of greenness increase (OGI) and greenness decrease (OGD) were also calculated using the simulated phenology. Finally, crop types were mapped using the phenology information. The results show that the reconstructed high spatiotemporal data had a high quality with a proportion of good observations (PGQ) higher than 0.95 and the HPLM approach can simulate time series Normalized Different Vegetation Index (NDVI) very well with R-2 ranging from 0.635 to 0.952 in Luntai and 0.719 to 0.991 in Bole, respectively. The reconstructed high spatiotemporal data were able to extract crop phenology in single crop fields, which provided a very detailed pattern relative to that from time series MODIS data. Moreover, the crop types can be classified using the reconstructed time series high spatiotemporal data with overall accuracy equal to 0.91 in Luntai and 0.95 in Bole, which is 0.028 and 0.046 higher than those obtained by using multi-temporal Landsat NDVI data.
研究领域[WOS]	Remote Sensing
收录类别	SCI
语种	英语
WOS记录号	WOS:000367534000026
内容类型	期刊论文
源URL	[http://ir.ceode.ac.cn/handle/183411/38048]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1.[Wu, Mingquan 2.Niu, Zheng 3.Wang, Changyao 4.Li, Wang 5.Hao, Pengyu] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 6.[Zhang, Xiaoyang] S Dakota State Univ, Dept Geog, Geospatial Sci Ctr Excellence, Brookings, SD 57007 USA 7.[Huang, Wenjiang] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Lab Digital Earth Sci, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Wu, Mingquan,Zhang, Xiaoyang,Huang, Wenjiang,et al. Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring[J]. REMOTE SENSING,2015,7(12):15583-15604.
APA	Wu, Mingquan.,Zhang, Xiaoyang.,Huang, Wenjiang.,Niu, Zheng.,Wang, Changyao.,...&Hao, Pengyu.(2015).Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring.REMOTE SENSING,7(12),15583-15604.
MLA	Wu, Mingquan,et al."Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring".REMOTE SENSING 7.12(2015):15583-15604.