{"title":"利用NDVI和气温监测邢台冬小麦物候","authors":"Junming Liu, Wencai Si","doi":"10.1109/ICCASE.2011.5997798","DOIUrl":null,"url":null,"abstract":"The Normalized Difference Vegetation Index can accurately reflect the phenology changes of a wide range of crop areas. This paper discusses the monitoring methods of returning green and heading stages of winter wheat. Xingtai in the southern Hebei in China is selected as the study area and it uses SPOT / VEGETATION Maximum Value Composite (MVC) NDVI data in period of ten days to analyze relevance of MVC NDVI and the highest temperature of the same period. Then it makes the MVC NDVI data to date with the highest air temperature, and reconstructs the NDVI time series data during the growing season of winter wheat. The NDVI curve is fitted by the asymmetric Gaussian model, and green-turning and heading stages of winter wheat are extracted by dynamic threshold method. At the same time, it makes the MVC NDVI to the middle and end of every period of ten days, and then follows the same method to extract the same phenology phases. Finally, the paper makes a comparative analysis about these methods referred above based on the field observation data. This analysis indicates that there is a significant correlation between MVC NDVI and the highest air temperature of the same period for the winter wheat in the research area. Monitoring accuracy of the starting day of returning green and heading stages can be improved by the NDVI curve combined with the highest air temperature.","PeriodicalId":369749,"journal":{"name":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Using NDVI and Air Temperature to Monitoring Winter-Wheat Phenology in Xingtai, Hebei, China\",\"authors\":\"Junming Liu, Wencai Si\",\"doi\":\"10.1109/ICCASE.2011.5997798\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Normalized Difference Vegetation Index can accurately reflect the phenology changes of a wide range of crop areas. This paper discusses the monitoring methods of returning green and heading stages of winter wheat. Xingtai in the southern Hebei in China is selected as the study area and it uses SPOT / VEGETATION Maximum Value Composite (MVC) NDVI data in period of ten days to analyze relevance of MVC NDVI and the highest temperature of the same period. Then it makes the MVC NDVI data to date with the highest air temperature, and reconstructs the NDVI time series data during the growing season of winter wheat. The NDVI curve is fitted by the asymmetric Gaussian model, and green-turning and heading stages of winter wheat are extracted by dynamic threshold method. At the same time, it makes the MVC NDVI to the middle and end of every period of ten days, and then follows the same method to extract the same phenology phases. Finally, the paper makes a comparative analysis about these methods referred above based on the field observation data. This analysis indicates that there is a significant correlation between MVC NDVI and the highest air temperature of the same period for the winter wheat in the research area. Monitoring accuracy of the starting day of returning green and heading stages can be improved by the NDVI curve combined with the highest air temperature.\",\"PeriodicalId\":369749,\"journal\":{\"name\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"volume\":\"130 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCASE.2011.5997798\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCASE.2011.5997798","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
归一化植被指数能准确反映大范围作物区域的物候变化。探讨了冬小麦返青期和抽穗期的监测方法。选取河北南部邢台地区为研究区,利用10 d的SPOT / VEGETATION Maximum Value Composite (MVC) NDVI数据,分析MVC NDVI与同期最高气温的相关性。然后将MVC NDVI数据提取到气温最高的年份,重构出冬小麦生长期的NDVI时间序列数据。采用非对称高斯模型拟合NDVI曲线,采用动态阈值法提取冬小麦的转绿期和抽穗期。同时,将MVC NDVI提取到每10天周期的中期和末期,然后按照相同的方法提取相同的物候期。最后,结合野外观测资料,对上述几种方法进行了对比分析。分析表明,研究区小麦MVC NDVI与同期最高气温呈显著相关。将NDVI曲线与最高气温相结合,可以提高回果岭起始日和抽穗阶段的监测精度。
Using NDVI and Air Temperature to Monitoring Winter-Wheat Phenology in Xingtai, Hebei, China
The Normalized Difference Vegetation Index can accurately reflect the phenology changes of a wide range of crop areas. This paper discusses the monitoring methods of returning green and heading stages of winter wheat. Xingtai in the southern Hebei in China is selected as the study area and it uses SPOT / VEGETATION Maximum Value Composite (MVC) NDVI data in period of ten days to analyze relevance of MVC NDVI and the highest temperature of the same period. Then it makes the MVC NDVI data to date with the highest air temperature, and reconstructs the NDVI time series data during the growing season of winter wheat. The NDVI curve is fitted by the asymmetric Gaussian model, and green-turning and heading stages of winter wheat are extracted by dynamic threshold method. At the same time, it makes the MVC NDVI to the middle and end of every period of ten days, and then follows the same method to extract the same phenology phases. Finally, the paper makes a comparative analysis about these methods referred above based on the field observation data. This analysis indicates that there is a significant correlation between MVC NDVI and the highest air temperature of the same period for the winter wheat in the research area. Monitoring accuracy of the starting day of returning green and heading stages can be improved by the NDVI curve combined with the highest air temperature.