首页 >  2001, Vol. 5, Issue (6) : 442-447

摘要

全文摘要次数: 4138 全文下载次数: 27
引用本文:

DOI:

10.11834/jrs.20010607

收稿日期:

2000-09-28

修改日期:

2000-12-22

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利用NOAA NDVI数据集监测冬小麦生育期的研究
1.中国农业大学 资源环境学院,北京 100094;2.Wageningen Agricultural University,The Nehterlands
摘要:

探索了利用NDVI研究作物生育期的方法,对黄淮海冬麦区的返青期、抽穗期、成熟期进行了估测,并利用地面实际观测资料进行了验证。结果表明,NDVI数据对大范围农作物生育期监测是可行的。冬小麦遥感反青期由南到北依次推迟,符合春季绿波由南到北推移规律。对冬小麦遥感生育期年际变化分析表明,黄淮海平原返青期变化相对较大,而抽穗期和成熟期变化较小。根据历年月平均温度与返青期分析,冬小麦返青日期与2月份平均温度密切相关。对于局部地区,利用5d合成1km分辨率数据,且按农业生态分区分别制定生育期判别标准,估测效果将更好。

关键词:

冬小麦  生育期  NOAA NDVI
Monitoring Phenological Key Stages of Winter Wheat with NOAA NDVI Data
Abstract:

The objective of this study was to monitor phenological stages of winter wheat in HHH plain of China. Three key phenological stages were defined based on NOAA/AVHRR NDVI time series data collected in the HHH plain of China from 1990 through 2000. In a winter wheat_summer maize rotation system, the recovering, heading and maturity stages of winter wheat were recorded using 6 km resolution decadal NDVI. Recovering of winter wheat was identified by two consecutive NDVI increments after a period of stagnating values. Similarly, maturity of winter wheat was identified by the last two consecutive NDVI decrements. The heading stage was identified by maximum NDVI value. The satellite_derived data proved to be consistent with the 'green wave' moving through the HHH Plain in spring. Through analysis of historical climate data, the recovering stage of winter wheat recorded by satellite was closely correlated to the temperatures measured in February, significant correlation between phenological stages and rainfall could not be detected. Comparison with synchronous phenological observations on the ground confirmed the coherence of satellite_derived phenology data. The inter_annual variability of recovering stage is higher than that of heading and maturity stages. Application of irrigation and the relatively short ten_year period for which data were available explain why inter_annual fluctuation of crop phenology was relatively small. The 6 km spatial resolution decadal NDVI limited the prediction accuracy. It is expected that satellite data with greater spatial and temporal resolutions and the improved smoothing methods will further increase the precision of the estimated data.

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