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引用本文:

DOI:

10.11834/jrs.20040613

收稿日期:

2003-07-29

修改日期:

2004-03-08

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复种指数遥感监测方法
中国科学院 遥感应用研究所,北京 100101
摘要:

复种指数是反映水土光与自然资源利用程度的指标 ,其实质是沿时间序列 ,反映某一种植制度对耕地的利用程度。联系复种指数与时间序列NDVI曲线的纽带是农作物年内的循环规律。时间序列的NDVI值蕴涵着植被的生长和枯萎的年循环节律 ,经时间序列谐函数分析法 (HarmonicAnalysisofTimeSeries ,HANTS)重构的NDVI曲线 ,可以准确地反映农作物的出苗、拔节、抽穗、收获等物理过程。因此 ,根据时间序列的NDVI曲线的周期性 ,可以反向捕捉到耕地农作物动态的信息 ,进而得到耕地的复种指数。本文依据上述原理 ,提出复种指数遥感监测的方法 ,然后用 1999年至 2002年4年的VGT(SPOT4卫星vegetation数据 )旬合成NDVI时间序列数据集提取了复种指数 ,并利用地面样区观测结果和统计数据进行检验 ,取得很高的精度。

A Methodology for Retrieving Cropping Index from NDVI Profile
Abstract:

Cropping index is a very important indicator, which reflects the situation and degree of arable land to be used by a certain planting system at a certain period. Crop growth dynamic can be monitored by the time series of NDVI data. The differences of crop growth show in the curve of time series of NDVI clearly. The curve of time series of NDVI describes the crop process of seeding, jointing, tasseling, and harvesting and so on. There exist some peaks and valleys on the curve of time series of NDVI. These peaks correspond the period of crop tasseling, and valleys the period of crop harvesting. The link that connects the cropping index with a time series of NDVI is the seasonal rhythm of agricultural crops in a year. Time series of NDVI contain the rhythm of vegetation growth and wilt. But due to cloud contamination, the curve of time series of NDVI has a lot of noise. This paper tried to remove the cloud contamination from the curve of time series of NDVI with the assistance of HANTS software. The reconstructed time series of NDVI can accurately reflect the biophysical processes of planting, seedling, elongating, heading, harvesting of agricultural crops. So according to the period of time series of NDVI, the dynamic information of crop under cultivated land can be extracted and cropping index of arable land can be further calculated. The paper presentsu remote sensing method for extracting the cropping index and then extracted the cropping index from 4 years of VEGETATION decadal composite time series of NDVI over the period of 1999 to 2002. The validation results show a high accuracy compared to the 4 test sites ground data and other available information.

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