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摘要： 精确提取作物种植面积一直是农业遥感关注的主要问题之一。综合运用低分辨率的时相变化特征和中分辨率的光谱特征,提出一种夏玉米识别方法。首先基于MODIS NDVI时间序列曲线,分析夏玉米在时相变化上的识别特征,构建识别模型。夏玉米纯像元利用识别模型识别,而耕地和非耕地类型的植被产生的混合像元,则基于像元分解办法获取耕地组分的NDVI时序特征,再利用识别模型判定,然后结合土地利用数据根据空间关系得到中分辨率结果;玉米与其他作物的混合像元则利用中分辨率尺度光谱差异加以区分。研究结果表明,在伊洛河流域主要农业区,识别精度达到90.33%,为作物类型识别提供了新的思路。 关键词： 作物类型识别;  时相特征;  光谱特征;  像元分解;  伊洛河流域     Abstract: Accurate extraction of crop acreage has been one of the main concerned issues of agricultural remote sensing.Timely information about crop acreage at regional and national scales is also essential for predicting crop yields,and agricultural planning.In this paper,a new crop identification method is proposed combining with medium\|resolution and low\|resolution remote sensing data.Firstly,based on the differences of NDVI time series curve for various types of vegetation,we analyze the identifying characteristics of maize on the seasonal rhythm,and build an identification model.Then,the maize pure pixels are identified according to the closeness with the standard NDVI curve of maize.For the mixed pixels from maize and other vegetation,their sub\|pixel NDVI time series are extracted based on pixel unmixing method and the sub\|pixels are identified according to the model above;further,the identification results are repositioned to the medium\|resolution scales according to the spatial relationship.The mixed pixels area from maize and other crops are identified based on spectral differences in TM remote sensing image.Finally,the identified results are integrated into the medium resolution scale.In the dominating agricultural area of the Yiluo basin,the identified results of maize show that the acreage is 132 704 hm2,and the accuracy is 90.33%.The method proposed by this paper improved the identification accuracy and provided a new perspective to solve problems for extraction of crop cultivation information.

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