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作者	单位
石涛，张丽，杨元建	（1. 安徽省芜湖市气象局，安徽芜湖241000；2.安徽省气象科学研究所农业气象灾害评估及风险转移实验室，安徽合肥 230031）

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中文摘要:

美国国家航空航天局（NASA）成功发射了最新系列的陆地卫星（Landsat-8），搭载的陆地成像仪（OLI）对波段进行了重新调整，从而避免了大气吸收干扰，能够更好地区分植被和无植被特征，为农业遥感提供了全新的高质量数据。本文选取皖北（阜阳、蚌埠、宿州）为研究区域，以Landsat-8遥感影像为研究数据，经缨帽变换得到遥感影像的主成分信息，并用其分量甄选出不同地物的端元，最后建立线性混合像元模型（LSMM），并对皖北地区冬小麦进行提取。与历史统计数据对比，冬小麦种植面积的提取精度达到了90%以上,说明利用Landsat-8和LSMM开展大尺度范围的小麦种植面积提取具有明显的优势。

英文摘要:

National Aeronautics and Space Administration (NASA) successfully launched the latest land satellite (Landsat-8). The band of operational land imager(OLI) was adjusted to avoid atmospheric absorption interference and can distinguish vegetation from no vegetation features better,thereby it provided a new high-quality data for agricultural remote sensing. This study selected the northern Anhui (Fuyang,Bengbu,Suzhou) as the study area and took Landsat-8 remote sensing image as the research data,and principal component information was used to extract pure/mixed pixel of winter wheat though tasseled cap transformation in order to select the end-member of different objects. Finally,the winter wheat planting area of northern Anhui was calculated by establishing linear spectral mixture model(LSMM),and the accuracy exceed 90% after verification. In summary,the extraction of winter wheat area based on Landsat-8 and LSMM in large scale range had obvious advantages.

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