通过卫星影像利用水稻不同物候期的特征对其进行识别是目前在水稻信息提取方面比较有效的方式。 首先根据水稻区别于其他植被的显著特征, 即水稻生长前期稻田的下垫面含有大量水的特性, 将用于提取水域信息的归一化水体指数(normalized difference water index, NDWI)合理地应用在水稻前期的信息提取中, 并且利用两个物候期的NDWI做比值, 扩大了水稻与其他地物之间的差异。 再借助归一化植被指数(normalized differential vegetation index, NDVI）在不同物候期的增长变化特征可以进一步提高水稻信息提取的精度。 研究发现充分利用水稻在不同物候期的特殊性, 并结合与水稻特性相关的指数, 将NDWI和NDVI两种指数同时用于水稻提取, 确定合理、 准确、 有效的提取方法是提高水稻提取精度的主要途径。 本文以安徽省来安县的水稻为研究对象, 基于2013年7月12日和8月30日获取的两幅高分一号卫星WFV影像数据, 利用水稻分蘖期和抽穗期的NDVI和NDWI构建了水稻信息提取模式, 有效地提取出了来安县的水稻信息分布并进行制图, 最后结合在研究区野外实地考察的信息数据对提取结果进行验证和评价。 研究结果表明利用该模式能够快速、 准确地从遥感影像上获取水稻分布信息, 具有很好的普适性。

In the present, using the characteristics of paddy rice at different phenophase to identify it by remote sensing images is an efficient way in the information extraction. According to the remarkably properties of paddy rice different from other vegetation, which the surface of paddy fields is with a large number of water in the early stage, NDWI (normalized difference water index) which is used to extract water information can reasonably be applied in the extraction of paddy rice at the early stage of the growth. And using NDWI ratio of two phenophase can expand the difference between paddy rice and other surface features, which is an important part for the extraction of paddy rice with high accuracy. Then using the variation of NDVI (normalized differential vegetation index) in different phenophase can further enhance accuracy of paddy rice information extraction. This study finds that making full advantage of the particularity of paddy rice in different phenophase and combining two indices (NDWI and NDVI) associated with paddy rice can establish a reasonable, accurate and effective extraction model of paddy rice. This is also the main way to improve the accuracy of paddy rice extraction.The present paper takes Lai’an in Anhui Province as the research area, and rice as the research object. It constructs the extraction model of paddy rice information using NDVI and NDWI between tillering stage and heading stage. Then the model was applied to GF1-WFV remote sensing image on July 12, 2013 and August 30, 2013.And it effectively extracted out of paddy rice distribution in Lai’an and carried on the mapping. At last, the result of extraction was verified and evaluated combined with field investigation data in the study area. The result shows that using the extraction model can quickly and accurately obtain the distribution of rice information, and it has the very good universality.