中文摘要：

卫星遥感技术能够快速、准确、大面积对农作物生长进行监测,多时相遥感监测可克服单时相遥感监测的不足,利于实现对农作物生长变化的动态监测。以江苏省大丰市为研究区域,选用拔节期和抽穗期两景环境（HJ）卫星遥感影像进行不同地物光谱信息识别与种植面积提取研究。首先,在分析两景HJ星影像植被光谱信息的基础上,提取出各自影像的归一化差值植被指数（NDVI）影像,并对两景NDVI影像分别进行加运算和减运算,得到另外两景NDVI合成影像。其次,通过对提取到的四景NDVI影像光谱信息进行比较分析,最终选用植被光谱信息特征较为明显的加运算合成影像进行冬小麦种植面积提取。最后,基于影像不同地物的NDVI阈值划分,并叠加GPS样点信息校正,提取到大丰市冬小麦种植面积数据及其空间分布信息。结果显示,大丰市遥感提取冬小麦种植面积为78 712.13 hm2,精度为92.51%。在该市20个乡镇（或农场）冬小麦种植面积提取精度中,精度大于95%有9个乡镇（或农场）,精度在90%至95%之间的有7个乡镇（或农场）,仅有4个乡镇（或农场）提取精度在80%至90%之间。说明,利用不同时相遥感合成运算方法得到的合成影像,能明显增强冬小麦光谱信息与其他植被信息特征区别,有利于实现高精度提取冬小麦种植面积的目的。

英文摘要：

Satellite remote sensing technology can speedily,accurately and widely monitor the growth of crops.Multitemporal remote sensing monitoring overcomes the deficiency of single phase remote sensing monitoring and realizes the dynamic monitoring of crop growth.In this research,ground objects spectral information was analyzed and planting area was extrated with two units of HJ satellite remote sensing images at jointing and heading stages of winter wheat Dafeng city,Jiangsu province.Firstly,according to the spectral information,the normalized difference vegetation index（NDVI） was extracted in images.The NDVI images were made into plus synthesizing and subtract synthesizing operation,and the other two units of synthetic NDVI images were achieved.Secondly,by comparing and analyzing the spectral information for four units of NDVI images,the plus synthesizing image which had distinct spectral information feature of vegetation was applied for winter wheat planting area extration.Finally,based on the classification of NDVI threshold value and the superposition information of GPS samples,the data of winter wheat planting area and information of spatial distribution were extracted.The results showed that the winter wheat area extracted by the synthetic image was 78 712.13 hm2,with the accuracy up to 92.51%.Nine towns or farms out of 20 ones displayed accuracies of more than 95%,7 between 90% and 95%,only 4 between 80% and 90%.It was concluded that the NDVI images was conducive to realize high-precision extraction of winter wheat planting area by enhancing the difference between winter wheat spectral information and vegetation characteristics..