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遥感裸土识别制图为水土流失治理工作提供了科学依据。本文以SPOT-5影像为实验数据,提出一种以土壤指数NDSI和不透水面指数NDISI提取裸土的方法。通过热红外波段的亚像元分解技术,将同期120 m分辨率的TM 6波段细化为10 m分辨率的地表温度影像,为SPOT-5影像计算NDISI不透水面指数增加了必要的热红外波段。在此基础上,构建双重指数模型,获得10 m分辨率的裸土数据。研究表明,双重指数模型可较好地解决裸土提取中建筑用地与裸土相混淆的问题,提取裸土的总精度可达95.4%。通过比较10 m的SPOT-5和30 m的TM影像的裸土提取结果,发现影像分辨率的提升可使裸土信息提取结果更加准确、精细。因此,本文为更高分辨率裸土识别制图,提供了一种有效的方法。
Remote sensing of bare soil identification mapping provides a scientific basis for soil erosion control work. In this paper, SPOT-5 images as experimental data, a soil index NDSI and impervious surface NDISI extraction of bare soil method. Through the sub-pixel decomposition technique in the thermal infrared band, the TM 6 band with 120 m resolution in the same period is refined into a 10 m-resolution surface temperature image, and calculating the NDISI impermeable surface index for the SPOT-5 image adds the necessary thermal infrared Band. Based on this, a dual exponential model is constructed to obtain bare soil data of 10 m resolution. The research shows that the double exponential model can solve the confusion of construction land and bare soil in bare soil extraction, and the total accuracy of extracting bare soil can reach 95.4%. By comparing the bare soil extraction results of 10 m SPOT-5 and 30 m TM images, it is found that the enhancement of image resolution can make the bare soil information extraction more accurate and precise. Therefore, this paper provides an effective method for identifying mapping of higher resolution bare soil.