摘要
本文以廊坊市为例,采用Landsat8的热红外传感器(Thermal Infrared Sensor,TIRS)数据结合NDVI指数提取建筑用地(construction land,CL),取得了较好的结果。首先根据NDVI获取建筑用地的大致分布范围,然后利用TIRS数据反演得到地表温度(Land surface temperature,LST),根据阈值法将地表温度二值化为建筑用地和非建筑用地,再与NDVI数据运算获得建筑用地范围。将结果与NDBI和MNDBI、ULI对比,并利用Google Earth高分辨率数据进行精度验证,发现利用landdsat8的TIRS反演的LST数据结合NDVI数据提取建筑用地,与NDBI和MNDBI、ULI相比准确度更高。
This study is based on the experiment in the local city of Langfang,good results are obtained when the Landsat8 Thermal Infrared Sensor(TIRS)data is combined with the NDVI index to extract construction land(CL).Firstly,the approximate distribution range of building land is obtained according to NDVI,then the surface temperature(LST)is obtained by using TIRS data inversion,and the surface temperature is binarized into construction land and non-construction land according to the value method,and then with NDVI.The data is calculated to obtain the scope of the building land.Compared with NDBI and MNDBI,ULI and using Google Earth high spatial resolution data for accuracy verification,it shows that the LST data of the TIRS inversion using landdsat8 combined with the NDVI data to extract the building land can achieve higher precision than NDBI,MNDBI and ULI.
作者
赵子辉
张改英
刘肖兵
Zhao Zihui;Zhang Gaiying;Liu Xiaobing(School of Remote Sensing and Information Engineering,North China Institute of Aerospace Engineering,Langfang 065000,China;Hebei Normal University,Shijiazhuang 050000,China;Beijing Tianheng Xinye Technology Development Co.LTD,Beijing 100000,China;Information Engineering University,Zhengzhou 450001,China)
出处
《北华航天工业学院学报》
CAS
2022年第6期11-13,共3页
Journal of North China Institute of Aerospace Engineering
作者简介
第一作者:赵子辉(1989-),女,硕士,讲师,河北邢台人,主要研究方向为遥感与时空数据分析。
