归一化植被指数在遗址探测中的应用

发布时间：2018-05-24 01:54

本文选题：遥感考古 + NDVI时间序列　；参考：《测绘科学》2016年03期

【摘要】：针对目前遗址探测研究多基于单时相遥感数据开展,存在偶然性,对最佳探测时间的研究较少等问题,该文以洛阳盆地为研究对象,利用多时相遥感数据,通过时间序列谐波分析算法(HANTS)重构时间序列植被指数数据集,去噪的同时对比分析出利用冬小麦长势信息进行地下遗址遥感监测的最佳时间区间。研究表明,受地下遗址的胁迫,在分蘖期,冬小麦长势明显比非遗址区的长势差,表明该时期是进行地下遗址探测的最佳时期,进而对最佳探测时期内NDVI积分,有效增强了遗址区和非遗址区之间差异,突出地下遗址的位置和轮廓信息。利用该研究成果,文章成功探测到汉魏洛阳故城以及古伊洛河异常区,与现有的考古资料相吻合。
[Abstract]:In order to solve the problem that the research on site exploration is mostly based on single phase remote sensing data, there are some problems such as contingency and less research on optimal detection time, this paper takes Luoyang Basin as the research object and uses multi-temporal remote sensing data. The time series vegetation index data set was reconstructed by time series harmonic analysis algorithm (HANTS), and the optimal time interval for remote sensing monitoring of underground sites using winter wheat growth information was compared and analyzed while denoising. The results show that, under the stress of underground site, winter wheat growth is obviously worse than that in non-site area at tillering stage, which indicates that this period is the best time for underground site detection, and then the NDVI integral is obtained during the best detection period. The difference between site and non-site areas is effectively enhanced, and the location and contour information of underground sites are highlighted. Using the research results, the paper successfully detects Luoyang Old City and the anomalous area of ancient Yiluo River in the Han and Wei dynasties, which coincides with the existing archaeological data.
【作者单位】：中国科学院遥感与数字地球研究所教育部国家文物局遥感考古联合实验室;中国科学院大学;
【基金】：十二五国家科技支撑计划项目(2013BAK08B06) 中国科学院遥感与数字地球所所长青年基金专项(Y3SG8300CX)
【分类号】：P237

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