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Orthogonal Equations of Multi-Spectral Satellite Imagery for the Identification of Un-Excavated Archaeological Sites

机译:用于识别未发掘考古遗址的多光谱卫星影像的正交方程

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This paper aims to introduce new linear orthogonal equations for different satellite data derived from QuickBird; IKONOS; WorldView-2; GeoEye-1, ASTER; Landsat 4 TM and Landsat 7 ETM+ sensors, in order to enhance the exposure of crop marks. The latest are of significant value for the detection of buried archaeological features using remote sensing techniques. The proposed transformations, re-projects the initial VNIR bands of the satellite image, into a new 3D coordinate system where the first component is the so called “crop mark”, the second component “vegetation” and the third component “soil”. For the purpose of this study, a large ground spectral signature database has been explored and analyzed separately for each different satellite image. The narrow band reflectance has been re-calculated using the Relative Spectral Response filters of each sensor, and then a PCA analysis was carried out. Subsequently, the first three PCA components were rotated in order to enhance the detection of crop marks. Finally, all proposed transformations have been successfully evaluated in different existing archaeological sites and some interesting crop marks have been exposed.
机译:本文旨在针对QuickBird衍生的不同卫星数据引入新的线性正交方程。 IKONOS; WorldView-2; GeoEye-1,ASTER; Landsat 4 TM和Landsat 7 ETM +传感器,以增强对农作物痕迹的曝光。最新的数据对于使用遥感技术检测埋藏的考古特征具有重要价值。提出的转换将卫星图像的初始VNIR波段重新投影到新的3D坐标系中,其中第一个分量是所谓的“作物标记”,第二个分量是“植被”,第三个分量是“土壤”。出于本研究的目的,已经针对每个不同的卫星图像分别探索和分析了大型地面光谱特征数据库。使用每个传感器的相对光谱响应滤镜重新计算了窄带反射率,然后进行了PCA分析。随后,旋转前三个PCA组件以增强对农作物痕迹的检测。最后,所有拟议的转化已在不同的现有考古现场得到成功评估,并且暴露了一些有趣的作物标记。

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