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Enhancement of spectral quality of archival aerial photographs using satellite imagery for detection of land cover

机译:使用卫星图像提高档案空中照片的谱质量,用于检测陆地覆盖

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摘要

Archival aerial photographs are often the only reliable source of information about the area. However, these data are single-band data that do not allow unambiguous detection of particular forms of land cover. Thus, the authors of this article seek to develop a method of coloring panchromatic aerial photographs, which enable increasing the spectral information of such images. The study used data integration algorithms based on pansharpening, implemented in commonly used remote sensing programs: ERDAS, ENVI, and PCI. Aerial photos and Landsat multispectral data recorded in 1987 and 2016 were chosen. This study proposes the use of modified intensity-hue-saturation and Brovey methods. The use of these methods enabled the addition of red-green-blue (RGB) components to monochrome images, thus enhancing their interpretability and spectral quality. The limitations of the proposed method relate to the availability of RGB satellite imagery, the accuracy of mutual orientation of the aerial and the satellite data, and the imperfection of archival aerial photographs. Therefore, it should be expected that the results of coloring will not be perfect compared to the results of the fusion of recent data with a similar ground sampling resolution, but still, they will allow a more accurate and efficient classification of land cover registered on archival aerial photographs.
机译:档案空中照片往往是该地区唯一可靠的信息来源。然而,这些数据是单频带数据,不允许明确地检测特定形式的陆地覆盖。因此,本文的作者寻求开发一种着色的彩色空中照片的方法,这使得能够增加这种图像的光谱信息。该研究使用了基于泛士彭化的数据集成算法,在常用的遥感程序中实现:Erdas,Envi和PCI。选择了1987年和2016年记录的空中照片和Landsat多光谱数据。本研究提出了使用改性强度 - 色调饱和度和Brovey方法。这些方法的使用使得将红绿蓝(RGB)组分添加到单色图像中,从而提高其解释性和光谱质量。所提出的方法的局限性涉及RGB卫星图像的可用性,空中和卫星数据的相互取向的准确性,以及档案空中照片的缺陷。因此,应该预期,与近期数据的融合结果相比,着色结果与具有类似地面采样分辨率的融合结果,但仍然可以允许更准确,有效地分类档案上的陆地覆盖空中照片。

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