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Luminance measurements for light pollution assessment

机译:用于光污染评估的亮度测量

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Light pollution is a phenomenon that needs to be closely monitored. There are currently many SQMs (Sky Quality Meters) that monitor the visibility of stars, but the method has the disadvantage that it does not eliminate the effect of humidity, clouds or aerosols. Another global assessment method uses ISS images that provide detailed information but cannot identify and locate the pollution sources. There is a need for a method accessible to the general public, which can measures the sources of light pollution. Using DSLR to measure luminance is a solution. There is information in the literature about the calibration of these devices to measure luminance, but the method nevertheless did not get wide spread. An identified problem is the photo camera's constant, which is shown to be, in fact, a conversion function. To overcome this limitation, the author presents the practical details that allow the rapid calibration of the DSLR using a single luminance standard for the entire measurement range. For practical measurements, it is indicated how the exposure latitude should be interpreted for extreme values of luminance. For the interpretation of the results, one uses general software environments, like MATLAB. The quantitative interpretation of the luminous field is thus a powerful and useful tool, far superior to the qualitative assessment currently possible. This is a change in strategy, from measuring the effect to measuring the sources of light pollution.
机译:光污染是需要密切监控的现象。当前有许多SQM(天空质量计)用于监视恒星的能见度,但是该方法的缺点是无法消除湿度,云或气溶胶的影响。另一种全球评估方法是使用ISS图像,该图像可提供详细信息,但无法识别和定位污染源。需要一种公众可以使用的方法,该方法可以测量光污染源。使用DSLR测量亮度是一种解决方案。在文献中有关于这些设备的校准信息以测量亮度,但是该方法并未得到广泛推广。识别出的问题是相机的常数,事实证明它是转换函数。为了克服这个限制,作者提出了一些实用的细节,这些细节允许在整个测量范围内使用单一亮度标准对DSLR进行快速校准。对于实际测量,它指示应如何解释亮度的极值的曝光范围。为了解释结果,人们使用了通用软件环境,例如MATLAB。因此,对光场的定量解释是一种强大而有用的工具,远远优于目前可能进行的定性评估。从测量效果到测量光污染源,这都是策略上的变化。

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