Coronal holes (CHs) are regions in the solar corona characterized by plasma density lower than in the surrounding quiet Sun. Therefore they appear dark in images of the solar atmosphere made, e.g., in extreme ultraviolet (EUV). Identifying CHs on solar images is difficult since CH boundaries are not sharp, but typically obscured by magnetic structures of surrounding active regions. Moreover, the areas, shapes, and intensities of CHs appear differently in different wavelengths. Coronal holes have been identified both visually by experienced observers and, more recently, by automated detection methods using different techniques. In this article, we apply a recent, robust CH identification algorithm to a new set of homogenized EUV synoptic maps based on four EUV lines measured by the Solar and Heliospheric Observatory/Extreme ultraviolet Imaging Telescope (SOHO/EIT) in 1996–2018 and the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) in 2010–2018 and create corresponding CH synoptic maps. We also use CHs of the hand-drawn McIntosh archive (McA) from 1973–2009 to extend the CH database to earlier times. We discuss the success of the four EUV lines to find CHs at high or low latitudes, and confirm that the combined EIT 195 Å/AIA 193 Å series applies best for both polar and low-latitude CH detection. While the polar CH detection suffers from the vantage-point limitation, the low-latitude CH areas extracted from this line correlate with the McA CH data very well. Using the simultaneous measurements between EIT and McA and EIT and AIA, we scale the different data series to the same level and form the longest uniform series of low-latitude CHs in 1973–2018. We find that, while the solar cycle maxima of low-latitude CHs in the descending phase of Solar Cycles 21–23 attain roughly similar values, the corresponding maximum during Solar Cycle 24 is reduced by a factor of two. This suggests that magnetic flux emergence is crucial for the formation of low-latitude CHs.

日冕孔（CHs）是日冕中的区域，其特征是等离子体密度低于周围的安静太阳。因此，它们在所形成的太阳大气图像中显得很暗，例如在极紫外（EUV）中。由于CH边界不清晰，但通常会被周围活动区域的磁性结构所遮盖，因此很难识别太阳图像上的CH。此外，CHs的面积，形状和强度在不同的波长下会有所不同。冠状孔已经由经验丰富的观察者视觉识别，并且最近通过使用不同技术的自动检测方法被识别。在本文中，我们应用了最新的，一套强大的CH识别算法，用于基于1996年至2018年太阳和太阳天文台/极端紫外线成像望远镜（SOHO / EIT）以及太阳动力学天文台/大气成像组件（SDO）测量的四条EUV线，对一组新的均质EUV天气图/ AIA），并创建相应的CH天气图。我们还使用1973-2009年手绘的McIntosh档案（McA）的CH来将CH数据库扩展到更早的时间。我们讨论了在高纬度或低纬度找到CH的4条EUV线的成功，并确认结合使用的EIT 195Å/ AIA 193Å系列适用于极地和低纬度CH检测。虽然极性CH检测受到有利点的限制，但从这条线提取的低纬度CH区域与McA CH数据非常相关。使用EIT和McA之间以及EIT和AIA之间的同时测量，我们将不同的数据序列缩放到相同的水平，并形成了1973-2018年最长的低纬度CH统一序列。我们发现，虽然在太阳周期21–23的下降阶段低纬度CHs的太阳周期最大值达到大致相似的值，但太阳周期24的相应最大值却减少了两倍。这表明，磁通的出现对于低纬度CH的形成至关重要。太阳周期24中相应的最大值减少了两倍。这表明，磁通的出现对于低纬度CH的形成至关重要。太阳周期24中相应的最大值减少了两倍。这表明，磁通的出现对于低纬度CH的形成至关重要。