Lake morphometry is a driver of limnological processes, yet digitized bathymetry is lacking for most lakes. Here, we describe a method for efficiently extracting hypsography from bathymetric maps using ImageJ. To validate our method, we compared results generated from two independent users to those obtained from digital elevation models for 100 lakes. The mean absolute difference between hypsographic curves extracted using ImageJ vs. digital elevation models (DEMs) was 0.049 (95% CI 0.041–0.056) proportion of lake area, suggesting that ImageJ provides accurate hypsography. We calculated the mean absolute difference between the two users (0.016; 95% CI: 0.011–0.021), which suggests high interobserver reliability. Finally, we compared DEMs to an interpolated hypsography using only the maximum lake depth and found large differences. We apply this method to extract data for 1012 lakes. Our data and approach will be useful where bathymetric maps exist but are not digitized.

中文翻译：

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使用 ImageJ 对湖泊测深数据进行数字化

湖泊形态测量是湖泊学过程的驱动因素，但大多数湖泊缺乏数字化测深。在这里，我们描述了一种使用 ImageJ 从测深图中有效提取地形的方法。为了验证我们的方法，我们将两个独立用户生成的结果与从 100 个湖泊的数字高程模型获得的结果进行了比较。使用 ImageJ 与数字高程模型 (DEM) 提取的地形曲线之间的平均绝对差异为 0.049 (95% CI 0.041–0.056) 湖泊面积比例，表明 ImageJ 提供了准确的地形测量。我们计算了两个用户之间的平均绝对差异（0.016；95% CI：0.011-0.021），这表明观察者间的可靠性很高。最后，我们将 DEM 与仅使用最大湖泊深度的插值地形图进行比较，发现了很大的差异。我们应用该方法提取了 1012 个湖泊的数据。我们的数据和方法在存在测深地图但未数字化的情况下将很有用。