In several regions of the world, the remoteness of potential bird hotspots and lack of trained observers have often prevented countries from effectively designing proper monitoring schemes at a national scale. For many countries, it is not known whether certain bird strongholds have been missed that should be included for more complete censuses. Such gaps at national scales, sometimes large, may be detrimental for global monitoring schemes. To address this, we used the irregular participation of Sudan to the International Waterbird Census (IWC) as a case study. We designed and tested a method based on remote‐sensing data of the country’s lowlands to detect open water bodies in order to develop predictive models of the potential distribution of waterbird abundance and diversity. To identify open water bodies and their flooding duration, we used a Modified Normalized Difference Water Index (MNDWI) derived from Landsat 8 data. Field ornithological surveys were then used as ground‐truth data to estimate the method’s accuracy. The statistical results (overall accuracy = 0.972; Kappa index = 0.93) confirmed its effectiveness. Remotely sensed water bodies and additional environmental covariates were then used to build simple habitat models of the distribution of waterbird abundance and diversity based on IWC field survey data. Of the 3119 remotely sensed clusters of open water bodies, three were predicted to host more than 10 000 waterbirds, 89 more than 1000 waterbirds and five more than 30 waterbird species. Located mainly in the southern agricultural floodplains along the main rivers, these predicted waterbird strongholds are therefore recommended for inclusion in the next IWC survey in Sudan. Our findings indicate that using remote sensing to identify open water bodies combined with simple statistical modelling is likely to be a cost‐effective solution to improve IWC sampling and to enhance both waterbird and wetland monitoring in vast under‐surveyed regions.

中文翻译：

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利用遥感改善萨赫勒地区的水鸟监测和养护：苏丹国际水鸟普查的案例研究

在世界上几个地区，潜在鸟类热点地区的偏远地区和缺乏训练有素的观察员经常使各国无法有效地在全国范围内设计适当的监测计划。对于许多国家来说，尚不清楚是否应该错过某些鸟类据点，以便进行更全面的普查。在国家范围内的这种差距有时甚至很大，这可能不利于全球监测计划。为了解决这个问题，我们以苏丹不定期参加国际水鸟普查为例进行了研究。我们设计并测试了一种基于该国低地遥感数据的方法来检测开放水域，以开发水鸟丰度和多样性的潜在分布预测模型。为了确定开放水域及其洪水持续时间，我们使用了来自Landsat 8数据的修正归一化差异水指数（MNDWI）。然后，将鸟类学调查作为实地数据来评估该方法的准确性。统计结果（总体准确度= 0.972； Kappa指数= 0.93）证实了其有效性。然后，根据IWC野外调查数据，利用遥感水体和其他环境协变量建立水鸟丰度和多样性分布的简单栖息地模型。在3119个遥感的开放水体簇中，预计有3个将容纳1万多只水鸟，有89种将有1000多只水鸟和5种有30多种水鸟。主要位于主要河流南部的农业洪泛区，因此，建议将这些预测的水鸟据点包括在下一次IWC苏丹调查中。我们的发现表明，使用遥感技术来识别开放水域并结合简单的统计模型可能是一种经济有效的解决方案，可以改善IWC采样并在调查不足的广大地区加强水鸟和湿地的监测。