Up-to-date information regarding impervious surface is valuable for urban planning and management. The objective of this study is to develop neural computing models used for automatic impervious surface area detection at a regional scale. To achieve this task, advanced optimizers of adaptive moment estimation (Adam), a variation of Adam called Adamax, Nesterov-accelerated adaptive moment estimation (Nadam), Adam with decoupled weight decay (AdamW), and a new exponential moving average variant (AMSGrad) are used to train the artificial neural network models employed for impervious surface detection. These advanced optimizers are benchmarked with the conventional gradient descent with momentum (GDM). Remotely sensed images collected from Sentinel-2 satellite for the study area of Da Nang city (Vietnam) are used to construct and verify the proposed approach. Moreover, texture descriptors including statistical measurements of color channels and binary gradient contour are employed to extract useful features for the neural computing model-based pattern recognition. Experimental result supported by statistical test points out that the Nadam optimizer-based neural computing model has achieved the most desired predictive accuracy for the data collected in the studied region with classification accuracy rate of 97.331%, precision = 0.961, recall = 0.984, negative predictive value = 0.985, and F1 score = 0.972. Therefore, the model developed in this study can be a helpful tool for decision-makers in the task of urban land-use planning and management.

中文翻译：

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使用图像纹理分析和具有高级优化器的神经计算模型自动进行不透水表面积检测

有关不透水表面的最新信息对于城市规划和管理很有价值。这项研究的目的是开发用于区域范围自动不渗透表面积检测的神经计算模型。为了完成此任务，需要使用先进的自适应矩估计器（Adam）优化器，称为Adamax的Adam变体，Nesterov加速的自适应矩估计（Nadam），具有解耦权重衰减的Adam（AdamW）以及新的指数移动平均变量（AMSGrad ）用于训练用于不透水表面检测的人工神经网络模型。这些先进的优化器以常规的动量梯度下降（GDM）为基准。从Sentinel-2卫星收集的岘港市（越南）研究区域的遥感图像用于构造和验证所提出的方法。此外，包括颜色通道和二进制梯度轮廓的统计测量在内的纹理描述符用于提取基于神经计算模型的模式识别的有用特征。统计测试支持的实验结果指出，基于Nadam优化器的神经计算模型已对研究区域中收集的数据实现了最理想的预测精度，分类精度率为97.331％，精度= 0.961，召回率= 0.984，负预测值= 0.985，F1得分= 0.972。因此，本研究开发的模型可以为决策者在城市土地利用规划和管理任务中提供有用的工具。