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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Estimating landscape imperviousness index from satellite imagery
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Estimating landscape imperviousness index from satellite imagery

机译：从卫星图像估计景观不渗透指数

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摘要

This letter presents a practical method for landscape imperviousness estimation through the synergistic use of Landsat Enhanced Thematic Mapper Plus (ETM+) and high-resolution imagery. A 1-m resolution color-infrared digital orthophoto was used to calibrate a stepwise multivariate statistical model for continuous landscape imperviousness estimation from medium-resolution ETM+ data. A variety of predictive variables were initially considered, but only brightness and greenness images were retained because they were account for most of the imperviousness variation measured from the calibration data. The performance of this method was assessed, both visually and statistically. Operationally, this method is promising because it does not involve any more sophisticated algorithms, such as classification tree or neural networks, but offers comparable mapping accuracy. Further improvements are also discussed.
机译：这封信提出了通过结合使用Landsat Enhanced Thematic Mapper Plus（ETM +）和高分辨率图像来进行景观防渗性评估的实用方法。使用1 m分辨率的彩色红外数字正射影像校准逐步多元统计模型，以便根据中等分辨率的ETM +数据进行连续的景观防渗估计。最初考虑了各种预测变量，但仅保留了亮度和绿色图像，因为它们是根据校准数据测得的大部分不渗透性变化的原因。从视觉和统计上评估了该方法的性能。在操作上，此方法很有希望，因为它不涉及任何更复杂的算法，例如分类树或神经网络，但可提供相当的映射精度。还讨论了进一步的改进。

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