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A New Water Index for Surface Water Extraction Using OHS Hyperspectral Imagery

机译：使用OHS Hyperspectral图像的地表水提取新的水指数

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Surface water, a vital earth resource, has an essential influence on ecological environment, society, economy, human health and many other aspects, therefore it is significant to extract and monitor water bodies. Due to characteristics of the large-scale instantaneous observation and revisiting, remote sensing data play an important role in exploring the earth natural resources. The strategy of using water indices, which is simple, easy to use and less time-consuming, is one of the mainstream methods of water body extraction based on remote sensing data. Most traditional water indices, for example. Modified Normalized Difference Water Index (MNDWI) and Automated Water Extraction Index (AWEI), are devised for Landsat such medium spatial resolution imagery and have to use short-wave infrared. As the only commercial hyperspectral satellite with satellite constellation in China, the OHS hyperspectral satellite, launched in 2018, has 32 spectral bands with a spatial resolution of 10m. In spite of the high spectral resolution, the upper limit of its band is only to the near infrared band (1000nm), so the existing water indices basically cannot be applied to this data. To solve this plight, we focus on the characteristics of OHS hyperspectral data, analyze the spectral differences between water bodies and other land cover types and propose a new water index (namely, OHS-WI). A set of pure pixels, consisting of typical water and nonwater (e.g. soil, vegetation and shadow), are selected. By analyzing the spectral patterns, we devised an index (OHS-WI) to discriminate water from other land cover types. By selecting Beijing, Guangzhou and Shenzhen such cities as test sites, we compared the proposed OHS-WI with the traditional Normalized Difference Water Index (NDWI) under two threshold selection strategies, i.e., OTSU (Maximum between-class variance) and optimum (Manually selected). We applied the proposed OHS-WI to generate water extraction results in a series of test sites, which reached a better accuracy than the NDWI method for both threshold selection strategies. The results using optimal threshold achieved high accuracy than that using OTSU threshold in three test sites, with the Kappa coefficient of 0.80, 0.73 and 0.86 (OHS-WI) and 0.67, 0.62 and 0.71 (NDWI). According to the quantitative evaluation metrics, the omission error is lower when using the OTSU threshold while the optimal threshold balances the commission and omission of the extraction results. It is worth noting that the results obtained by OHS-WI under the OTSU threshold are still better than the NDWI extraction results when the optimal threshold is used. The proposed OHS-WI outperformed the NDWI in all the study areas, which can be proved by the metrics of producer's accuracy, user's accuracy and Kappa coefficient. The extracted water maps show that the proposed method not only accurately extracts large water bodies, but also effectively retains small water bodies, which reduces the omission error of extraction results. A series of experimental results show that the OHS-WI water extraction method is full of potential for automatically extracting and monitoring water resources using hyperspectral remote sensing data.
机译：地表水，一个重要的地球资源，对生态环境，社会，经济，人类健康等方面具有重要影响，因此提取和监测水体很重要。由于大规模瞬时观察和重新探测的特征，遥感数据在探索地球自然资源方面发挥着重要作用。使用水指数的策略，简单，易于使用，耗时较少，是基于遥感数据的水体提取的主流方法之一。例如，最传统的水指数。改进的归一化差异水指数（MNDWI）和自动化水提取指数（AWEI），为LANDSAT这样的中等空间分辨率图像设计，并且必须使用短波红外线。作为中国唯一具有卫星星座的商业高光谱卫星，2018年推出的OHS高光谱卫星具有32个光谱带，空间分辨率为10米。尽管有高光谱分辨率，其频段的上限仅在近红外频带（1000nm）上，因此现有的水指数基本上不能应用于该数据。为了解决这个困境，我们专注于OHS高光谱数据的特点，分析水体和其他陆地覆盖类型之间的光谱差异，并提出了一种新的水指数（即，OHS-Wi）。选择了一系列纯片像素，由典型的水和非水（例如土壤，植被和阴影）组成。通过分析光谱图案，我们设计了一种指数（OHS-WI）来区分来自其他土地覆盖类型的水。通过选择北京，广州和深圳这样的城市作为测试网站，我们将建议的OHS-WI与传统的归一化差异水指数（NDWI）进行了比较了两个阈值选择策略，即OTSU（阶级之间的最大方差）和最佳（手动选择）。我们应用了所提出的OHS-Wi以产生水提取结果，这是一系列测试站点，这达到了比阈值选择策略的NDWI方法更好的准确性。使用最佳阈值的结果达到了比三个试验位点中的OTSU阈值高的精度高，Kappa系数为0.80,0.73和0.86（OHS-Wi）和0.67,0.62和0.71（NDWI）。根据定量评估指标，当使用OTSU阈值时，省略误差较低，而最佳阈值余额余额，并省略提取结果。值得注意的是，当使用最佳阈值时，在OTSU阈值下通过OHS-Wi获得的结果仍然优于NDWI提取结果。拟议的OHS-WI在所有研究领域中表现出NDWI，这可以通过生产者准确性，用户的准确性和Kappa系数的指标来证明。提取的水图表明，该方法不仅准确地提取大型水体，而且还有效地保留了小水体，这减少了提取结果的省略误差。一系列实验结果表明，OHS-WI水提取方法充满了使用超光谱遥感数据自动提取和监测水资源的潜力。

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