Rapid response flood assessment using minimum noise fraction and composed spline interpolation
Rapid response flood assessment using minimum noise fraction and composed spline interpolation
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DOI：
10.1109/tgrs.2007.895414
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发表时间：
2007-10-01
影响因子：
8.2
通讯作者：
Villa, Paolo
中科院分区：
文献类型：
--
作者：
Gianinetto, Marco;Villa, Paolo
每年，洪水在世界各地造成巨大的破坏和生命损失。就欧盟而言，极端洪水是最常见的自然灾害类型（在过去十年中占总数的44%），并且在未来，哈希洪水的数量预计会增加。作者最近的工作集中在开发一种简单有效的处理算法，用于利用光学遥感卫星数据和数字地形模型分析和绘制洪水损害图。本文从洪水制图和水深估算两方面介绍了处理技术的改进。针对第一个问题，引入了一种新的数据变换方法，用谱时最小噪声分数（STMNF）变换代替谱时主成分分析（STPCA），并通过更复杂的插值方法获得峰值水深。基于stmnf的技术被应用于1994年袭击意大利皮埃蒙特地区的20世纪最严重的洪水收集的数据。在洪水制图方面，STMNF方法总体精度为97.09%，kappa系数为0.889，用户精度为85.76%，生产者精度为95.96%，与之前的STPCA方法相比，委托误差更低。在水深计算方面，采用二阶组合样条插值法得到了最好的结果，与地面参考数据的总体一致性约为83%。
Every year, floods cause enormous damage and loss of human life all over the world. Regarding the European Union, extreme floods are the most common types of natural disasters (44% of the total in the last decade), and in the future, the number of Hash floods is expected to rise. Recent works of the authors have focused on the development of a straightforward and efficient processing algorithm for analyzing and mapping flood damages using optical remotely sensed satellite data and digital terrain models. In this paper, some improvements of the processing technique, both regarding the flood mapping and the water depth estimation, are presented. With respect to the first issue, a new data transformation is introduced, replacing the spectral-temporal principal component analysis (STPCA) with the spectral-temporal minimum noise fraction (STMNF) transformation, while the peak water depth is obtained through more sophisticated interpolation methods. The STMNF-based technique was applied to the data collected for the worst flood of the 20th Century that struck Piemonte Region, Italy, in 1994. Regarding the flood mapping, the STMNF method allowed an overall accuracy of 97.09% with a kappa coefficient of 0.889 to be established, obtaining a user accuracy of 85.76%, and a producer accuracy of 95.96%, with a lower commission error if compared to the previous STPCA method. Regarding the water depth computation, the best results were obtained using the second-order composed splines interpolator, obtaining an overall agreement with ground reference data of about 83%.