A NOVEL TOOL FOR UNSUPERVISED FLOOD MAPPING USING SENTINEL-1 IMAGES

被引：0

作者：

Amitrano, D. ^{[1
]}

Di Martino, G. ^{[1
]}

Iodice, A. ^{[1
]}

Riccio, D. ^{[1
]}

Ruello, G. ^{[1
]}

机构：

[1] Univ Napoli Federico II, Dept Elect Engn & Informat Technol, Via Claudio 21, I-80125 Naples, Italy

来源：

IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年

关键词：

Synthetic aperture radar; sentinel-1; flooding; classification; fuzzy systems;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we present a novel method for mapping flooded areas exploiting Sentinel-1 ground range detected products. The work introduces two novelties. As first, the input products. In fact, as far we know, no applications using these products has been so far presented in literature. Secondly, a new unsupervised methodology, based on the usage of opportune layers combined in a fuzzy decision system, is presented. Experimental results, obtained both on the single SAR image and on a couple of acquisitions in a change detection framework showed that our method is able to outperform the most popular classification techniques in terms of standard assessment parameters.

引用

页码：4909 / 4912

页数：4

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