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水力发电学报 ›› 2021, Vol. 40 ›› Issue (2): 111-120.doi: 10.11660/slfdxb.20210211

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基于高分卫星数据多时相重建的水体信息提取

  

  • 出版日期:2021-02-25 发布日期:2021-02-25

Extraction of water body information from GF-1 satellite images using spatiotemporal reconstruction approach

  • Online:2021-02-25 Published:2021-02-25

摘要: 基于我国高分一号卫星WFV数据,利用其较高的时空分辨率特性,建立库区高分影像时间序列与水体“检测?重建?提取”的流程框架,以提高面向三峡库区的水体分布及面积变化的动态监测能力。研究结果表明:基于多特征联合的面向对象的云检测总体精度高达96.8%,且云阴影的生产者与用户精度均高于76%。多时相重建算法可以对云覆盖区域进行有效的填补,且重建后的影像可反映出完整的空间变化和差异性。从2013—2017年的水体面积提取结果可知,三峡库区水体面积并未出现明显增大或减小的趋势,多年平均水体面积为540.6 km2。研究结果为三峡库区综合治理提供了数据和技术支撑,提高了高分卫星数据在三峡库区水体面积提取中的应用价值和能力。

关键词: 三峡库区, 高分一号, 云检测, 时空重建, 水体面积变化

Abstract: To facilitate dynamic monitoring of the spatial distribution of water bodies in the Three Gorges reservoir area, we have developed a framework of water body detection, reconstruction and extraction using China’s GF-1 satellite images of high spatiotemporal resolution. Results show the method of object-oriented change detection has an overall accuracy of cloud detection up to 97%, with the producer's accuracy and user's accuracy of cloud detection both higher than 76%. Large cloud-contaminated areas can be effectively recovered using a spatiotemporal reconstruction approach, which can reflect the complete spatial variations. In addition, we find the water surface area of this reservoir, with a mean of 540.6 km2, did not significantly increase or decrease during 2013-2017. This study is useful for comprehensive, integrated management of the reservoir area, with important implications for applying GF-1 satellite images in this region.

Key words: Three Gorges Reservoir area, GF-1 satellite images, cloud detection, spatiotemporal reconstruction, variation in water surface area

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