[1]陈诚,谢映,陈燕丽,等.基于Sentinel-1A的青狮潭水库水体面积监测[J].气象研究与应用,2022,43(04):26-31.[doi:10.19849/j.cnki.CN45-1356/P.2022.4.05]
　Chen Cheng,Xie Ying,Chen Yanli,et al.Water area monitoring of Qingshitan Reservoir based on Sentinel-1A[J].Journal of Meteorological Research and Application,2022,43(04):26-31.[doi:10.19849/j.cnki.CN45-1356/P.2022.4.05]
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基于Sentinel-1A的青狮潭水库水体面积监测()
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气象研究与应用[ISSN:1673-8411/CN:45-1356/P]

卷:
第43卷
期数:
2022年04期
页码:
26-31
栏目:
生态气象
出版日期:
2022-12-15

文章信息/Info

Title:
Water area monitoring of Qingshitan Reservoir based on Sentinel-1A
作者:
陈诚1;  谢映1;  陈燕丽1;  莫建飞1;  李明志2
1. 广西壮族自治区气象科学研究所, 南宁 530022;
2. 百色市气象局, 广西 百色 533000
Author(s):
Chen Cheng1;  Xie Ying1;  Chen Yanli1;  Mo Jianfei1;  Li Mingzhi2
1. Guangxi Institute of Meteorological Sciences, Nanning 530022, China;
2. Baise Meteorological Bureau, Guangxi Baise 533000, China
关键词:
合成孔径雷达(SAR); 水体识别; 水库监测; 时间序列分析; Sentinel-1A卫星
Keywords:
Synthetic Aperture Radar(SAR); water identification; reservoir monitoring; time series analysis; Sentinel-1A satellite
分类号:
P237
DOI:
10.19849/j.cnki.CN45-1356/P.2022.4.05
摘要:
青狮潭水库是广西北部第一大水库,水体变化对桂林市的漓江黄金水道调控有着重要影响。基于Sentinel-1A遥感数据,利用结合地形数据的阈值法对青狮潭水库进行水体面积监测。结果表明,2019年3-12月期间,水库水体面积为0.16~0.25hm2,水库面积空间变化主要集中在库区的西南侧和北侧;经与光学遥感监测定性对比,SAR影像提取水体准确,与目视解译的水体进行定量分析表明水体提取精度为93.58%,Kappa系数0.945,可满足水文监测需求。连续的监测结果可以为库区及其下游的生态管理、防汛抗旱工作提供参考。
Abstract:
Qingshitan Reservoir is the largest reservoir in northern Guangxi, and the change of water in Qingshitan Reservoir has an important influence on the Waterway regulation of the Lijiang River in Guilin. Based on Sentinel-1A remote sensing data and topographic data, this study used the threshold method to extract the water surface area of Qingshitan Reservoir. The results showed that the water surface area of Qingshitan Reservoir was 0.16~0.25hm2 from March to December 2019, and the spatial variation of the reservoir area was mainly concentrated in the southwest and north sides of the reservoir area; After qualitative comparison with optical remote sensing monitoring, Synthetic Aperture Radar(SAR) images extracted water bodies accurately, and quantitative analysis with visually interpreted water bodies showed that the water extraction accuracy is 93.58%, and the Kappa coefficient was 0.945, which can meet the hydrological monitoring needs. The continuous monitoring results can provide a reference for ecological management, flood control, and drought relief in the reservoir area and its downstream.

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备注/Memo

备注/Memo:
收稿日期:2022-04-20。
基金项目:广西气象科研计划项目(桂气科2022QN13、桂气科2021ZL04)
作者简介:陈诚(1994-),男,工程师,研究方向为遥感数字图像处理。E-mail:ccf185@163.com
通讯作者:陈燕丽(1982-),女,正研级高级工程师,研究方向为生态遥感技术应用。E-mail:cyl0505@sina.com
更新日期/Last Update: 1900-01-01