摘要
在水华遥感监测领域,水华面积是评估水体水华严重程度的重要指标,也是有关部门采取防治措施和确定应急响应等级的关键信息。针对中低分辨率影像采用传统方法估算水华面积精度较差的问题,以太湖为研究区,对比Sentinel-2、Sentinel-3数据提取水华面积的差异性,分析了Sentinel-3影像NDVI与混合像元中水华面积占比的关系,构建了基于NDVI密度分割法的蓝藻水华面积校正模型,对Sentinel-3提取的水华面积进行了校正;并对比分析了利用该模型与像元累加法、藻华像元生长算法进行水华面积统计与高分辨率Sentinel-2影像统计结果的一致性。研究结果表明:构建的校正模型在Sentinel-3影像水华面积估算中准确度和可靠性优于传统方法,能够有效提升该影像在水华监测领域的应用价值。
In the remote sensing monitoring for cyanobacteria blooms,the bloom area is a critical indicator for assessing the severity of the bloom and is crucial for relevant authorities in selecting preventive measures and determining emergency response levels.Traditional methods using medium-to-low-resolution imagery has limited precision in estimating bloom area.To address this issue,the cyanobacteria bloom areas of Taihu Lake as the study area extracted from Sentinel-2 and Sentinel-3 data were compared.Furthermore,the relationship between the NDVI from Sentinel-3 imagery and the cyanobacteria bloom area proportion within mixed pixels were analyzed.Based on these analyses,a corrected model for estimating bloom area was established using the NDVI density segmentation method to refine the bloom area extracted from Sentinel-3 images.The statistical results of bloom areas derived from Sentinel-3 with correction,Sentinel-3 without correction,and Sentinel-2 were compared and analyzed.The findings demonstrate that the corrected model significantly improves the accuracy and reliability of bloom area estimation using Sentinel-3 imagery compared to traditional methods,thereby enhancing its practical application value in cyanobacteria bloom monitoring.
作者
王雅萍
徐喜飞
李家国
何湜
WANG Ya-ping;XU Xi-fei;LI Jia-guo;HE Shi(School of Surveying and Land Information Engineering,Henan Polytechnic University,Jiaozuo 454003,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China)
出处
《长江科学院院报》
北大核心
2025年第2期165-171,共7页
Journal of Changjiang River Scientific Research Institute
基金
河南省科技攻关项目(232102210043)
河南理工大学青年骨干教师资助计划项目(2023XQG-12)。
