Advantages and potentials of SuperDove imagery for fine monitoring of suspended particulate matter in estuaries and tidal channels

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-03-01 Epub Date: 2025-02-20 DOI:10.1016/j.ecolind.2025.113258
Peng Li , Shenliang Chen , Congliang Xu , Wenjuan Wu , Jiarui Qi , Yinghai Ke , Hongyu Ji , Shihua Li , Xiaojing Zhong
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Abstract

Suspended particulate matter (SPM) concentration is an essential biogeochemical parameter for water quality evaluation and morphodynamic researches. As the newest satellite in Planet family, SuperDove (SD) with eight spectral bands achieves observation to Earth with unprecedented temporal and spatial resolution. In this study, we developed a SPM retrieval model for SD using in-situ datasets in Yellow River Estuary, and compared the spectral and SPM products of SD with Sentinel-2 MSI and Landsat-8 OLI, and finally investigated SPM variations within typical tidal channels in recent years using multiple SD images. The results revealed that SPM concentrations derived from SD achieved high accuracy (R2 = 0.95, Relative Percentage Difference = 30.69 %) based on our algorithm. While SD, MSI and OLI agreed well in terms of top-of-atmosphere reflectance, remote sensing reflectance and retrieved SPM concentrations, SD was able to effectively monitor SPM dynamics in tidal channels due to its higher spatial resolution. Several human-derived floods in recent years caused damage to the south embankment of Yellow River, resulting in lateral transport of high-SPM river water, which dramatically increased SPM concentration in the tidal channels and influenced the neighboring tidal channel networks through the newly developed fine trenches. Moreover, for commonly used satellite data, the spatial resolution of 3–30 m is required to characterize the details of SPM distribution, and the observation frequency of at least 1/1d is necessary to capture monthly change pattern of SPM, which demonstrated that SD imagery has great potential for monitoring SPM or other parameters in high-turbidity, strong-dynamic and small-scale waters.
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超级鸽子图像在河口和潮汐通道悬浮颗粒物精细监测中的优势和潜力
悬浮颗粒物(SPM)浓度是水质评价和形态动力学研究的重要生物地球化学参数。作为Planet家族最新的卫星,SuperDove (SD)拥有8个光谱波段,以前所未有的时间和空间分辨率对地观测。本研究基于黄河口原位数据建立了SPM反演模型,并与Sentinel-2 MSI和Landsat-8 OLI进行了光谱和SPM反演结果的比较,最后利用多幅SD图像研究了近年来黄河口典型潮汐通道SPM的变化。结果表明,基于该算法,SD提取的SPM浓度具有较高的准确度(R2 = 0.95,相对百分比差= 30.69%)。虽然SD、MSI和OLI在大气顶反射率、遥感反射率和反演的SPM浓度方面一致,但SD由于具有更高的空间分辨率,能够有效监测潮汐通道中的SPM动态。近年来几次人为洪水对黄河南岸造成破坏,导致高SPM河水侧向运移,使潮道内SPM浓度急剧增加,并通过新形成的细沟影响邻近潮道网。此外,对于常用的卫星数据,需要3-30 m的空间分辨率来表征SPM分布的细节,并且需要至少1/1d的观测频率来捕获SPM的月变化模式,这表明SD图像在高浊度,强动力和小尺度水域的SPM或其他参数监测方面具有很大的潜力。
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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