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Integrating satellite imagery and geostatistics of point samples for monitoring spatio-temporal changes of total suspended solids in bay waters: application to Tien Yen Bay (Northern Vietnam)

机译:集成卫星图像和点样本的地统计信息,以监测海湾水域中总悬浮固体的时空变化:在天仁湾(越南北部)的应用

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摘要

High concentrations of total suspended solids (TSS) in coastal and bay areas strongly affect water quality and aquatic ecosystems. Frequent monitoring of spatiotemporal changes of TSS distribution in such areas is indispensable for understanding sediment fluxes and water cycles, and to preserve ecosystem health. This study aimed to identify appropriate and sufficient tools for assessing changes in TSS distribution in Tien Yen Bay in Northern Vietnam, a typical closed bay, which was selected as the study area because of its rich biodiversity. Initially, a physical based model using the reflectance at the sea surface was developed for estimating TSS concentrations from satellite image data, and a model with an exponential function was identified as suitable for the estimation. This model was fitted appropriately to provide a relationship between reflectance from the MODIS/Terra band 1 (visible red) after the atmospheric correction and the in situ TSS concentrations at 40 points. Ordinary kriging was then shown to be effective in improving the spatial resolution of the MODIS/Terra image-based estimation of the TSS concentration at a 250 m interval, because it could detect TSS variation in detail, in particular in the local estuaries. TSS distributions derived from 12 MODIS/Terra images from November 2009 to October 2010 clarified seasonal changes in TSS during one year. TSS concentrations were high during summer and lower during fall and winter. Such trends were conformable with the hydrodynamics in Tien Yen Bay. Consequently, the proposed method was more effective for TSS estimation than traditional methods using satellite image data only.
机译:沿海和海湾地区高浓度的总悬浮固体(TSS)强烈影响水质和水生生态系统。为了了解沉积物通量和水循环并维护生态系统健康,必须经常监测此类地区TSS分布的时空变化。这项研究旨在确定适当和足够的工具,以评估越南北部天安湾(一个典型的封闭海湾)的TSS分布变化,该地区由于其丰富的生物多样性而被选为研究区域。最初,开发了一种基于海面反射率的基于物理的模型,用于从卫星图像数据中估算TSS浓度,并确定具有指数函数的模型适合进行估算。对该模型进行了适当的拟合,以提供大气校正后来自MODIS / Terra波段1(可见红色)的反射率与40点处的原位TSS浓度之间的关系。然后证明了普通克里金法在提高基于MODIS / Terra图像的250 m间隔内TSS浓度估算的空间分辨率方面是有效的,因为它可以详细检测TSS变化,尤其是在本地河口。从2009年11月至2010年10月的12张MODIS / Terra图像中得出的TSS分布阐明了一年中TSS的季节性变化。 TSS的浓度在夏季高,而在秋季和冬季则低。这种趋势与天安湾的水动力相吻合。因此,与仅使用卫星图像数据的传统方法相比,该方法对于TSS估计更为有效。

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