A new approach to improve precipitable water vapour estimations of Sentinel-3A satellite data using LST, elevation and NDVI over Iran

IF 2.8 3区环境科学与生态学 Q2 WATER RESOURCES

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-23 DOI:10.1080/02626667.2023.2251468

H. Dadashi, M. Rahimzadegan

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引用次数: 0

Abstract

ABSTRACT The total precipitable water vapour (TPW) extraction algorithm using the Sentinel-3A Ocean and Land Colour Instrument (OLCI) has the potential to be improved on a regional scale. The aim of this study was to improve the TPW extraction algorithm of OLCI for the first time using environmental variables, including the Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), and elevation from mean sea level, on a regional scale over Iran. A previously developed TPW recovery algorithm was applied to the OLCI data during cloud-free days throughout a one-year period (1 January–29 December 2020). The artificial neural network (ANN) methodology was utilized in eight models. The evaluation results revealed the effectiveness of the models varied based on the topography and climate of each station. The assessment findings demonstrated that model 2, which integrated LST, elevation, and NDVI data in the ANN framework, outperformed other models across the study area.

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利用LST、高程和NDVI改进伊朗上空Sentinel-3A卫星数据可降水水汽估计的新方法

摘要：使用Sentinel-3A海洋和陆地颜色仪器（OLCI）的总可降水量（TPW）提取算法具有在区域范围内改进的潜力。本研究的目的是首次使用环境变量改进OLCI的TPW提取算法，包括伊朗地区尺度上的归一化差异植被指数（NDVI）、地表温度（LST）和平均海平面高程。之前开发的TPW恢复算法在一年期间（2020年1月1日至12月29日）的无云日期间应用于OLCI数据。在八个模型中使用了人工神经网络（ANN）方法。评估结果显示，模型的有效性因每个站点的地形和气候而异。评估结果表明，将LST、高程和NDVI数据集成在ANN框架中的模型2在整个研究区域的表现优于其他模型。

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来源期刊

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques 环境科学-水资源

CiteScore

6.60

自引率

11.40%

发文量

144

审稿时长

9.8 months

期刊介绍： Hydrological Sciences Journal is an international journal focused on hydrology and the relationship of water to atmospheric processes and climate. Hydrological Sciences Journal is the official journal of the International Association of Hydrological Sciences (IAHS). Hydrological Sciences Journal aims to provide a forum for original papers and for the exchange of information and views on significant developments in hydrology worldwide on subjects including: Hydrological cycle and processes Surface water Groundwater Water resource systems and management Geographical factors Earth and atmospheric processes Hydrological extremes and their impact Hydrological Sciences Journal offers a variety of formats for paper submission, including original articles, scientific notes, discussions, and rapid communications.