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Accueil du site → Master → Chine → 2021 → Retrieval of Surface Soil Moisture in Arid Area Based on Sentinel Data and Neural Network ——A Case Study of Vegetation Covered Area around Golmud City

Qinghai Institute of Saltlakes Chinese Academy of Sciences (2021)

Retrieval of Surface Soil Moisture in Arid Area Based on Sentinel Data and Neural Network ——A Case Study of Vegetation Covered Area around Golmud City

王二龙

Titre : Retrieval of Surface Soil Moisture in Arid Area Based on Sentinel Data and Neural Network ——A Case Study of Vegetation Covered Area around Golmud City

Auteur : 王二龙

Grade : Master 2021

Université : Qinghai Institute of Saltlakes Chinese Academy of Sciences

Résumé partiel
Soil moisture is an important component of the global water cycle.It is of great significance to study the spatial distribution of soil moisture,crop growth and yield,climate change,and spatial and temporal distribution of water resources.Water resources are scarce in the Qaidam Basin,in recent years in Golmud city surrounding,which is mainly composed of Chinese wolfberry and other economic crops developed several farms.Inversion of soil moisture has important scientific and technological support for agricultural production layout,ecological Environment protection and economic development strategy in this region.Large-scale monitoring has been a challenge because of the area’s size and sparsely populated population.In this study,the vegetation covered ground around Golmud City was taken as the research area,and the data of Sentinel-1 radar and Sentinel-2 optical data in the same period combined with the Water Cloud Model and BP and RBF neural network model were used to verify the results of measured soil moisture,and the inversion study of soil moisture around Golmud City was carried out.The main conclusions of this paper are as follows :(1)In the vegetation covered area,We need to consider the influence of vegetation layer on the radar back-scattering signal.It was found that the vegetation water content retrieved by NDWI index was used as the input parameter of the Water Cloud Model,with the purpose of removing the influence of surface vegetation,and a more real soil back-scattering coefficient could be obtained.According to the comparison of radar back-scattering coefficients before and after the removal of vegetation coverage,the VV polarization attenuation value obtained by NDVI index is about 0.01-2.6d B,and the average influence value of vegetation layer on radar VV polarization back-scattering coefficient is 0.39d B.The VH polarization is reduced by0.07-4.06 d B,and the average effect of vegetation layer on the back-scattering coefficient of VH polarization is 0.61 d B.The range of VV polarization attenuation value obtained by NDWI index is about 0.8-3.7d B.The average influence of vegetation layer on the radar VV polarization back-scattering coefficient is 1.58d B,and the VH polarization is reduced by 1.2-4.5d B.The average influence of vegetation layer on the radar VH polarization back-scattering coefficient is 2.57d B ;It is known that NDWI index is more suitable as the input parameter of Water Cloud Model

Mots clés : Sentinel satellite ;Soil moisture ;Water Cloud Model(WCM) ;BP Neural Network Model ;RBF Neural Network Model ;

Présentation (CNKI)

Page publiée le 29 octobre 2021