Study On Spatial Morphological Changes Of The Zhengzhou Section Of The Yellow River Based On Landsat Images(2010-2020)

As the second largest river in China,the development of the Yellow River basin has an important impact on China’s economy,agriculture and water resources.The management,development,conservation and administration of the Yellow River are of strategic importance to the socio-economic and ecological protection of China.The uncoordinated relationship between water and sand and the instability of the river channel have damaged the natural geomorphology of the lower reaches of the Yellow River,causing disorder in the water system and siltation of rivers and lakes,hindering the socio-economic development of the middle and lower reaches of the Yellow River and posing a great threat to the production and livelihood of the people in the middle and lower reaches of the Yellow River.Zhengzhou,as a representative section of the middle and lower reaches of the Yellow River,has undergone frequent changes in spatial patterns in recent decades.The results of the study to grasp the spatial morphological changes of the Zhengzhou section of the Yellow River can reflect the history of the river’s changes,and can provide a reference for the influencing factors of the changes and provide predictions for future changes in river morphology.Therefore,studying the spatial morphological changes of the Zhengzhou section of the Yellow River based on remote sensing images can provide support for the management and sustainable development of the Yellow River,and is of great significance to the management and protection of the middle and lower reaches of the Yellow River.The existing studies on the changes of the Yellow River mainly focus on the three directions of channel change,river shape change and water-sand change,but there is less research on the quantitative description of the spatial morphology of the Zhengzhou section of the Yellow River,and the universal quantitative indexes used in the studies cannot reflect the spatial morphological characteristics of the Zhengzhou section of the Yellow River,which has a variable main stream,frequent oscillations,wide and shallow river body,sandbars and scattered,braided bifurcation.With the successful launch of a large number of satellites in recent years,surface exploration and research based on satellite remote sensing have made rapid progress.How to use satellite remote sensing images for fast and accurate river information extraction is a popular topic of research in recent years.Traditional water extraction methods are based on the spectral features of the images,however,in practical applications,as river information is affected by the surrounding environmental factors,the traditional water extraction methods cannot meet the accuracy requirements of research on rivers.In this paper,we propose a deep learning network model for the extraction of water bodies in Zhengzhou section of the Yellow River,and based on the river information extracted from this model,we summarise the characteristics of the spatial morphology of Zhengzhou section of the Yellow River and design a quantitative indicator for different characteristics of the spatial morphology.The quantitative indicators of spatial morphology are designed for different characteristics.Based on the 2010-2020 Landsat 7 and Landsat 8 images,the study selected the Zhengzhou section of the Yellow River as the study area and carried out a quantitative analysis of the spatial morphological changes of the Zhengzhou section of the Yellow River from 2010 to 2020.The main innovative work and conclusions of this paper are as follows.(1)The rivers in the Zhengzhou section of the Yellow River are scattered and mixed with water and sand.The current commonly used water body extraction methods cannot meet the accuracy requirements of the study for the river.To address this problem,this paper proposes an AU-Net network model for water body extraction in the Zhengzhou section of the Yellow River,using the U-Net network as a benchmark.By introducing the ASPP module,the convolutional kernel perceptual field is expanded when fusing the image feature information.The feasibility and effectiveness of the network model are also verified through experiments.The results show that the AU-NET model has high recognition accuracy(MPA=0.97 and MIOU=0.99)on the middle and lower reaches of the Yellow River water body dataset.Combining the prediction result plots with the network convergence plots,the method in this paper also has advantages in robustness and fit,which are further demonstrated by clearer river edges,improved misclassification and omission of water bodies that occur in the U-net network,and better differentiation of tiny water bodies,solving the problem of accurate extraction of water bodies in the middle and lower reaches of the Yellow River.(2)According to the characteristics of the spatial morphology of the Zhengzhou section of the Yellow River,six quantitative descriptive indicators are designed in this paper,mainly covering four aspects of river stability,river core sandbar situation,river potential situation and river water quantity situation,and correlation analysis is carried out between each indicator.At the same time,the study proposes a method to quickly generate river sections and extract the required data for the Zhengzhou section of the Yellow River,and improves the Improved Relative Stability Index of River Regime(RSIRR-G).The method allows the index to be applied to the variable river paths in the Zhengzhou section of the Yellow River with ease of operation and low computational effort.The quantitative index designed in this paper fills a gap in the existing research on the quantitative analysis of spatial morphological changes in the Zhengzhou section of the Yellow River.(3)The quantitative indicators designed in this paper were used to analyse the changes in the spatial morphology of the Zhengzhou section of the Yellow River from 2010 to 2020.The main conclusions are as follows: The spatial morphology of the Zhengzhou section of the Yellow River has changed significantly from 2010 to 2020.The cross-section of stable river sections is increasing,and the cross-section of unstable river sections and transitional river sections is significantly decreasing;the main stream swing is gradually decreasing,gradually completing the transformation of wandering river-relatively stable river-stable river;the sandbars in the core of the river are constantly changing,and the flowing sandbars change from a scattered state to an aggregated state;the forked streams in the Zhengzhou section of the Yellow River show an increase-decrease-stable change;the overall large area of the river body disappears,and the dry area and fixed The area of dry and fixed streams continues to expand.The changes in the spatial pattern of the river in the Zhengzhou section of the Yellow River are inextricably linked to the various measures taken by the state to regulate water and sand in the middle and lower reaches of the Yellow River.The optimal regulation of water and sand conditions,combined with the increasing improvement of river training projects,can effectively improve the wandering and variable river morphology of the Zhengzhou section of the Yellow River and promote a more stable trend in the morphology of the Zhengzhou section of the Yellow River.Translated with www.Deep L.com/Translator(free version)The results of this study can be used to support the extraction of water bodies in the middle and lower reaches of the Yellow River,as well as the calculation of quantitative indicators of spatial morphology,which can effectively analyse the changing spatial morphology of the middle and lower reaches of the Yellow River over a long period of time,and thus contribute to the protection and management of water resources in the middle and lower reaches of the Yellow River.