Under the pressure of SDG15.3.1 compliance,it is imperative to solve the land salinization degradation problem in the Yellow River Basin as China’s granary.From the view of geographical scale,six zoning units were di...Under the pressure of SDG15.3.1 compliance,it is imperative to solve the land salinization degradation problem in the Yellow River Basin as China’s granary.From the view of geographical scale,six zoning units were divided in the Yellow River Basin with‘climate-meteorology-geomorphology’as the main controlling factor,and a salinization inversion model was constructed for each zoning unit.Appropriate surface parameters were selected to construct a three-dimensional feature space according to the individual geographical zones.Based on the cloud data processing capability of the Google Earth Engine platform,a feature space inversion process was applied for automatic inversion of salinization.Salinization distribution maps of the Yellow River Basin in 2015 and 2020 were obtained at 30 m resolution by classifying the salinization inversion result.The distribution and spatiotemporal variation of salinization as well as the causes of salinization were analyzed.Reasonable prevention and control suggestions were subsequently proposed.This study could also be scaled up to larger and more complex geographical regions.展开更多
China’s Yellow River Delta represents a typical area with moist semi-humid soil salinization,and its salinization has seriously affected the sustainable use of local resources.The use of remote sensing technology to ...China’s Yellow River Delta represents a typical area with moist semi-humid soil salinization,and its salinization has seriously affected the sustainable use of local resources.The use of remote sensing technology to understand changes in the spatial and temporal patterns of salinization is key to combating regional land degradation.In this study,a feature space model was constructed for remote sensing and monitoring land salinization using Landsat 8 OIL multi-spectral images.The feature parameters were paired to construct a feature space model;a total of eight feature space models were obtained.An accuracy analysis was conducted by combining salt-loving vegetation data with measured data,and the model demonstrating the highest accuracy was selected to develop salinization inversion maps for 2015 and 2020.The results showed that:(1)The total salinization area of the Yellow River Delta displayed a slight upward trend,increasing from 4244 km^(2) in 2015 to 4629 km^(2) in 2020.However,the area’s salting degree reduced substantially,and the areas of saline soil and severe salinization were reduced in size;(2)The areas with reduced salinization severity were mainly concentrated in areas surrounding cities,and primarily comprised wetlands and some regions around the Bohai Sea;(3)Numerous factors such as the implementation of the“Bohai Granary”cultivation engagement plan,increase in human activities to greening local residential living environments,and seawater intrusion caused by the reduction of sediment contents have impacted the distribution of salinization areas in the Yellow River Delta;(4)The characteristic space method of salinization monitoring has better applicability and can be promoted in humid-sub humid regions.展开更多
文摘Under the pressure of SDG15.3.1 compliance,it is imperative to solve the land salinization degradation problem in the Yellow River Basin as China’s granary.From the view of geographical scale,six zoning units were divided in the Yellow River Basin with‘climate-meteorology-geomorphology’as the main controlling factor,and a salinization inversion model was constructed for each zoning unit.Appropriate surface parameters were selected to construct a three-dimensional feature space according to the individual geographical zones.Based on the cloud data processing capability of the Google Earth Engine platform,a feature space inversion process was applied for automatic inversion of salinization.Salinization distribution maps of the Yellow River Basin in 2015 and 2020 were obtained at 30 m resolution by classifying the salinization inversion result.The distribution and spatiotemporal variation of salinization as well as the causes of salinization were analyzed.Reasonable prevention and control suggestions were subsequently proposed.This study could also be scaled up to larger and more complex geographical regions.
基金The Strategic Priority Research Program of Chinese Academy of Sciences(XDA19040501)The Construction Project of the China Knowledge Center for Engineering Sciences and Technology(CKCEST-2021-2-18)。
文摘China’s Yellow River Delta represents a typical area with moist semi-humid soil salinization,and its salinization has seriously affected the sustainable use of local resources.The use of remote sensing technology to understand changes in the spatial and temporal patterns of salinization is key to combating regional land degradation.In this study,a feature space model was constructed for remote sensing and monitoring land salinization using Landsat 8 OIL multi-spectral images.The feature parameters were paired to construct a feature space model;a total of eight feature space models were obtained.An accuracy analysis was conducted by combining salt-loving vegetation data with measured data,and the model demonstrating the highest accuracy was selected to develop salinization inversion maps for 2015 and 2020.The results showed that:(1)The total salinization area of the Yellow River Delta displayed a slight upward trend,increasing from 4244 km^(2) in 2015 to 4629 km^(2) in 2020.However,the area’s salting degree reduced substantially,and the areas of saline soil and severe salinization were reduced in size;(2)The areas with reduced salinization severity were mainly concentrated in areas surrounding cities,and primarily comprised wetlands and some regions around the Bohai Sea;(3)Numerous factors such as the implementation of the“Bohai Granary”cultivation engagement plan,increase in human activities to greening local residential living environments,and seawater intrusion caused by the reduction of sediment contents have impacted the distribution of salinization areas in the Yellow River Delta;(4)The characteristic space method of salinization monitoring has better applicability and can be promoted in humid-sub humid regions.
