Spatial and Temporal Pattern Changes and Driving Forces:Analysis of Salinization in the Yellow River Delta from 2015 to 2020  

黄河三角洲2015-2020盐渍化时空变化及成因分析

作　　者：HONG Mengmeng WANG Juanle HAN Baomin 洪梦梦;王卷乐;韩保民(山东理工大学建筑工程学院,山东淄博255049;中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京100101)

机构地区：[1]School of Civil and Architectural Engineering,Shandong University of Technology,Shandong 255049,China [2]State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China

出　　处：《Journal of Resources and Ecology》2022年第5期786-796,共11页资源与生态学报（英文版）

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)。

摘　　要：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.黄河三角洲是我国湿润-半湿润土壤盐渍化的典型地区,其盐渍化现象已严重影响当地土壤资源的可持续利用。本研究利用Landsat 8 OIL多光谱影像,运用ENVI、ArcGIS等软件提取研究区内的7个相关地表特征参量并将其两两组合,构建特征空间模型,选取其中拟合度较高的8个特征空间模型,结合喜盐植被对其进行精度分析并筛选出精度最高的模型形成盐渍化反演图。结果表明:2015年Albedo-SI模型的适用性最高,精度为75%;2020年NSNM模型的适用性最高,精度为67.5%。研究结果显示:(1)黄河三角洲盐渍化总体面积呈轻微上升趋势,由2015年的4244km^(2)上升至2020年的4629km^(2),但其盐渍化程度显著下降,盐土及重度盐渍化面积减少;(2)盐渍化减轻地区主要分布在城市周边地区及水稻面积增多地区,盐渍化加重地区为湿地及部分沿海地区;(3)“渤海粮仓”计划的实施、当地居民生活环境绿化改造等人类活动、黄河泥沙含量减少造成的海水倒灌等因素均对区域盐渍化分布造成影响;(4)特征空间方法对盐渍化监测具有较好的适用性,可以在更多湿润-半湿润地区推广。

关 键 词：SALINIZATION land degradation feature space salt-loving vegetation the Yellow River Delta 

分 类 号：S156.41[农业科学—土壤学]