干旱区地理2025，Vol.48Issue(12)：2143-2157,15.DOI:10.12118/j.issn.1000-6060.2025.044
艾比湖春夏季土壤盐渍化卫星监测对比分析
Comparative analysis of satellite monitoring of soil salinization in Ebinur Lake during spring and summer
摘要
Abstract
Soil salinization is a major factor in arid and semi-arid regions,adversely affecting agricultural produc-tion and the ecological environment.Accurately capturing the spatiotemporal distribution of soil salinization has become a key focus in current research across the fields of ecology,geography,and agriculture.In this study,Sen-tinel-2A imagery from April and July,along with corresponding in-situ measurements of the salinity of surface soil,were utilized to construct soil salinity inversion models for the Ebinur Lake region.Five machine learning al-gorithms[random forest(RF),support vector regression,decision tree regression,adaptive boosting(Adaboost),and gradient boosting regression tree]and two deep learning methods(deep belief network and fully convolution-al network]were employed for this purpose.Variables were selected using the Boruta algorithm to enhance the performance of the model.The results indicate that:(1)In April,the soil salinity exhibited a strong positive corre-lation with various spectral bands,whereas the overall correlation strength decreased in July.Among multispec-tral indices,the intensity indices(Int1,Int2),salinity indices(S3,S5,S6,SI,SI1,SI2,SI3),and the ratio index showed strong positive correlations with the soil salinity,whereas the normalized difference index displayed a strong neg-ative correlation.(2)The RF model achieved the highest predictive accuracy in both time periods,with an aver-age R2 and RMSE of 0.72 and 0.13 in April and 0.66,and 0.15 in July,respectively.Therefore,the RF model was identified as the optimal model in this study.Furthermore,in terms of temporal selection,soil salinity inversion in April yielded higher accuracy compared to July,indicating that April is more favorable for soil salinity monitor-ing in arid regions.关键词
Sentinel-2A/土壤含盐量/遥感反演/机器学习/深度学习Key words
Sentinel-2A/soil salinity/remote sensing inversion/machine learning/deep learning引用本文复制引用
GUO Jiali,MA Yonggang,PAN Heng,LI Na,SUN Changning,SUN Qian,ZHOU Wenchang,DANG Yuxuan..艾比湖春夏季土壤盐渍化卫星监测对比分析[J].干旱区地理,2025,48(12):2143-2157,15.基金项目
第三次新疆综合科学考察项目(2021xjkk1400) （2021xjkk1400）
新疆维吾尔自治区自然科学基金(2023D01D01)资助 （2023D01D01）
