农业机械学报2024，Vol.55Issue(2)：208-219,12.DOI:10.6041/j.issn.1000-1298.2024.02.020
基于Landsat8与Sentinel-1遥感图像融合的土壤含水率反演模型
Soil Moisture Content Inversion Model Based on Landsat8 and Sentinel-1 Image Fusion
摘要
Abstract
To address the current problems that a single optical satellite is easily affected by clouds and SAR satellite is easily affected by vegetation and soil roughness when being applied into soil moisture content inversion,taking Shahaoqu of Iletao Irrigation Area as study area,and taking soil moisture content of four depths in April 2019 as study object,PCA and GS were used to fuse Landsat8 and Sentinel-1 images and the quality of the fused images was evaluated.Then a total of 1 134 remote sensing indices were constructed with the gray value of the fused images,and soil moisture content inversion models were constructed based on three variable screening methods(correlation coefficient analysis,variable projection importance analysis and gray correlation analysis)and four machine learning algorithms(BP,ELM,RF,and SVM).The study results showed that the fused images of PCA and GS fusion could successfully maintain the advantages of both Sentinel-1 and Landsat8 images in quantitatively inversion of soil moisture content.The three-dimension indices constructed based on the fused images were generally more sensitive to soil moisture content than two-dimension indices constructed based on fused images.The VIP-ELM model based on GS fusion had the highest accuracy in the surface soil moisture content inversion(R2=0.66,RMSE was 1.35％).When VIP-ELM model based on GS fusion was applied to the soil moisture content inversion at all depths,20～40 cm achieved the best performance(R2=0.79,RMSE was 0.94％),followed by 0～10 cm,40～60 cm and 10～20 cm.This finding can provide astrong reference for using multi-source satellite image fusion to monitor soil moisture content.关键词
土壤含水率/卫星图像融合/机器学习/耦合模型Key words
soil moisture content/satellite image fusion/machine learning/coupled model分类
农业科技引用本文复制引用
陈俊英,项茹,贺玉洁,吴雨箫,殷皓原,张智韬..基于Landsat8与Sentinel-1遥感图像融合的土壤含水率反演模型[J].农业机械学报,2024,55(2):208-219,12.基金项目
国家自然科学基金项目(51979234、52279047、52179044、51979232)和国家重点研发计划项目(2022YFD1900404) （51979234、52279047、52179044、51979232）
