河南理工大学学报（自然科学版）2025，Vol.44Issue(3)：112-118,7.DOI:10.16186/j.cnki.1673-9787.2023120040
基于时空融合模型和TVDI的土壤水分监测方法研究
Study on soil moisture monitoring method based on Spatiotemporal Image-fusion Model and TVDI
摘要
Abstract
Objectives To address the limitations of using single-source remote sensing data(e.g.,MODIS or Landsat TIRS/TIRS-2)in monitoring soil moisture through the Temperature Vegetation Dryness Index(TVDI),which often leads to insufficient spatiotemporal resolution,Methods a soil moisture monitoring ap-proach was proposed by integrating the spatiotemporal image-fusion model(STI-FM)with TVDI.This study evaluated the monitoring performance of this method and assessed the applicability of STI-FM in fusing multi-source remote sensing land surface temperature(LST)data within the study area.Results(1)The STI-FM model demonstrates superior performance in fusing MODIS and Landsat TIRS/TIRS-2 land surface temperature(LST)data,achieving strong correlation(R²=0.89)and low error(RMSE=2.85 K)between the predicted and satellite-observed LST values,confirming its applicability in the study area.(2)Com-pared to traditional TVDI,the modified TVDI combining STI-FM-enhanced LST data and optimized vegeta-tion indices significantly improved soil moisture monitoring accuracy.The correlation coefficients between TVDI and soil moisture increased by 0.07(June)and 0.14(July)compared to original NDVI-LST feature space calculations.(3)The improved TVDI achieved higher accuracy than ERA5-Land reanalysis soil mois-ture data.Correlation coefficients between TVDI and soil moisture surpassed ERA5-Land by 0.10(June)and 0.44(July).Conclusions The STI-FM-enhanced TVDI framework significantly improves soil moisture monitoring by simultaneously enhancing estimation accuracy and providing higher spatial resolution com-pared to conventional methods,offering a novel paradigm for TVDI-based moisture retrieval.关键词
土壤水分/TVDI/时空融合模型/时空融合/适用性Key words
soil moisture/TVDI/spatiotemporal image-fusion model/spatio-temporal fusion/applicability分类
农业科技引用本文复制引用
赵军,刘坚,胡飞鹏,托瑞,孙紫云..基于时空融合模型和TVDI的土壤水分监测方法研究[J].河南理工大学学报（自然科学版）,2025,44(3):112-118,7.基金项目
国家自然科学基金资助项目(42161072) （42161072）
