biostudies-literatureUnknown16Zhao Z<h4>Introduction</h4>The Leaf Area Index (LAI) is a critical biophysical parameter for assessing crop canopy structure and health. Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensors offer a high-throughput solution for LAI estimation, but flight altitude compromises between efficiency and image resolution, ultimately impacting accuracy. This study investigates the integration of super-resolution (SR) image reconstruction with multi-sensor data to enhance LAI estimation for soybeans across varying UAV flight altitudes.<h4>Methods</h4>RGB and multispectral images were captured at four flight altitudes: 15 m, 30 m, 45 m, and 60 m. The acquired images were processed using several SR algorithms (SwinIR, Real-ESRGAN, SRCNN, and EDSR). Texture features were extracted from the RGBFrontiers in plant science1700660https://www.ebi.ac.uk/biostudies/studies/S-EPMC12675413biostudies-literatureUAV multi-source data fusion with super-resolution for accurate soybean leaf area index estimation.PMC12675413Jiang ZZhang XYao HZhao ZZeng DfalseUAV multi-source data fusion with super-resolution for accurate soybean leaf area index estimation.<h4>Introduction</h4>The Leaf Area Index (LAI) is a critical biophysical parameter for assessing crop canopy structure and health. Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensors offer a high-throughput solution for LAI estimation, but flight altitude compromises between efficiency and image resolution, ultimately impacting accuracy. This study investigates the integration of super-resolution (SR) image reconstruction with multi-sensor data to enhance LAI estimation for soybeans across varying UAV flight altitudes.<h4>Methods</h4>RGB and multispectral images were captured at four flight altitudes: 15 m, 30 m, 45 m, and 60 m. The acquired images were processed using several SR algorithms (SwinIR, Real-ESRGAN, SRCNN, and EDSR). Texture features were extracted from the RGB2025-01-01T00:00:00Z20252026-06-05T23:30:02.837Z2026-05-23T03:13:39.493ZS-EPMC126754134135836410.3389/fpls.2025.1700660