Cao et al. (2026) A unified kernel-driven modeling framework adapted to continuous, discrete and row-planted canopies in the thermal infrared domain

Identification

• Journal: Remote Sensing of Environment
• Year: 2026
• Date: 2026-07-06
• Authors: Biao Cao Biao Cao, Yingjie Wang, Jean‐Philippe Gastellu‐Etchegorry
• DOI: 10.1016/j.rse.2026.115548

Research Groups

• State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, China
• Centre d'Etudes Spatiales de la BIOsph`ere (CESBIO) - UPS, CNES, CNRS, IRD, Universit´e de Toulouse, France

Short Summary

This study presents a unified kernel-driven modeling framework for continuous, discrete and row-planted canopies in the thermal infrared domain, achieving significant improvements over existing models with RMSE reduction percentages up to 84.9% for simulated scenes and 61.2% for measured scenes.

Objective

• Develop a unified kernel-driven modeling framework that can accurately simulate the angular effect of row structure on land surface temperature (LST) in row-planted canopies.

Study Configuration

• Spatial Scale: Local to regional scales, with applications to agricultural areas and horticultural crops.
• Temporal Scale: Long-term monitoring and prediction of LST for water management and yield forecasting.

Methodology and Data

• Models used: Unified kernel-driven modeling framework, including isotropic kernel, base shape kernel, hotspot kernel, and hot belt kernel; two instantiated models (Kimes-RL-Ganis and Kimes-Chen-Ganis).
• Data sources: DART-simulated datasets and airborne-measured multi-angle datasets.

Main Results

• The unified framework achieved significant improvements over existing models, with RMSE reduction percentages up to 84.9% for simulated scenes (1.322–1.445 K to 0.300–0.349 K) and 61.2% for measured scenes (1.580–1.654 K to 0.882–0.909 K).

Contributions

• The study provides a unified framework that can accurately simulate the angular effect of row structure on LST in row-planted canopies, offering significant potential for advancing angular normalization of land surface temperature across diverse vegetation types.

Funding

• This research was supported by [project/program name and reference code], [project/program name and reference code].

Citation

@article{Cao2026unified,
  author = {Cao, Biao Cao Biao and Wang, Yingjie and Gastellu‐Etchegorry, Jean‐Philippe},
  title = {A unified kernel-driven modeling framework adapted to continuous, discrete and row-planted canopies in the thermal infrared domain},
  journal = {Remote Sensing of Environment},
  year = {2026},
  doi = {10.1016/j.rse.2026.115548},
  url = {https://doi.org/10.1016/j.rse.2026.115548}
}