Zhong et al. (2026) A Vegetation Growth Pattern-Constrained Interpolation Method for High-Resolution Daily FPAR/LAI Reconstruction and NPP Spatial Disaggregation

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-09-18
• Authors: Meiheng Zhong, Zi Ye, Yihao Liu, Siqi Long, Rixiu Zhou, Dehua Zhao
• DOI: 10.3390/rs18183211

Research Groups

• Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences
• University of Nanjing

Short Summary

This study develops a phenology-constrained interpolation method to reconstruct high-spatial-resolution fractions of absorbed photosynthetically active radiation (FPAR) and leaf area index (LAI) for urban vegetation productivity characterization. The method achieves accurate results, with potential applications in net primary productivity (NPP) estimation.

Objective

• Reconstruct annual daily 10 m FPAR and LAI for characterizing urban vegetation productivity

Study Configuration

• Spatial Scale: 10 m spatial resolution for FPAR and LAI reconstruction
• Temporal Scale: Annual daily dynamics of FPAR and LAI

Methodology and Data

• Models used: Phenology-constrained interpolation method with logistic functions
• Data sources: Sentinel-2 images, MOD15A2H FPAR/LAI data (500 m resolution)

Main Results

• The reconstructed 10 m FPAR and LAI achieved R2 values of 0.69–0.95 and 0.82–0.97, respectively.
• Cross-comparison with independent Sentinel-2 retrievals showed mean relative differences of −0.23% and −1.32%, and mean absolute relative differences of 5.12% and 7.43% for FPAR and LAI, respectively.

Contributions

• The study provides a novel method for reconstructing high-spatial-resolution FPAR and LAI, which can be used as inputs for NPP estimation.
• The results highlight the importance of considering fine-scale patterns of urban vegetation productivity in characterizing regional carbon fluxes.

Funding

• This research was supported by the National Natural Science Foundation of China (Grant No. 42171365)

Citation

@article{Zhong2026Vegetation,
  author = {Zhong, Meiheng and Ye, Zi and Liu, Yihao and Long, Siqi and Zhou, Rixiu and Zhao, Dehua},
  title = {A Vegetation Growth Pattern-Constrained Interpolation Method for High-Resolution Daily FPAR/LAI Reconstruction and NPP Spatial Disaggregation},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18183211},
  url = {https://doi.org/10.3390/rs18183211}
}