Fan et al. (2026) Emissivity-Driven Directional Biases in Geostationary Satellite Land Surface Temperature: Integrated Comparison and Parametric Analysis Across Complex Terrain in Hunan, China

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-01-15
• Authors: Jiazhi Fan, Qinzhe Han, Bing Sui, Leishi Chen, Luping Yang, Guanru Lv, Bi Zhou, Enguang Li
• DOI: 10.3390/rs18020284

Research Groups

Not explicitly specified in the provided text, but the study focuses on Hunan Province, China, using East Asian geostationary satellites, suggesting involvement of research institutions in China or East Asia.

Short Summary

This study investigates the impact of angular effects (directional anisotropy) on land surface temperature (LST) retrievals from three East Asian geostationary satellites over Hunan Province, China. It finds that emissivity kernel-induced anisotropy is the primary driver of LST deviations, leading to systematic cold biases across all products, with varying accuracy depending on solar and viewing geometry and terrain characteristics.

Objective

• To examine the impact of angular effects (directional anisotropy) on land surface temperature (LST) retrievals from FengYun 4A, FengYun 4B, and Himawari 9 geostationary satellites across Hunan Province, China, through integrated comparison with in situ measurements and reanalysis data.

Study Configuration

• Spatial Scale: Hunan Province, China.
• Temporal Scale: Diurnal (implied by "diurnal retrieval precision" and continuous monitoring by geostationary satellites).

Methodology and Data

• Models used: Parametric modeling (for analyzing emissivity and solar kernel-induced anisotropy).
• Data sources:
  • Satellite: FengYun 4A (FY4A), FengYun 4B (FY4B), Himawari 9 LST products.
  • Observation: In situ measurements.
  • Reanalysis: Reanalysis data.

Main Results

• All satellite LST products exhibit a systematic cold bias.
• FengYun 4B (FY4B) achieves the highest retrieval accuracy among the tested products.
• Diurnal retrieval precision increases with higher solar zenith angles (SZA).
• No consistent relationship was observed between viewing zenith angle (VZA) and retrieval accuracy.
• The retrieval bias of the FY4 series significantly increases when the sun and sensor are aligned in azimuth, particularly when the relative azimuth angle (RAA) is less than or equal to 30 degrees.
• Emissivity kernel-induced anisotropy is identified as the principal driver of significant LST deviations in central Hunan.
• Solar kernel effects result in LST overestimation in mountainous regions and underestimation in plains.
• Increases in elevation or vegetation density reduce emissivity-induced errors but amplify errors caused by shadowing and sunlit effects.
• Emissivity anisotropy is confirmed as the primary source of LST directional anisotropy (DA).

Contributions

• Deepens the understanding of land surface temperature (LST) directional anisotropy (DA) in remote sensing.
• Provides essential guidance for refining LST retrieval algorithms.
• Improves the applicability of satellite-derived LST products, especially in complex terrains.
• Quantifies and characterizes angular effects on LST from specific East Asian geostationary satellites (FY4A, FY4B, Himawari 9) over a complex geographical region.

Funding

Not specified in the provided text.

Citation

@article{Fan2026EmissivityDriven,
  author = {Fan, Jiazhi and Han, Qinzhe and Sui, Bing and Chen, Leishi and Yang, Luping and Lv, Guanru and Zhou, Bi and Li, Enguang},
  title = {Emissivity-Driven Directional Biases in Geostationary Satellite Land Surface Temperature: Integrated Comparison and Parametric Analysis Across Complex Terrain in Hunan, China},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18020284},
  url = {https://doi.org/10.3390/rs18020284}
}