Forest Structure Alters Heat Signals Detected by Satellites

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A new study published in the Journal of Remote Sensing reveals that forest heat signals detected by thermal infrared satellites depend strongly on the three-dimensional structure of the forest canopy, not just the properties of leaves or soil. Using a detailed 3D radiative transfer model, researchers found that directional emissivity changes with viewing angle, canopy density, and tree arrangement, offering a more accurate path for retrieving forest temperatures and improving climate-relevant remote sensing.

Why it matters

Land surface temperature and emissivity are crucial for understanding ecosystem energy balance, evapotranspiration, vegetation health, and water use. However, satellites do not directly measure true surface temperature; they record radiance that must be converted through complex inversion models. This is especially challenging in forests, where 3D canopy structure makes thermal signals highly directional. The findings from this study can help improve land surface temperature retrieval for upcoming thermal satellite missions by better accounting for forest structure and observation angle.

The details

The researchers used the DART 3D radiative transfer model to simulate directional emissivity across eight realistic RAMI-V forest scenes with varying structures, including pine, birch, citrus orchard, poplar, savanna, and temperate forest cases. They found that directional emissivity ranged from 0.972 to 0.996 across the different forest types, a spread large enough to produce forest temperature retrieval errors greater than 1 K. The analysis revealed that canopy architecture strongly controls thermal behavior, with forests having higher leaf area index and more homogeneous tree distribution showing relatively high mean emissivity values around 0.994, while row-planted or more open stands were closer to 0.985, and winter pine stands with low leaf area index fell to about 0.980 or even 0.974.

• The study was published on February 19, 2026 in the Journal of Remote Sensing.

What’s next

The findings from this study could help improve land surface temperature retrieval for upcoming thermal satellite missions by better accounting for forest structure and observation angle. It also provides a stronger physical basis for multi-angular emissivity correction, especially in forests with sparse cover, low leaf area, or row planting. In the longer term, the approach may support more reliable ecosystem monitoring, climate modeling, and precision observation of forest stress, energy exchange, and land-atmosphere interactions at high spatial resolution.