A Geometric Kernel-Driven Model to Simulate Thermal Radiation Directionality by Accounting for Component Temperatures Over Sparse Tree-Covered Surfaces (GTTA-Sparse)
Year: 2026
Type: article
Abstract: Existing kernel-driven models for angular effect correction of satellite data over vegetated areas generally lack explicit physical interpretations of their kernel coefficients and face challenges in component temperature retrieval. To address these issues, we propose a Geometric kernel-driven model that explicitly Accounts for the radiative contributions of the scene components to simulate Thermal radiation directionality (TRD) over Sparse Tree-covered surfaces (GTTA-sparse). The model decomposes TRD into three contributions: the effects of trees on the ground, the illuminated canopy, and the illuminated ground. Validation against discrete anisotropic radiative transfer (DART) simulations and uncrewed aerial vehicle (UAV) data showed that the GTTA-sparse model achieved root mean square errors (RMSEs) of 0.04–0.05 K and 0.67–0.83 K for TRD. The GTTA-sparse model is insensitive to solar angles but sensitive to large view angles (30°–60°). It is suitable for surfaces where the tree geometric structural ratio (TGSR) is less than or equal to 1. The effects of leaf-induced gaps within tree crowns are reflected in kernel coefficients ($f_{1}$,$f_{2},f_{3}$), whose variations quantify the biases in kernel functions ($k_{1},k_{2}$,$k_{3}$) caused by crown gaps. The GTTA-sparse model achieved high accuracy in component temperature retrieval, with a bias below 1 K for illuminated ground. The GTTA-sparse framework provides a physically consistent approach for modeling TRD over tree-covered surfaces.
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,645
OpenAlex ID: W7204141325