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LESS: LargE-Scale remote sensing data and image simulation framework over heterogeneous 3D scenes

DOI:10.1016/j.rse.2018.11.036 期刊:Remote Sensing of Environment 出版年份:2019 更新时间:2025-09-23 15:23:52
摘要: Three-dimensional (3D) radiative transfer modeling of the transport and interaction of radiation through earth surfaces is challenging due to the complexity of the landscapes as well as the intensive computational cost of 3D radiative transfer simulations. To reduce computation time, current models work with schematic landscapes or with small-scale realistic scenes. The computer graphics community provides the most accurate and efficient models (known as renderers) but they were not designed specifically for performing scientific radiative transfer simulations. In this study, we propose LESS, a new 3D radiative transfer modeling framework. LESS employs a weighted forward photon tracing method to simulate multispectral bidirectional reflectance factor (BRF) or flux-related data (e.g., downwelling radiation) and a backward path tracing method to generate sensor images (e.g., fisheye images) or large-scale (e.g. 1 km2) spectral images. The backward path tracing also has been extended to simulate thermal infrared radiation by using an on-the-fly computation of the sunlit and shaded scene components. This framework is achieved through the development of a user-friendly graphic user interface (GUI) and a set of tools to help construct the landscape and set parameters. The accuracy of LESS is evaluated with other models as well as field measurements in terms of directional BRFs and pixel-wise simulated image comparisons, which shows very good agreement. LESS has the potential in simulating datasets of realistically reconstructed landscapes. Such simulated datasets can be used as benchmarks for various applications in remote sensing, forestry investigation and photogrammetry.
作者: Jianbo Qi,Donghui Xie,Jean-Philippe Gastellu-Etchegorry,Linyuan Li,Wuming Zhang,Xihan Mu,Leslie K. Norford,Tiangang Yin,Guangjian Yan
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To propose LESS, a new 3D radiative transfer modeling framework for simulating multispectral bidirectional reflectance factor (BRF), flux-related data, sensor images, and thermal infrared radiation over heterogeneous 3D scenes, addressing the challenges of computational cost and complexity in existing models.

LESS is an effective 3D radiative transfer modeling framework that accurately simulates BRF, thermal infrared images, and large-scale spectral data. It shows good agreement with other models and field measurements, offering advantages in computational efficiency and memory usage. The flexible architecture allows for future extensions, such as LiDAR simulation and GPU acceleration, making it a valuable tool for remote sensing applications.

The current version of LESS does not support thermal radiation simulation in forward mode due to high computational demands and sampling errors. It is less suitable for studying radiative budget with thermal emission. Additionally, the framework may require further optimization for very large scenes or real-time applications, and the accuracy depends on the quality of input parameters and scene reconstruction.

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