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全文摘要次数: 86 全文下载次数: 80
引用本文:

DOI:

10.11834/jrs.20243510

收稿日期:

2023-11-30

修改日期:

2024-03-19

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三维解析辐射传输模型ESRT原理及其异质森林冠层光谱模拟应用
摘要:

森林场景中的复杂空间异质性会影响冠层反射特性,如何处理异质性问题是辐射传输建模领域的难点。为克服经典解析模型简化场景导致的精度受限问题以及计算机模拟模型在大场景模拟中的运行效率受限问题,我们基于随机辐射传输理论开发了三维解析辐射传输模型ESRT,然而ESRT模型在不同复杂森林场景的应用尚待挖掘,需要更多的野外实测数据进行模型验证与评估。本文介绍了ESRT模型的基本原理和输入输出参数,并基于21个混交林样地和50个虫害胁迫样地调查数据,探讨模型模拟不同类型异质森林冠层光谱的能力,并分析混交、虫害程度对森林冠层光谱的影响。结果表明,相比原版SRT模型,扩展的ESRT模型模拟混交林、虫害胁迫林分冠层光谱与样地实测光谱有更好的一致性,模拟精度更接近三维计算机模型;针阔混交比、受害叶片的垂直分布均会影响冠层光谱信号。ESRT模型提供了面向多种异质森林场景的辐射传输模拟框架,平衡了三维结构的模拟精度与经典解析模型的模拟效率,更适合大尺度的复杂林分模拟。研究可为ESRT模型的复杂森林场景监测应用提供一定的理论基础。

Principles of the Three-dimensional Analytical Radiative Transfer Model ESRT and its Applications in Simulating Heterogeneous Forest Canopy Spectra
Abstract:

【Objective】The complicated spatial heterogeneity in forest scenes may have an effect on canopy reflectance. How to address heterogeneity is a challenge in the field of radiative transfer modeling. To overcome the accuracy limitations of classical analytical models caused by simplified scenarios and the efficiency limitations of computer simulation models in large-scale applications, we developed a three-dimensional analytical radiative transfer model called ESRT based on stochastic radiative transfer theory. At present, the application of ESRT in different complex forest scenes still needs to be explored, and more field data is essential for model verification. 【Method】This paper introduces the basic principles and input-output parameters of the ESRT model, in which two key input parameters were proposed to express different heterogeneous canopy structures: (1) the intercanopy heterogeneity index (yr), representing the ratio of tree crowns with different optical properties to the total number of trees; (2) the intracrown heterogeneity index (yi), denoting the ratio of elements with different optical properties within a single tree crown to the total number of elements. To evaluate the model performance in simulating different kinds of heterogeneous forest canopy spectra, 21 30m×30m sample plots in mixed forests and 50 10m×10m quadrats in pest-damaged forests were set up with individual tree measurements and remote sensing data acquirements. Control experiments based on the original SRT model and the three-dimensional model LESS were conducted for the two cases to compare simulation results with the extended ESRT model. Based on the framework of ESRT, sensitivity analyses were conducted to reveal the effect of mixing and pest levels on forest canopy spectra. 【Result】The results showed that compared to the original SRT model simulations, the canopy spectra simulated by the extended ESRT model have better consistency with the measured spectra from the sample plots for the cases of mixed forests (R2 = 0.77,RMSE = 0.075) and pest-damaged forests (R2 = 0.64, RMSE = 0.039), and the simulation accuracy is closer to that of a 3D computer model. The conifer-broadleaf ratio and the vertical distribution of damaged foliage can both affect the canopy spectral signals. In mixed forests, the canopy NDVI decreases with the decrease of forest coverage and with the increase of coniferous tree species proportion. Canopy coverage is the main factor affecting NDVI when the coverage is low, but the impact of mixing on NDVI becomes more apparent when the coverage is high. In pest-damaged forests, the sensitivity of BRF to yi varies significantly with damage types. BRF of the bottom damaged forest exhibits slight change at lower yi and then shows a sharp change toward the maximum of yi. On the contrary, BRF of the top damaged forest changes dramatically at lower yi but levels off at higher yi. 【Conclusion】The three-dimensional analytical model ESRT balances the simulation accuracy of three-dimensional structures with the simulation efficiency of classical analytical models, resolving the difficulty in accurately and efficiently simulating radiation transfer in the presence of heterogeneity. The computation time is suitable for large-scale heterogeneous forest canopies. The extended ESRT can simulate forests with mixed canopy types and heterogeneous leaf distribution structures within the canopy, potentially aiding forest managers in more accurately and effectively monitoring forest dynamic changes.

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