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摘要

引用本文:

DOI:

10.11834/jrs.20208329

收稿日期:

2018-08-10

修改日期:

2019-03-14

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应用随机辐射传输模型反演云南松林分郁闭度
李骁尧, 黄华国
北京林业大学林学院省部共建森林培育与保护教育部重点实验室
摘要:

随机辐射传输模型可用于模拟水平分布不均一森林的辐射传输过程。本文以云南松林分为研究对象,提出一种应用随机辐射传输模型的郁闭度反演方法。该方法以随机辐射传输模型中参数与林分郁闭度的定量关系为基础,提出了针对云南松的冠型等效模型,构建了郁闭度和卫星反射率(GF-1和Landsat-8卫星影像)的查找表,并实施了反演。基于野外实测的30个样地进行了郁闭度数据验证,并和基于NDVI回归模型的反演方法进行对比。结果表明,反演结果能够较准确反映云南松林分郁闭状况(R2=0.8345,RMSE=0.0688),通过冠型修正能够降低反演误差,冠型等效模型是合理的。反演方法机理清晰且适用范围广,研究成果可为大面积森林郁闭度反演提供模型和方法支持。

Retrieving canopy closure of Yunnan Pine forests by Stochastic Radiative Transfer Model
Abstract:

Remote sensing is one of most important methods to estimate forest canopy closure at large. There are mainly three kinds of remote sensing algorithms for canopy closure retrieval: statistical models, physical models and mixed models. Most practices used statistical models, which are lacking physical explanation and limited in local areas. The physical models are with clearer understanding on mechanism, which can be used in large areas. However, due to the higher complexity, physical models are less applied. The Stochastic Radiative Transfer (SRT) model is applicable in simulating forests with horizontally distributed heterogeneity, which may stand for different canopy closure. Exploring the inversion method using the SRT model would help to improve the efficiency and precision of canopy closure inversion. In this paper, based on the SRT model, an inversion method has been proposed on canopy closure retrieval of Yunnan Pine forests. The fundamental is the quantitative relationship between the canopy closure and the probability of finding foliage elements in SRT Model. To match the Yunnan Pine crown shape, an equivalent model was used to correct the cylinder shape assumption. Then, a look-up-table was constructed to inverse the canopy closure to reflectances from GF-1 and Landsat-8 satellite images. The probability of finding foliage elements and leaf area index are determined in the case of a minimum difference between simulated reflectances and satellite observations, in order to calculate the canopy closure based on the stochastic Beer–Lambert–Bouguer law. The 30 plots of field data were used to assess the inversion accuracy. A statistical inversion method based on NDVI is conducted for comparison. Results show that the inversion can accurately map canopy closure of Yunnan pine forests in the study area(R2=0.8345,RMSE=0.0688). Reflectance of the bands used for retrieval performs sensitivity to canopy closure. And using composite image from GF-1 and Landsat-8 is feasible. The equivalent shape correction model is reasonable which reduces the RMSE by 0.0466, and the algorithm is flexible in different crown cases. This study can provide supports on both forward models and inversion methods for large scale forest canopy closure retrieval. The research could be extended to any tree species by changing the model parameter input, and any crown type by crown shape equivalent correction.

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