| 基于DART模型森林结构参数反演 |
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| 引用本文： | 王强,刘丹丹,张为成.基于DART模型森林结构参数反演[J].黑龙江工程学院学报,2012(2):32-35. |
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| 作者姓名： | 王强 刘丹丹 张为成 |
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| 作者单位： | [1]黑龙江工程学院测绘工程学院,黑龙江哈尔滨150050 [2]哈尔滨工业大学电子与信息工程学院,黑龙江哈尔滨150001 |
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| 基金项目： | 黑龙江省教育厅骨干教师基金项目（1251G052）;黑龙江省青年基金项目（QC20L0017）;黑龙江省教育厅面上项目（F201234） |
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| 摘 要： | 为充分发挥多角度遥感技术在森林资源监测过程中的作用,首先需要认识遥感信号产生的机理,了解植被冠层辐射传输的过程,建立合适的数学模型进行定量描述,最终达到从遥感信号中提取植被信息的目的。利用CHRIS多角度遥感数据验证DART多角度物理模型,DART多角度物理模型确定影响双向反射率分布函数(BRDF)的不同敏感参数,根据试验区的特点设计并正演建立查找表,由平方差最小原则通过多角度遥感图像反演LAI。反演得到的LAI与样地实测数据比较分析,结果表明多角度遥感反演精度满足要求。
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| 关 键 词： | 多角度遥感 DART模型 叶面积指数 反演 |
Retrieval of conifer LAI based on the multiple-angle model |
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| WANG Qiang,LIU Dan-dan,ZHANG Wei-cheng.Retrieval of conifer LAI based on the multiple-angle model[J].Journal of Heilongjiang Institute of Technology,2012(2):32-35. |
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| Authors: | WANG Qiang LIU Dan-dan ZHANG Wei-cheng |
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| Affiliation: | 1. School of Surveying and Mapping Engineering, H eilongjiang Institute of Techonogy, Harbin 150050, China 2. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 15000I, China) |
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| Abstract: | In order to quantitatively and correctly estimate the parameters of forest from remote sensing measurements, it is important to thoroughly understand the interacting processes of electromagnetic radia- tion with foliage elements, and construct an appropriate mathematical model to describe such processes. The mathematical model was built for achieving the vegetation information from remote sensing signals. The paper test DART model using CHRIS data and ascertained the different sensitive parameters that af- fect Bidirectional Reflectance Distribution Function（BRDF） using DART model. The look-up table was constructed according with the characteristics of study area. The forest leaf area index（LAI） was inversed by method of least squares. The results show that the inversion acculate using multi-angle remote sensing is good and has the value for theoretical research and practical application. |
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| Keywords: | multi-angle remote sensing DART Model leaf area index inversion |
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