發(fā)布時間：2019-03-03 12:36

【摘要】：隨著科學技術的發(fā)展,激光產品已成為人們觀察客觀世界的”眼睛”和”神經(jīng)”。目前激光雷達遙感技術在數(shù)字化信息獲取方面有著重要的地位,激光雷達離散點云數(shù)據(jù)具有三維坐標信息,對于地物研究能表達其在空間中的細節(jié)信息,因而在許多領域有著廣泛的應用。 樹冠結構是林木進行光合作用等生態(tài)學過程不可或缺的重要組成部分,研究樹冠的空間結構有著重要的意義。不同樹種或同一樹種之間樹冠的空間結構分布因外界因素和本身特性的影響會存在一定的差異性,這種差異性就是空間異質性。分析空間差異性的方法很多,因樹木一般具有分形特征,最初使用的是分形維數(shù)法,但由于分形理論的始祖Mandelbrot發(fā)現(xiàn)分形維數(shù)相同的對象間,空間結構表現(xiàn)形式會存在明顯的差異性,僅用分形維數(shù)這一指標不足以描述空間分布的差異性,因此需要其它指標(如空隙度指數(shù))來區(qū)分不同物體。由于林冠的重要性,國內外學者進行了大量的研究,關于林冠方面的研究成果越來越多,但至今仍沒有一個利用激光雷達點云數(shù)據(jù)優(yōu)勢研究樹冠三維空間結構的相關報道,大多數(shù)研究都是基于光學影像或研究區(qū)的某片林分提出的。在上述背景下,文章介紹了空隙度指數(shù)的定義和三維滑動盒算法。同時,以激光雷達點云數(shù)據(jù)為數(shù)據(jù)源,提出了一種基于體素和三維凸包的空隙度指數(shù)的改進方法。本文主要對單個樹冠空隙度指數(shù)的算法及其在林業(yè)研究中的應用進行了初步的研究和改進。研究所開展的工作有： (1)對國內外近些年來樹冠結構的研究現(xiàn)狀進行了全面的綜述,并分析了不同數(shù)據(jù)源和方法的主要應用領域和存在的主要問題； (2)詳細介紹了激光雷達點云數(shù)據(jù)的基本形式和優(yōu)缺點,以及作為本文研究樹冠結構數(shù)據(jù)源的優(yōu)勢； (3)詳細闡述了空隙度指數(shù)的基本定義和原始的計算方法,并在其基礎上做了改進。同時,用改進的方法計算點云樹冠的三維空隙度指數(shù),繼而根據(jù)實驗果分析了該方法的有效性； (4)利用三維形狀方法分別檢測實驗中各點云樹冠的三維形狀,判斷樹冠間的形狀表面差異性,從而與本文中提出的空隙度指數(shù)分析法進行比較； (5)闡述了空隙度指數(shù)在樹冠空間異質性分析研究中的作用,并對其應用范圍和前景作了展望。 文中利用實測的樹冠點云數(shù)據(jù)檢驗了改進算法應用在樹冠空間結構上的有效性。實驗結果表明,激光雷達離散點云數(shù)據(jù)作為研究樹冠三維空間結構分布的數(shù)據(jù)源是有效的,為研究不同樹種樹冠的空間分布異同與生態(tài)變化過程在森林經(jīng)理方面的研究提供數(shù)據(jù)支持,同時提供了一種區(qū)分不同樹種的新方法。
[Abstract]:With the development of science and technology, laser products have become "eyes" and "nerves" to observe the objective world. At present, lidar remote sensing technology plays an important role in digital information acquisition. Lidar discrete point cloud data has three-dimensional coordinate information, and it can express the detailed information in space for the research of ground objects. Therefore, it has a wide range of applications in many fields. Canopy structure is an indispensable part of forest photosynthesis and other ecological processes. It is of great significance to study the spatial structure of tree crown. The spatial distribution of canopy between different tree species or the same tree species will be different due to the influence of external factors and its own characteristics, and this difference is spatial heterogeneity. There are many methods to analyze spatial differences, because trees generally have fractal characteristics, and the fractal dimension method was used at first, but because Mandelbrot, the ancestor of fractal theory, found that the fractal dimension is the same among objects. There are obvious differences in the representation of spatial structure. The fractal dimension is not enough to describe the difference of spatial distribution, so other indexes (such as void index) are needed to distinguish different objects. Because of the importance of canopy, scholars at home and abroad have done a lot of research, and more research results have been made on canopy, but there is still no relevant report to study 3D spatial structure of tree crown by using the advantage of point cloud data of lidar. Most of the studies are based on optical images or a stand in the study area. Under the above background, the definition of void index and the algorithm of three-dimensional sliding box are introduced in this paper. At the same time, an improved method of voidage index based on voxel and 3-D convex hull is proposed based on lidar point cloud data. This paper mainly studies and improves the algorithm of single tree crown void index and its application in forestry research. The research work is as follows: (1) the research status of crown structure at home and abroad in recent years is comprehensively reviewed, and the main application fields and main problems of different data sources and methods are analyzed; (2) the basic forms, advantages and disadvantages of Lidar point cloud data are introduced in detail, and the advantages of Lidar point cloud data as the data source of tree crown structure are introduced in detail. (3) the basic definition of void index and the original calculation method are described in detail, and the improvement is made on the basis of it. At the same time, the improved method is used to calculate the three-dimensional void index of the crown of point cloud, and then the validity of the method is analyzed according to the experimental results. (4) using the three-dimensional shape method to detect the three-dimensional shape of the crown of each point cloud in the experiment, and to judge the difference of the shape surface between the crowns, so as to compare it with the void index analysis method proposed in this paper. (5) the role of void index in spatial heterogeneity analysis of tree crown is expounded, and its application scope and prospect are prospected. In this paper, the validity of the improved algorithm in tree crown spatial structure is verified by using the measured tree crown point cloud data. The experimental results show that the Lidar discrete point cloud data can be used as a data source to study the three-dimensional spatial distribution of tree crown. This paper provides data support for the study of spatial distribution and ecological change process of different tree species in forest management, and provides a new method to distinguish different tree species.
【學位授予單位】：昆明理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN958.98

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