【摘要】：隨著科學(xué)技術(shù)的發(fā)展,激光產(chǎn)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(dá)遙感技術(shù)在數(shù)字化信息獲取方面有著重要的地位,激光雷達(dá)離散點(diǎn)云數(shù)據(jù)具有三維坐標(biāo)信息,對(duì)于地物研究能表達(dá)其在空間中的細(xì)節(jié)信息,因而在許多領(lǐng)域有著廣泛的應(yīng)用。 樹(shù)冠結(jié)構(gòu)是林木進(jìn)行光合作用等生態(tài)學(xué)過(guò)程不可或缺的重要組成部分,研究樹(shù)冠的空間結(jié)構(gòu)有著重要的意義。不同樹(shù)種或同一樹(shù)種之間樹(shù)冠的空間結(jié)構(gòu)分布因外界因素和本身特性的影響會(huì)存在一定的差異性,這種差異性就是空間異質(zhì)性。分析空間差異性的方法很多,因樹(shù)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(duì)象間,空間結(jié)構(gòu)表現(xiàn)形式會(huì)存在明顯的差異性,僅用分形維數(shù)這一指標(biāo)不足以描述空間分布的差異性,因此需要其它指標(biāo)(如空隙度指數(shù))來(lái)區(qū)分不同物體。由于林冠的重要性,國(guó)內(nèi)外學(xué)者進(jìn)行了大量的研究,關(guān)于林冠方面的研究成果越來(lái)越多,但至今仍沒(méi)有一個(gè)利用激光雷達(dá)點(diǎn)云數(shù)據(jù)優(yōu)勢(shì)研究樹(shù)冠三維空間結(jié)構(gòu)的相關(guān)報(bào)道,大多數(shù)研究都是基于光學(xué)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(dòng)盒算法。同時(shí),以激光雷達(dá)點(diǎn)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(jìn)方法。本文主要對(duì)單個(gè)樹(shù)冠空隙度指數(shù)的算法及其在林業(yè)研究中的應(yīng)用進(jìn)行了初步的研究和改進(jìn)。研究所開(kāi)展的工作有： (1)對(duì)國(guó)內(nèi)外近些年來(lái)樹(shù)冠結(jié)構(gòu)的研究現(xiàn)狀進(jìn)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(yīng)用領(lǐng)域和存在的主要問(wèn)題； (2)詳細(xì)介紹了激光雷達(dá)點(diǎn)云數(shù)據(jù)的基本形式和優(yōu)缺點(diǎn),以及作為本文研究樹(shù)冠結(jié)構(gòu)數(shù)據(jù)源的優(yōu)勢(shì)； (3)詳細(xì)闡述了空隙度指數(shù)的基本定義和原始的計(jì)算方法,并在其基礎(chǔ)上做了改進(jìn)。同時(shí),用改進(jìn)的方法計(jì)算點(diǎn)云樹(shù)冠的三維空隙度指數(shù),繼而根據(jù)實(shí)驗(yàn)果分析了該方法的有效性； (4)利用三維形狀方法分別檢測(cè)實(shí)驗(yàn)中各點(diǎn)云樹(shù)冠的三維形狀,判斷樹(shù)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(jìn)行比較； (5)闡述了空隙度指數(shù)在樹(shù)冠空間異質(zhì)性分析研究中的作用,并對(duì)其應(yīng)用范圍和前景作了展望。 文中利用實(shí)測(cè)的樹(shù)冠點(diǎn)云數(shù)據(jù)檢驗(yàn)了改進(jìn)算法應(yīng)用在樹(shù)冠空間結(jié)構(gòu)上的有效性。實(shí)驗(yàn)結(jié)果表明,激光雷達(dá)離散點(diǎn)云數(shù)據(jù)作為研究樹(shù)冠三維空間結(jié)構(gòu)分布的數(shù)據(jù)源是有效的,為研究不同樹(shù)種樹(shù)冠的空間分布異同與生態(tài)變化過(guò)程在森林經(jīng)理方面的研究提供數(shù)據(jù)支持,同時(shí)提供了一種區(qū)分不同樹(shù)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(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN958.98

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