哈萨克斯坦土地利用景观格局演变及驱动因素分析

发布时间：2018-11-20 19:56

【摘要】：土地利用是地球表层系统最突出的景观标志,景观格局是一定地域内各种自然环境因素与社会经济因素共同作用的产物,研究其演变发展特征可以了解景观格局的形成、作用机制。通过对景观格局的时空动态分析以及深入剖析景观格局演变背后的驱动因素,可以客观反映生态环境变化状况,协调人类活动,并为实现生态环境良性发展提供依据。中亚地区由于生态环境恶化严重,且存在土地利用类型复杂,对环境变化敏感程度高,景观差异性大等特征,已逐渐成为全球土地利用及景观格局研究的重要区域之一。论文首先对有关土地利用、景观格局的国内外相关研究进行综述,如土地利用分类及其动态监测研究,景观格局演变的定量化、时空特征、尺度效应、驱动机制等研究。在总结现有土地利用景观格局演变分析方法的基础上,提出了本文的研究内容及技术路线。本文利用哈萨克斯坦1990年,2000年,2010年的土地利用数据分析了近20年该国土地利用变化状况。通过将哈萨克斯坦地区均等划分为100km×100km大小的网格区域,同时计算每个网格的景观格局指数,以定量分析哈萨克斯坦内部景观格局的分布特征,把握景观格局演变规律。同时,构建自然驱动因素、人文驱动因素两个方面的环境因子,采用多元线性回归分析法,对景观格局变化的驱动因素进行分析。研究表明哈萨克斯坦景观整体呈现破碎度降低、空间集聚性加强,斑块平均面积明显增大的趋势。同时,面积加权平均形状指数的变化体现了人类活动对景观斑块的作用力。多样性指数和均匀度指数的变动体现了哈萨克斯坦景观格局在研究期间由于各类因素,特别是人类活动的作用使景观类型的分布偏于单一化,且越来越不均衡,出现了少数优势景观的支配作用越来越强的现象。通过对各类景观格局演变驱动因素的多元回归建模分析可以看出,人工景观受地表含水量、人口密度、地形起伏等驱动要素的作用较大。草地、水域等自然景观受自然驱动因素的作用较大。多样性指数、均匀度指数受人口密度、人均gdp等驱动要素的作用较大。蔓延度指数、散布与并列系数受地表温度、地表含水量、地形起伏度等驱动要素的作用较大。
[Abstract]:Land use is the most prominent landscape sign of the earth's surface system, and landscape pattern is the product of the interaction of various natural environment factors and social and economic factors in a certain region. The formation of landscape pattern can be understood by studying the evolution and development characteristics of the landscape pattern. Mechanism of action By analyzing the spatial and temporal dynamics of the landscape pattern and the driving factors behind the evolution of the landscape pattern, we can objectively reflect the changing situation of the ecological environment, coordinate human activities, and provide the basis for the realization of the benign development of the ecological environment. Due to the serious deterioration of ecological environment, the existence of complex land use types, high sensitivity to environmental change and great landscape diversity, Central Asia has gradually become one of the important regions in the study of global land use and landscape pattern. Firstly, this paper summarizes the related researches on land use and landscape pattern at home and abroad, such as land use classification and its dynamic monitoring, quantification of landscape pattern evolution, space-time characteristics, scale effect, driving mechanism and so on. On the basis of summarizing the existing analysis methods of landscape pattern evolution of land use, the research content and technical route of this paper are put forward. In this paper, the land use data of Kazakhstan in 1990, 2000 and 2010 are used to analyze the land use change in recent 20 years. By dividing Kazakhstan equally into grid areas of 100km 脳 100km size and calculating the landscape pattern index of each grid, the distribution characteristics of landscape pattern in Kazakhstan were quantitatively analyzed and the evolution law of landscape pattern was grasped. At the same time, the environmental factors of natural driving factor and humanistic driving factor are constructed, and the driving factors of landscape pattern change are analyzed by using multiple linear regression analysis method. The results showed that the whole landscape of Kazakhstan showed a tendency of decreasing fragmentation, strengthening spatial agglomeration and increasing the average area of patches. At the same time, the change of area-weighted average shape index reflects the force of human activity on landscape patches. The changes in the diversity index and the evenness index reflect the fact that the distribution of landscape patterns in Kazakhstan has become more and more uniform and uneven during the period under study due to various factors, in particular the role of human activities, There is a small number of dominant landscape dominance more and more strong phenomenon. Through the multiple regression modeling analysis of the driving factors of landscape pattern evolution, it can be seen that artificial landscape is influenced by surface water content, population density, terrain fluctuation and other driving factors. Grassland, water and other natural landscape by the role of natural driving factors. Diversity index and evenness index are influenced by population density and gdp per capita. The diffusivity index, dispersion and parallel coefficient are greatly influenced by surface temperature, surface water content, topographic fluctuation and so on.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TU984

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