基于植被格局分形特征的流域水土流失响应及其应用研究

发布时间：2018-06-01 12:11

本文选题：植被格局 + 分形维数　；参考：《西安理工大学》2016年博士论文

【摘要】：本文应用多学科交叉理论知识,结合GIS和RS技术,以陕北黄土高原大理河流域为对象,研究了植被分布格局的分形维数与水土流失的关系。构建了基于NDVI植被指数的大理河流域植被格局布朗运动分形维数计算模型,阐明了大理河流域NDVI植被指数的空间分布特征,揭示了大理河流域不同空间尺度的植被格局FBM分形维数年际变化、空间分布、垂直分布特征及其变化规律,构建了基于灰色关联分析的大理河流域侵蚀产沙量模型,对比研究了植被格局FBM分形维数与NDVI植被指数在综合量化流域植被参数方面的优劣,分析了植被格局分形维数与土壤侵蚀强度之间的相关系,提出了大理河流域的水土保持重点治理小流域及其治理对策,并将植被格局FBM分形维数应用于西气东输二线工程水土保持动态监测。本论文取得的主要创新性成果如下:(1)阐明了大理河流域NDVI的时空变化特征。大理河流域的NDVI值为0.221;大理河流域从上游到下游NDVI值递增,分别为0.193、0.214和0.259,说明大理河流域上游的植被覆盖度较低,下游植被覆盖度相较高。大理河流域14个面积在179.4～392.5km2之间的小流域的NDVI值在0.155～0.268之间;大理河流域53个面积在21.9～208.9km2之间的小流域的NDVI值在0.133～0.287之间。各子流域的像元NDVI值在0.1～0.3之间的像元面积占流域总面积的比例在59～90%之间,所占比例相对比较固定。NDVI植被指数值的大小由大于0.3和小于0.1的像元数所占百分比的多少来决定的。NDVI植被指数随着小于0.1的像元所占比例的增加呈现递减趋势,NDVI植被指数随着大于0.3的像元所占百分比的增加而递增的趋势。(2)揭示了大理河流域植被格局FBM分形维数的时空变化规律。2006年大理河整个流域的植被格局FBM分形维数为2.817,大理河流域上游、中游和下游的植被格局FBM分形维数分别为2.810、2.814、2.816;植被格局FBM分形维数随着子流域面积尺度的增大而增大,当子流域的流域面积达到一定值后,植被格局FBM分形维数无限接近于整个流域的植被格局FBM分形维数,说明植被格局分形维数具有尺度效应。大理河流域1990～2006年期间植被格局FBM分形维数介于2.695～2.850之间,并对大理河各子流域时间、空间、垂直变化特征进行了研究。(3)不同NDVI值的像元数增大幅度随着流域面积的增大而减少,随着面积的增加,单位面积ND VI值的像元数在减少。单位面积上不同ND VI值的像元数与植被格局FBM分形维数之间表现递减的趋势,两者的相关系数为-0.663(p0.01)。研究了大理河流域的植被覆盖特征和植被景观格局的时空变化特征,分析了近年来大理河流域植被动态变化规律。(4)植被分布格局(FBM)研究了植被格局FBM分形维数与海拔高程之间的关系,结果表明,植被格局FBM分形维数值随着海拔高度的增加呈现减小趋势,低海拔区域植被格局分形维数最大2.847,其次为中低海拔2.833、中高海拔2.826,而高海拔区域最小2.809。(5)植被格局FBM分形维数优于NDVI植被指数反映植被特征,可以更好反映植被覆盖与水土流失之间的关系。根据大理河曹坪站、青阳岔站和李家河站的38场汛期次暴雨洪水径流泥沙实测资料,以降雨侵蚀因子(即径流侵蚀功率)、地形地貌因子(即地貌特征FBM分形维数)、植被覆盖因子(NDVI植被指数)或植被格局因子(即植被格局分形维数)作为主要影响因子,采用数理统计法建立了大理河流域侵蚀产沙量多元线性回归模型,结果表明以植被格局FBM分形维数作为地表植被覆盖量化因子的流域侵蚀产沙量多元线性回归模型的模拟精度较高;灰色关联分析结果表明,与流域NDVI植被指数相比,植被格局 FBM分形维数更能全面准确地反映下垫面植被特征与流域水土流失之间的关系。(6)阐明了大理河流域及其各级子流域的土壤侵蚀强度和流域地形因子(包括沟壑密度、坡度和地形起伏度)的空间分布特征;采用偏相关分析法计算得到土壤侵蚀强度与植被格局FBM分形维数之间的相关系数为-0.712,两者呈负相关关系;利用灰色关联分析法计算得到坡度、沟壑密度、起伏度和植被格局FBM分形维数与土壤侵蚀强度之间的关联度分别为0.702、0.701、0.705和0.706。利用SPSS统计分析软件构建了以植被格局分形维数、坡度、沟壑密度、地形起伏度为参数的土壤侵蚀强度多元线性回归模型;采用聚类分析法将大理河流域的53个小流域划分为一般治理小流域和重点治理小流域2大类,并提出了大理河流域24个重点治理小流域的初步水土保持治理对策。(7)将植被分布格局FBM分形维数应用于西气东输二线的水土流失监测之中。以西气东输二线工程三个水土保持监测重点地段的遥感影像资料为基础信息源,计算得到管线工程施工工前、后三个水土保持监测重点地段的NDVI植被指数和植被格局FBM分形维数,并通过数据对比分析,阐明了水土保持监测重点地段管线施工前、后植被格局动态变化特征;在对比分析了卫星遥感影像和无人机高分航拍影像优缺点的基础上,以无人机高分航拍影像为基础信息源,计算得到西气东输二线工程典型弃渣场和管线作业带水土保持治理前、后的NDVI植被指数和植被格局FBM分形维数。
[Abstract]:In this paper, the relationship between the fractal dimension of the vegetation distribution pattern and the soil erosion in the Dali River Basin in the Loess Plateau of Northern Shaanxi Province is studied with GIS and RS technology. The fractal dimension calculation model of the Brown movement of the vegetation pattern in the Dali River Basin Based on the NDVI vegetation index is constructed, and the NDV of the Dali river basin is clarified. The spatial distribution characteristics of I vegetation index revealed the interannual variation, spatial distribution, vertical distribution and variation of the fractal dimension of vegetation pattern FBM in different spatial scales of the Dali River Basin, and constructed the erosion and sediment yield model of the Dali River Basin Based on grey correlation analysis, and compared the fractal dimension of the vegetation pattern and the NDVI vegetation of the vegetation pattern FBM. The index is good and bad in quantifying the vegetation parameters of the basin. The correlation line between the fractal dimension of the vegetation pattern and the soil erosion intensity is analyzed. The key watershed and the Countermeasures of soil and water conservation in the Dali River Basin are put forward, and the fractal dimension of the vegetation pattern FBM is applied to the dynamic monitoring of soil and water conservation in the second line project of the west east gas transmission line. The main innovative achievements of this paper are as follows: (1) the spatial and temporal variation characteristics of NDVI in the Dali River Basin were clarified. The NDVI value of the Dali River Basin was 0.221, and the NDVI value of the Dali River Basin increased from upstream to downstream, respectively, 0.193,0.214 and 0.259, indicating that the vegetation coverage of the upper reaches of the Dali River Basin was lower and the lower vegetation coverage in the lower reaches of the Dali river. The NDVI value of 14 small basins with 14 areas between 179.4 and 392.5km2 in the river basin is between 0.155 and 0.268, and the NDVI value of 53 small basins in the Dali river basin between 21.9 and 208.9km2 is 0.133 to 0.287. The pixel area of the pixel area of each sub basin is between 0.1 and 0.3 and the proportion of the total area of the flow domain is between 59 and 90%. The.NDVI vegetation index, which is determined by the ratio of the ratio of the ratio of the.NDVI vegetation index to the number of pixels larger than 0.3 and less than 0.1, decreases with the increase of the percentage less than 0.1, and the NDVI vegetation index increases with the increase of the percentage of pixels larger than 0.3. (2) revealed The spatial and temporal variation of the fractal dimension of the vegetation pattern FBM in the Dali River Basin.2006, the fractal dimension of the vegetation pattern of the whole Dali river basin is 2.817, the upper reaches of the Dali River Basin, the vegetation pattern of the middle and lower reaches of the Dali River Basin are 2.810,2.814,2.816, and the fractal dimension of the vegetation pattern FBM increases with the increase of the size of the sub basin area. When the area of the basin reaches a certain value, the fractal dimension of the vegetation pattern FBM is infinitely close to the FBM fractal dimension of the vegetation pattern in the whole basin, indicating that the fractal dimension of the vegetation pattern has a scale effect. The fractal dimension of the vegetation pattern of the vegetation pattern of the Dali River Basin is between 2.695 and 2.850 during the 1990~2006 years of the Dali River Basin, and it has also been used in the sub basins of the Dali river. The characteristics of time, space and vertical change are studied. (3) the number of pixel numbers of different NDVI values decreases with the increase of the area of the basin. As the area increases, the number of pixels per unit area ND VI value decreases. The number of pixels with different ND VI values on the unit area and the FBM fractal dimension of the vegetation grid decreases. The correlation coefficient is -0.663 (P0.01). The characteristics of vegetation cover and the temporal and spatial variation of vegetation landscape pattern in the Dali River Basin are studied. The dynamic changes of vegetation in the Dali River Basin in recent years are analyzed. (4) the relationship between the vegetation pattern (FBM) and the relationship between the fractal dimension of the vegetation pattern FBM and the elevation is studied. The results show that the vegetation pattern is divided into FBM points. The fractal dimension of shape dimension decreases with the increase of altitude. The fractal dimension of vegetation pattern in low altitude region is 2.847, followed by middle and low altitude 2.833, middle and high elevation 2.826, and the minimum 2.809. (5) vegetation pattern FBM fractal dimension of high altitude region is better than NDVI vegetation index reflecting vegetation characteristics, which can better reflect vegetation cover and soil and water flow. According to the measured data of runoff and sediment in 38 flood season rainstorm floods in the Dali River Cao Ping Station, Qingyang fork station and Li Jia He Railway Station, the rainfall erosion factor (i.e., runoff erosion power), topographic and geomorphic factors (the FBM fractal dimension of geomorphic characteristics), vegetation cover factor (NDVI vegetation index) or vegetation pattern factor (vegetation pattern division) As the main influencing factor, the multivariate linear regression model of erosion and sediment yield in the Dali River Basin was established by mathematical statistics. The results showed that the simulation accuracy of the multiple linear regression model of the erosion and sediment yield of the basin erosion by the fractal dimension of the vegetation pattern FBM as the quantitative factor of the surface vegetation coverage was higher. The grey correlation analysis results showed that the model was more accurate. Compared with the NDVI vegetation index of the basin, the fractal dimension of the vegetation pattern FBM can reflect the relationship between the vegetation characteristics of the underlying surface and the soil erosion in the basin. (6) the spatial distribution of soil erosion intensity and topographic factors (including gully density, slope and topographic undulation) in the Dali River Basin and its subbasins at all levels are clarified. The correlation coefficient between soil erosion intensity and the fractal dimension of vegetation pattern FBM was calculated by partial correlation analysis (-0.712), and the correlation of slope, ravine density, undulation and vegetation pattern FBM fractal dimension with soil erosion intensity was 0.702,0.7, respectively, with the grey correlation analysis method. 01,0.705 and 0.706. use SPSS statistical analysis software to construct a multi linear regression model of soil erosion intensity based on fractal dimension of vegetation pattern, slope, ravine density and terrain undulation, and divide 53 small basins in Dali river basin into 2 categories: general watershed and key watershed. The Countermeasures of soil and water conservation in the 24 key watershed of Dali River Basin are introduced. (7) the fractal dimension of the vegetation distribution pattern FBM is applied to the soil erosion monitoring of the second line of the west to east gas transmission line. The remote sensing image data of three key areas of soil and water conservation monitoring in the second line of the west east gas transmission line project are the basic information sources, and the pipeline engineering is calculated. Before the construction, the NDVI vegetation index and the fractal dimension of the vegetation pattern FBM in the key area of the three soil and water conservation areas were monitored, and the dynamic changes of the post vegetation pattern before the pipeline construction in the key areas of soil and water conservation monitoring were clarified, and the advantages and disadvantages of the satellite remote sensing images and the UAV aerial photograph images were compared and analyzed. On the basis of this, the NDVI vegetation index and the FBM fractal dimension of the vegetation pattern were calculated before the soil and water conservation of the typical waste field and pipeline operation zone of the second line of west east gas transmission project.
【学位授予单位】：西安理工大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：S157

【相似文献】