| 基于GIS与RS的大理河流域植被格局分形维数时空变化特征 |
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| 引用本文： | 李斌斌,李占斌,李鹏.基于GIS与RS的大理河流域植被格局分形维数时空变化特征[J].农业工程学报,2015,31(12):173-178. |
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| 作者姓名： | 李斌斌 李占斌 李鹏 |
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| 作者单位： | 1. 西安理工大学西北水资源与环境生态教育部重点实验室,西安 710048; 2. 北京水保生态工程咨询有限公司,北京 100055;,1. 西安理工大学西北水资源与环境生态教育部重点实验室,西安 710048; 3. 中国科学院水利部水土保持研究所土壤侵蚀与旱地农业国家重点实验室,杨凌 712100;,1. 西安理工大学西北水资源与环境生态教育部重点实验室,西安 710048; |
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| 基金项目： | 国家自然科学基金"黄土高原生态建设的生态-水文过程响应机理研究"（41330858）;国家自然科学基金"基于能量过程的坡沟系统侵蚀产沙过程调控与模拟"（41471226）;水利部公益性行业科研专项经费项目（201201084） |
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| 摘 要： | 为掌握大理河流域植被格局时间和空间分布特征,构建了基于分形布朗运动理论的流域植被格局量化模型。该文利用自1990年至2006年共计5期TM/ETM影像为基础信息源,在ARCGIS平台下计算得到大理河流域各时相的像元归一化植被指数(normalized difference vegetation index,NDVI),建立了流域像元尺度的栅格结构数字植被模型(digital vegetation model,DVM),并逐个计算得到各子流域植被格局分形维数。结果显示分形维数都大于2.5,介于2.7311~2.8499之间,各下一级子流域植被覆盖分形维数的大小都没有超过其所在的更大流域的分形维数。植被格局分形维数(fractional brownian motion,FBM)从下游到上游随着离出口点距离的增大而逐渐变小,植被格局自下游到上游逐渐趋于破碎复杂。各子流域从1990年至2006年植被格局分形维数基本随着时间的变化呈现了先减小后增大的趋势。该文建立的流域植被格局分形量化模型在综合量化流域植被格局破碎程度等方面具有一定的优越性。
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| 关 键 词： | 植被 遥感 模型 大理河 分形维数 时空变化 植被覆盖 |
| 收稿时间： | 2015/3/24 0:00:00 |
| 修稿时间： | 6/4/2015 12:00:00 AM |
Spatial and temporal variation characteristics of vegetation cover fractal dimension in Dali River watershed based on GIS and RS |
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| Li Binbin,Li Zhanbin and Li Peng.Spatial and temporal variation characteristics of vegetation cover fractal dimension in Dali River watershed based on GIS and RS[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(12):173-178. |
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| Authors: | Li Binbin Li Zhanbin and Li Peng |
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| Institution: | 1. Key Lab of Northwest Water Resources and Environment Ecology of MOE at XAUT, Xi'an University of Technology, Xi'an 710048, China;2. Beijing Soil Conservation and Ecology Engineering Consulting Company limited, Beijing 100055,1. Key Lab of Northwest Water Resources and Environment Ecology of MOE at XAUT, Xi'an University of Technology, Xi'an 710048, China;3. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China and 1. Key Lab of Northwest Water Resources and Environment Ecology of MOE at XAUT, Xi'an University of Technology, Xi'an 710048, China |
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| Abstract: | Abstract: Based on the spatial distribution model of NDVI (normalized difference vegetation index) value which is extracted from remote sensing image, spatial distribution features of the watershed surface NDVI value can be understood to be composed of a large number of equal units, and the side length of the units is equal to the size of the remote sensing image pixels. NDVI value is stored in each unit of attribute sheet "VALUE". In this paper, we realize the measurement of NDVI increment at every point on the watershed by the development of GIS algorithm and the establishment of the moving window in the research process. The moving window statistical method divides the whole watershed into a number of equal DVM (digital vegetation model) cells (r×r, r is an odd multiple of the pixel size, r>1). Each cell is called a "window" and the cells don't have overlap for each other. We computerize the difference of NDVI values between each pixel point and the center pixel point in each cell. We calculate NDVI increment value of the watershed points at a certain spatial scale by the moving window statistical method, then computerize mathematics expectations of measure collection, which is composed of all NDVI incremental values. To study the characteristics of fractal dimension of the vegetation cover and its variation at different scales, it is divided into 4 scales according to the area of the basin, with 5 phases per level. The first level is the entire Dali River basin with an area of 3 906 km2, approximately 5 million times of pixel size (30 m × 30 m). At the second stage, Dali River basin will be divided into 3 parts i.e. upstream, midstream and downstream, with an average area of approximately 1 000 km2, approximately 1 million times of pixel size (30 m × 30 m). At the third stage, it will be divided into 14 small basins of Dali River, with an area of 179.4-392.5 km2, about 200 thousand times of pixel size (30 m × 30 m). At the fourth stage, it will be divided into 53 small basins of Dali River (No.1 to 53), with an area of 21.9-108.9 km2, about 40 thousand times of pixel size (30 m × 30 m). Firstly, on the basis of information source from 5 issues of TM/ETM images from 1990 to 2006, the image data are processed, the vegetation information at basin stage is extracted by the platform of geographic information system (GIS), and then watershed DVM is established. FBM (fractional brownian motion) fractal dimension for watershed vegetation cover is between 2.7311 and 2.8499. By calculation and analysis, vegetation cover FBM fractal dimension is increasing from upstream to downstream, so vegetation distribution is more uniform from upstream to downstream. Vegetation cover fractal dimension is increasing with the watershed area. Through analyzing spatial and temporal variation of each sub-watershed at all levels, it presents the curvilinear trend of decreasing firstly and then increasing as the change of time from 1990 to 2006; at the same time, the vegetation coverage fractal dimension of each sub-watershed at all levels is no more than its bigger sub-watershed. |
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| Keywords: | vegetation remote sensing models Dali river fractal dimension spatial and temporal variation vegetation cover fractional brownian motion |
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