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### 基于植被动态的黄土高原生态地理分区

1. 北京大学城市与环境学院,地表过程分析与模拟教育部重点实验室,北京 100871
• 收稿日期:2015-04-01 修回日期:2015-07-08 出版日期:2015-09-15 发布日期:2015-09-15
• 作者简介:

作者简介：张甜（1991- ）,女,陕西汉中人,硕士,研究方向为综合自然地理与景观生态。E-mail: zhangtiangis@163.com

• 基金资助:
国家自然科学基金优秀青年科学基金项目（41322004）

### Eco-geographical regionalization in Loess Plateau based on the dynamic consistency of vegetation

Tian ZHANG(), Jian PENG(), Yanxu LIU, Mingyue ZHAO

1. Laboratory for Earth Surface Process, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
• Received:2015-04-01 Revised:2015-07-08 Online:2015-09-15 Published:2015-09-15

Abstract:

As a new branch of natural regionalization, eco-geographical regionalization is a core study subject of geography and ecology in recent years, and it has been widely concerned by scholars at home and abroad, which plays a very important role in understanding the geographical differentiation, social production and regional planning activities. However, the traditional researches on eco-geographical regionalization were mostly based on the three-level deduction method from top to bottom. Moreover, the existing researches of eco-geographical regionalization did not focus much on the optimization method on multi- regionalization. Meanwhile, the Loess Plateau in China was widely known as the typical ecological fragile zone, where the growth and restoration of vegetation are closely related with the mitigation of local ecological dilemma, therefore, it would be helpful to have a deeper recognition on the eco-environment of the Loess Plateau and its spatial distribution if we consider the condition of vegetation restoration as an important index to evaluate the rationality of regionalization. This paper selected the annual average temperature of January and July, the number of days with the temperature >10oC, annual precipitation, annual average solar radiation, the drought index, NDVI, DEM and vegetation coverage as the ecological indicators, and used a method based on self-organizing mapping neural network (SOFM) to evaluate the bioclimatic regionalization in the Loess Plateau. Then we discussed the spatial distribution of the chosen indicators based on the GIS spatial analysis and mapping function. In this paper, we compared the 12 types of regionalization in the Loess Plateau and chose the best one to reflect the vegetation restoration during 29 years in the study area based on the dynamic consistency of vegetation and the two-type screening method. Eventually, we found it more reasonable to divide the Loess Plateau into six parts, and each part could fundamentally fit the actual ecological condition and the spatial characteristics of the study area. At the same time, vegetation shows a similar growth trend in each part and the coefficient of the final regionalization scheme of variation index of the annual average NPP is the lowest, which means the aggregation degree of elements is the strongest inside the region. The regionalization scheme of this study has a good consistency with the existing regionalization scheme, and it is clearer than the existing ones because of the different regionalization scales. Therefore, this paper explored the multi-program optimization method in the eco-geographical regionalization, and enhanced the objectivity of the bottom-up eco-geographical regionalization.