1984-2008年北京湿地景观格局驱动机制(英文)

The landscape pattern of Beijing wetlands has undergone a significant change as a result of natural and artificial elements.Supported by remote sensing and GIS technology,using multi-temporal TM images from 1984 to 2008 in Beijing,this paper analyzed the dynamic characteristics of wetlands landscape pattern through selected typical indices including patch area,patch average area,fractal dimension index,diversity,dominance,contagion indices and the spatial centroids of each wetlands type were calculated.Finally,the paper explored the evolution mode and driving factors of wetland landscape pattern.The results were obtained as follows:the total wetland area increased during the period 1984-1996,then decline from 1996 to 2004.The wetland area in 1994 accounted for only 47.37% of that in 2004.The proportion of artificial wetland area was larger than that of natural wetland.The proportion of reservoir wetland was 33.50% to 53.73% and had the maximum average area.pond and paddy field wetland type with the least average area accounted for 16.46% to 45.09% of the total wetland area.The driving forces of the natural river wetland were mainly natural elements;its fractal dimension index was greater than the others.The Shannon diversity index of wetland landscape increased from 1.11 in 1992 to 1.34 in 2004,indicating that the difference between proportions of each wetland type decreased and areas of each wetland type were evenly distributed.The contagion index went down from 65.59 to 58.41,indicating that the connectivity degraded.Miyun Reservoir had the largest area and its area change had a great impact on the location of the centroid.Wetland resources degenerated gradually from the joint effects of natural and artificial factors.During the period 2006-2008,the precipitation increased and the drought condition was relieved.The government implemented series of positive policies to save water resources,and the wetland area increased.     

基于航片的北京市城市绿地信息快速提取

城市绿地信息对城市绿地规划及生态城市建设具有重要意义。而遥感技术能综合反映地表真实状况,为大范围城市绿地信息的快速获取提供有力途径。本文主要研究了遥感在城市绿化资源调查中的应用,基于0.5米分辨率的航空影像,提出了一种城市绿地信息的快速提取方法,并以北京市为例,进行了北京市绿地信息的快速提取。在绿地信息提取中,植被指数(如归一化植被指数,NDVI)被证实为快速有效的方法,适用于大面积城市绿地信息的快速及自动提取,而由于航片一般缺乏常用的近红外波段,因此研究采用植被颜色指数进行城市绿地信息的快速提取,该方法也适宜于无人机影像。对于北京研究区,本文通过不同指数结果的对比和精度分析选取适宜指数,并基于ENVI软件实现了城市绿地的批量提取,可快速得到全北京市城市绿地结果。     

北京市核心区共享单车骑行时空特征分析

共享单车在“低碳交通”的背景之下应运而生，给人们的出行带来了极大的便捷，同时，在共享单车的使用和管理过程中也存在一些问题，例如共享单车的投放不均衡等。本研究以北京市核心区为研究区，利用空间大数据分析等方法，对共享单车出行的时间序列和空间特征进行了分析，结果表明：(1)从共享单车出行的时间特征来看，一是从工作日的共享单车日均出行量远远大于休息日的日均出行量，工作日的日均出行量为623 257辆，休息日的日均出行量为245 039辆；二是工作日和休息日的共享单车出行高峰时段均为上午8点—9点以及下午的17点—18点；三是共享单车的出行时长主要集中在10 min以内，30 min以上的占比较少；(2)从共享单车出行的空间特征来看，一是北京市核心区工作日共享单车的出行呈现出“大聚集，小分散”的特点，且早高峰与晚高峰共享单车出行的空间流动趋势恰好相反，休息日呈现出“早分散，晚集聚”的特点。