东篱科研大数据发现系统（DRDS）

位置：成果数据库 > 期刊 > 期刊详情页

基于Quickbird卫星影像的沈阳城市绿地景观格局的空间幅度效应

ISSN号：1007-7588
期刊名称：《资源科学》
时间：0
分类：Q149[生物学—生态学;生物学—普通生物学] TP7[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
作者机构：[1]中国科学院沈阳应用生态研究所,沈阳110016, [2]中国科学院研究生院,北京100049
相关基金：国家自然科学基金重大研究计划重点项目（编号：90411019）;中国科学院沈阳应用生态研究所领域前沿项目（编号：06LYQYA001）.

作者：唐玲[1,2], 谭丽[1,2], 何兴元[1], 李小玉[1], 陈玮[1], 张国友[1,2]

关键词：景观格局, 空间幅度, 梯度分析, Quickbird影像, 城市绿地, 沈阳市, Landscape pattern, Spatial extent , Gradient analysis , Quickbird imagery, Urban green space , Shenyang city

中文摘要：

基于2006年Quickbird卫星影像数据解译的沈阳城市绿地分布图,利用GIS技术和景观结构分析软件FRAGSTATS,结合梯度分析方法定量分析了沈阳城市绿地景观格局,并探讨了其幅度效应。结果表明：绿地的空间格局可以应用梯度分析与景观指数来定量。不同的绿地类型沿景观格局梯度确实表现出明显的“空间特征”。不同景观指数沿样带的表现也有差异。斑块密度和景观形状指数具有明显的梯度特征,而最大斑块指数,斑块类型百分比,多样性指数和景观聚集度指数则不明显。为了研究绿地景观的幅度效应,尝试了不同的窗口大小,5km的幅度是比较合理的尺度,能够通过景观指标的变化反映城市绿地空间格局。

英文摘要：

This paper analyzes the urban landscape of Shenyang and quantifies the spatial pattern of urban green space, and investigate the effect of spatial extent in analysis of urban green space landscape pattern. We used GIS and the landscape structure analysis program FRAGSTATS, and an urban green space map based on a 2006 Quiekbird image. This provides a new method to analyze urban green space by using high-resolution images, GIS, and combining gradient analysis and landscape pattern analysis. This paper analyses the five types of urban green space： green parks, green space attached to homes or businesses, road greenbehs, green space protected for production and agricultural land, along an urban gradient transect. The results of the transect analysis with landscape-level metrics showed that the spatial pattern of urban green space could be reliably quantified using landscape metrics with a gradient analysis approach. The patch density and landscape shape index showed significant gradient characteristics, while the large patch index, Shannon＇ s diversity index, the percentage of landscape, and the landscape aggregation index were the opposite. The landscape metrics had different variation patterns when spatial extent was varied. The rate of change in space exhibits two aspects. At a small range （ ≤ 4km）, the landscape index fluctuated extremely, and it cannot show a good gradient of landscape features. When the range is larger （≥5km）, the landscape index changes are mild. It can eliminate interference from the high resolution and regional differences, although it also causes the loss of some gradient features. Therefore, the rate of 5km is the most appropriate scale for studying the gradient of green landscape metrics in Shenyang City. It can avoid big fluctuations in the landscape indexes, and also accurately represent the changes of the urban landscape.

同期刊论文项目