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南京市市域热场分布与景观格局的关联分析

周雅星1,刘茂松1**,徐驰1,方芳1,钟晶晶1,张明娟2   

  1. 1南京大学生命科学学院, 南京 210093; 2南京农业大学园艺学院, 南京 210095)
  • 出版日期:2014-08-10 发布日期:2014-08-10

Correlation between thermal field and landscape pattern in the Nanjing metropolitan region.

ZHOU Ya-xing1, LIU Mao-song1**, XU Chi1, FANG Fang1, ZHONG Jing-jing1, ZHANG Ming-juan2   

  1. (1School of Life Sciences, Nanjing University, Nanjing 210093, China; 2School of Horticulture, Nanjing Agricultural University, Nanjing 210095, China)
  • Online:2014-08-10 Published:2014-08-10

摘要:

为探讨景观中热场格局的形成机制,以南京市为例,基于Landsat/ETM+遥感影像,获取研究区土地利用和地表温度信息,在1、2.5和5 km三个分析粒度上,分别计算了各景观单元的地表温度均值、温度变异系数与土地利用类型(耕地、林地、水体和聚落)的关联关系,并对景观组成特征、结构特征、空间区位特征等对热场格局影响的相对重要性进行了定量分析。结果表明:水体和林地具有显著的降温效应,耕地降温效应不显著。景观组成与结构因子是热场分布最重要的预测变量,点位特征和与到中心城区距离对热场的解释率较小。在3个分析粒度上,地类水平的结构特征对地类温度均值和变幅的解释能力均最强,且在较大分析粒度上优势显著;组成特征对温度均值与变异系数的解释能力次之,但独立影响较低;景观水平的结构特征对温度均值的解释能力较弱但对温度变幅的解释能力较强,且在2.5 km的分析粒度上独立作用显著。结果表明,对土地利用结构特征的调控可作为缓解城市热岛效应的有效途径。
 

关键词: 红花龙胆, 物种分布模型, 地理分布格局, 西南地区, 气候变化

Abstract: Using the data of land use and land surface temperature (LST) retrieved from Landsat/ETM+ images, we examined the relationships between the thermal field and landscape pattern in the Nanjing metropolitan region. The correlations between land use types (cropland, forest, water and settlements), mean LST and coefficient of variation (CV) of LST were quantified at three grain sizes (i.e., 1, 2.5 and 5 km). The relative importance of the effects of landscape composition, landscape structure (including landscapelevel and classlevel) and spatial factors on the thermal field pattern was distinguished quantitatively. The results showed that water bodies and forests played a significant role in lowering LST, while this cooling effect produced by croplands was relatively weak. Landscape composition and structure contributed most to explaining the thermal field pattern, while the location factors and the distance from the city center had minor effects. At all three grain sizes studied, considerable variances of mean LST and the CV of LST of each land use type could be explained by the class-level structure (especially at the grain size of 5 km). Landscape composition was the second important factor in explaining the mean and CV of LST, but its unique explanatory power was minimal. Landscape-level structure had a relatively small effect on mean LST but a relatively large effect on the CV of LST; and its unique explanatory power was prominent at the grain size of 2.5 km. Our results suggested that the regulation of land use structure could be a useful approach in order to relieve the urban heat island effect.

Key words: species distribution models, Southwest China, geographic distribution, Gentiana rhodantha, climate change