闽南三市绿地景观格局与地表温度的空间关系

深入探索绿地景观格局对热环境的影响机制,对于改善城市生态环境具有重要意义。基于厦门、漳州、泉州三市的Landsat遥感数据,应用景观生态学与空间自相关理论,探讨了绿地景观与地表温度的空间分布特征,并用双变量空间自相关与空间自回归模型分析两者之间的空间关系。结果表明:闽南三市绿地与地表温度均具有显著的空间自相关性;内陆的高海拔地区,绿地分布密集,地表温度较低,而城区、乡镇及大片的耕地,绿地分布较少,地表温度较高;漳州、泉州绿地景观格局对地表温度的影响更显著,厦门最弱;绿地的景观类型比例、最大斑块指数、聚集度指数、平均斑块面积与地表温度呈负相关,斑块密度与地表温度呈正相关;边缘密度、平均形状指数与地表温度的关系存在不确定性;空间滞后模型与空间误差模型能更好地解释绿地景观格局与地表温度的空间关系。

Spatial relationship of greenspace landscape pattern with land surface temperature in three cities of southern Fujian

Exploring the effects of greenspace landscape pattern on thermal environment is of great significance to improving urban ecological environment.Based on Landsat remote sensing data in Xiamen,Zhangzhou and Quanzhou of southern Fujian,landscape ecology and spatial autocorrelation theory were used to quantify spatial distribution characteristics of greenspace landscape and land surface temperature.Further,we used bivariate spatial autocorrelation and spatial autoregressive model to analyze the spatial relationships.The results showed that both of greenspace and land surface temperature had significant spatial autocorrelation.In the inland areas with high elevations,greenspace was significantly concentrated with relatively low land surface temperature,while in urban areas,towns and large areas of cultivated land,greenspace was less distributed and relatively high land surface temperature.Greenspace landscape pattern had stronger effects on the land surface temperature in Zhangzhou and Quanzhou than in Xiamen.The percentage of landscape,largest patch index,aggregation index and mean patch area of greenspace were negatively correlated with land surface temperature,whereas patch density was positively correlated with land surface temperature.The correlation between edge density,mean shape index and land surface temperature is uncertain.Spatial lag model and spatial error model performed better in explaining the spatial relationship between greenspace landscape pattern and land surface temperature.