He Xingyuan

Estimation of the Relationship Between Urban Vegetation Configuration and Land Surface Temperature with Remote Sensing

Urban vegetation can help decrease Land surface temperature (LST) to mitigate urban heat island (UHI) effects. The relationship between LST and urban vegetation amount has been extensively documented. However, few studies have examined the relationship between LST and urban vegetation configuration and particularly whether the relationship changes across scales. In this study, LST in Changchun, China was obtained from Landsat-5 Thematic Mapper (TM) data and then correlated to urban vegetation amount and configuration information derived from high-spatial-resolution SPOT satellite data to uncover the relationship between urban vegetation configuration and LST. These results suggest that not only by increasing the amounts of urban vegetation, but also by optimizing their spatial pattern of urban vegetation can decrease LST. Given a fixed amount of urban vegetation, LST can be significantly decreased or increased by different configuration of urban vegetation. Besides the relationship between LST and urban vegetation configuration is complex and scale dependant and spatial scales should be considered when we try to explore the relationship between them. These findings can deepen the understanding of their interactions between LST and urban vegetation and provide useful information for urban planners about how to arrange urban vegetation at the landscape level to improve urban thermal environment.

Comparison of Two Approaches for Detecting the Depth of Edge Influence on Vegetation Diversity in the Arid Valley of Southwestern China

Three types of landscape boundary (forest/pepper field, forest/cabbage field, and forest/grassland) were selected in the aird valley of upper reaches of Minjiang River, southwestern China. On the basis of vegetation diversity, the depth of edge influence (DEI) on different types of landscape boundaries was estimated using principal components analysis (PCA) method and moving split-window techniques (MSWT). The results showed that in the 5 transects, PCA method was able to detect the edge influence depth with 3 transects, while MSWT could explain 4 transects. It is concluded that PCA and MSWT both can be used to detect the depth of edge influence within 50 m from the edge to the interior. Similar conclusions were drawn in the forest of each transect with the two methods, but no similar conclusions were drawn in the pepper field of each transect. Although the two methods have advantages and disadvantages respectively, they are useful tools for characterizing edge dynamics. Comparing the two methods, MSWT is more successful.

Structure and Ecological Benefits Evaluation of Street Trees in Shenyang Based on i-Tree (STRATUM) Model

Sampling method was employed to investigate the structure and ecological benefits of street trees in the area within Second Ring Road of Shenyang. The study area covers about 161 km2£¬and 61 main roads. Based on the field data, the i-Tree (STRATUM) model was run to analyze street trees¡¯structure and ecological benefits. The results showed that there were 19 street tree species in the study area, which were belong to 13 families and 15 genera. The most common tree species are Sophora japonica, Populus alba, and Fraxinus chinensis, the percentage of which reached 68.32% of the total population. The proportion of small trees (d.b.h.

Landscape pattern change in the upper valley of Min River

The upper valley of Min River (102°59′–104°14′E, 31°26′–33°16′N), which is consisted of the counties Wenchuan, Maoxian, Lixian, Heishui, and Songpan, refers to the part up to Dujiangyan City, and locates on the transition zone from the Tibetan Plateau to the Sichuan Basin. It is one of the most important forest areas in China, especially in Sichuan Province. Over past two decades, the landscape changed remarkably in the region. The 3S techniques (Remote Sensing (RS), Geographic Information System (GIS) and Global Position System (GPS)) were used to classify the images and analyze the landscape change. The remotely sensed data of Landsat TM 1986 and Landsat ETM+2000 were used to analyze the landscape change of the region. The landscape were classified into 10 types of cropland, forest, shrub land, economic forest, grassland, build up land, river, lake, swamp, and unused land. The results showed that: 1) the woodland and grassland were dominating landscape types in the upper valley of Min River, which is more than 91% of the study area; 2) the alteration of the landscape was mainly happened among forest, shrub land, grassland, economic forest, cropland, and build up land, where forest decreased from 51.17% to 47.56%; 3) the landscape fragmentation in the upper valley of Min River was aggravated from 1986 to 2000.