Understanding the effects of the impervious surfaces pattern on land surface temperature in an urban area

It is well known that urban impervious surface （IS） has a warming effect on urban land surface temperature （LST）. However, the influence of an IS＇s structure, components, and spatial distribution on LST has rarely been quantitatively studied within strictly urban areas. Using ETM＋ remote sensing images from the downtown area of Shanghai, China in 2010, this study characterized and quantified the influence of the IS spatial pattern on LST by selecting the percent cover of each IS cover feature and ten configuration metrics. The IS fraction was estimated by linear spectral mixture analysis （LSMA）, and LST was retrieved using a mono-window algorithm. The results indicate that high fraction IS cover features account for the majority of the study area. The high fraction IS cover features are widely distributed and concentrated in groups, which is similar with that of high temperature zones. Both the percent composition and the configuration of IS cover features greatly affect the magnitude of LST, but the percent composition is a more important factor in determining LST than the configuration of those features. The significances and effects of the given configuration variables on LST vary greatly among IS cover features.

Long-range cross-correlation between urban impervious surfaces and land surface temperatures

The thermal effect of urban impervious surfaces （UIS） is a complex problem. It is thus necessary to study the relationship between UIS and land surface temperatures （LST） using complexity science theory and methods. This paper investigates the long-range cross- correlation between UIS and LST with detrended cross- correlation analysis and multifractal detrended cross- correlation analysis, utilizing data from downtown Shanghai, China. UIS estimates were obtained from linear spectral mixture analysis, and LST was retrieved through application of the mono-window algorithm, using Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data for 1997-2010. These results highlight a positive long-range cross-correlation between UIS and LST across People＇s Square in Shanghai. LST has a long memory for a certain spatial range of UIS values, such that a large increment in UIS is likely to be followed by a large increment in LST. While the multifractal long-range cross- correlation between UIS and LST was observed over a longer time period in the W-E direction （2002-2010） than in the N-S （2007-2010）, these observed correlations show a weakening during the study period as urbanization increased.

Change of impervious surface area and its impacts on urban landscape:an example of Shenyang between 2010 and 2017

Introduction:One of the most striking features of urbanization is the replacement of the original natural land cover type by artificial impervious surface area(ISA).However,the extent of the contribution of various environmental factors,especially the growth of 3D space to ISA expansion,and the scope and mechanism of their influences in dramatically expanding cities,are yet to be determined.The boosted regression tree(BRT)model was adopted to analyze the main influencing factors and driving mechanisms of ISA change in Shenyang,China between 2010 and 2017.Outcomes:The nearly complete-coverage ISA(≥0.7)increased from 42%in 2010 to 47%in 2017.The percentage of landscape with a high ISA fraction increased,while the landscape evenness and diversity of ISA decreased.The BRT analysis revealed that elevation,regional population density,and landscape class had the largest influences on the change of urban ISA,contributing 22.55%,18.16%,and 11.18%to the model,respectively.Conclusion:Overall,topographic and socioeconomic factors had the greatest influence on urban ISA change in Shenyang,followed by land use type and building pattern indices.The trend of high aggregation was strong in large commercial and residential areas.The 3D expansion of the city had an influence on its areal expansion.

哈尔滨市中心城区不透水面时空变化及驱动力分析（英文）

Associated with the rapid economic development of China, the level of urbanization is becoming a serious concern. Harbin, the capital city of Heilongjiang Province, China and one of the political, economic, cultural, and transportation centers of the northeastern region of China, has experienced rapid urbanization recently. To examine the spatial patterns of long-term urbanization and explore its driving forces, we employed the impervious surface fraction derived from remote sensing image as a primary indicator. Specifically, urban imper- vious surface information for the central city of Harbin in 1984, 1993, 2002, and 2010 was extracted from Landsat Thematic Mapper image using a Linear Spectral Mixture Analysis （LMSA）. Then, the spatial and temporal variation characteristics and the driving factors of percent impervious surface area （ISA） changes were analyzed throughout this 26-year period （1984 to 2010）. Analysis of results suggests that： （1） ISAs in the central city of Harbin con- stantly increased, particularly from 1993 to 2010, a rapid urbanization period; （2） the gravity center of impervious surface area in the central city was located in Nangang District in 1984, moving southeast from 1984 to 1993, northwest from 1993 to 2002, and continuing toward the southeast from 2002 to 2010; and （3） the urban growth of the central city can be character- ized as edge-type growth.