Urban heat island is a global issue and a consequence of rapid urbanization that leads to higher land surface temperature in urban areas. The range is 0.6˚C -1.3˚C compared to rural and suburban areas. LST (Land surface temperature) is an important parameter in determining the heat island. Understanding the relationship between green space configuration and LST is essential to the effective design of the mechanisms, which reduce the effect of urbanization on UHI (urban heat island). This study examines the correlation between LST and spatial configuration of green space in the urban landscape of Neyshabur city, Iran. Satellite images are obtained from Landsat ETM+ satellite sensor with a spatial resolution of 60 meters in August 2010 and used for the estimation of LST. In order to identify the configuration of green space, five configuration metrics LSI (landscape Shape Index), MPFD (Mean Patch Fractal Dimension), ED (Edge Density), MPS (Mean Patch Size) and MSI (Mean Shape Index) are used. In addition, configuration of the green space and temperature is compared by Pearson's correlation-coefficient. Negative values represent a suppressive/negative effect on each other; the fact that other indicators of spatial configuration are inversely related to temperature means that they weaken the effect of UHI. Results of the study showed that the spatial configuration of the green space notably affects increased LST and UHI. On the other hand, the configuration indicator with the greatest impact on LST was ED, because with increase in margin density further decreases LST.
This study evaluates the green space ecological quality with regard to its spatial properties. It investigates how the spatial properties of green space patches affect ecological aspects of municipal green spaces of Mashhad in Iran. The importance and necessity of this investigation is to develop a concept to evaluate the quality of urban green patches based on the perspective and method of landscape ecology. In accordance with our objectives, the quality concept is defined by quantitative (size, area, density) and qualitative (shape, complexity, connectivity) factors as referred to spatial configuration and composition of landscape structure. However, to have a better understanding of the quality concept, we explored the relationship between landscape variables and ecological quality by spatial analysis and correlation tests. We (1) drew the urban green space map by images processing, (2) quantified landscape metrics for the green space patches, (3) analyzed and represented the metric value spatially, (4) calculated ecological quality and drew the grade map, (5) measured the Pearson correlation coefficients and linear regression between ecological quality and each landscape metric. Results of this study provided the evidence to study ecological quality by integrating metrics map and analyzing spatial heterogeneity in Mashhad city. Results showed that the extent and continuity of the green spaces were too low to effectively support some key ecological services. Additionally, the Pearson's correlation coefficients and linear regression revealed strong relationships between ecological quality and most landscape metrics except LSI. Although it was expected that the qualitative variables of green space had higher influence on the ecological quality, quantitative variables had the highest effect due to the origin and nature of the green patches.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.