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This study focuses on investigation of vegetation growth effect on lowering land surface temperature (LST) within the urban residential area. The area of study is located in residential area of USJ Puchong, Selangor. Two dates of Landsat 5 TM is use d to generate land use map, NDVI maps and LST maps. Results show that the replacement of natural green areas into vegetated areas demonstrated significant low temperature of the residential in urban area after 20 years of development. Hence, provide bette r quality of environment of urban resident and create sustainable development. Subsequently, it is important to consider an environment factors to plan a sustainable urban development, and furthermore to provide a quality environment for urban residents.

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Abstract. Earlier studies have indicated that, the temperature distribution in the urban area is significantly warmer than its surrounding suburban areas. The process of urbanization has created urban heat island (UHI). As a city expands, trees are cut down to accommodate commercial development, industrial areas, roads, and suburban growth. Trees or green areas normally play vital role mitigat the UHI effects especially in regulating high temperature in saturated urban areas. This study attempts to assess the effects of vegetation growth on land surface temperature (LST) distribution in urban areas.rea within the City of Shah Alam, Selangor has been selected as the study area. Land use/land cover and LST maps of two different dates are generated from Landsat 5 TM images of the year 1991 and 2009. Only five major land cover classes are considered in this study. Mono-window algorithm is used to generate the LST maps. Landsat 5 TM images are also used to generate the NDVI maps. Results from this study have shown that there are significant land use changes within the study area. Although the conversion of green areas into residential and commercial areas significantly increase the LST, matured trees will help to mitigate the effects of UHI

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Abstract. The population size, population density and rate of urbanization are often crediting to contributing increasing a crime pattern specially in city. Urbanism model stating that the rise in urban crime and social problems is based on three population indicators namely; size, density and heterogeneity. The objective of this paper is to identify crime patterns of the hot spot urban crime location and the factors influencing the crime pattern relationship with population size, population density and rate of urbanization population. This study employed the ArcGIS Pro 2.4 tool such as Emerging Hot Spot Analysis (Space Time) to determine a crime pattern and Ordinary Least Squares (OLS) Regression to determine the factors influencing the crime patterns. By using these analyses tools, this study found that 54 (53%) out of 102 total neighbourhood locations (2011–2017 years) had a 99 percent significance confidence level where z-score exceeded +2.58 with a small p-value (p < 0.01) as the hot spot crime location. The result of data analysis using OLS regression explains that combination of exploratory variable model rate of urbanization and population size contributes 56 percent (R2 = 0.559) variance in crime index rate incident [F (3,39) = 18.779, p < 0.01). While the population density (β = 0.045, t = 0.700, p > 0.10) is not a significance contributes to the change in crime index rate in Petaling and Klang district. The importance of the study is useful information for encouraging government and law enforcement agencies to promote safety and reduce risk of urban population crime areas.

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