ABSTRACT:A common consequence of rapid and uncontrollable urbanization is Urban Heat Island (UHI). It occurs due to the negligence on climate behaviour which degrades the quality of urban climate condition. Recently, addressing urban climate in urban planning through mapping has received worldwide attention. Therefore, the need to identify the significant factors is a must. This study aims to analyse the relationships between Land Surface Temperature (LST) and two urban parameters namely built-up and green areas. Geographical Information System (GIS) and remote sensing techniques were used to prepare the necessary data layers required for this study. The built-up and the green areas were extracted from Landsat 8 satellite images either using the Normalized Difference Built-Up Index (NDBI), Normalized Difference Vegetation Index (NDVI) or Modified Normalize Difference Water Index (MNDWI) algorithms, while the mono-window algorithm was used to retrieve the Land Surface Temperature (LST). Correlation analysis and Multi-Linear Regression (MLR) model were applied to quantitatively analyse the effects of the urban parameters. From the study, it was found that the two urban parameters have significant effects on the LST of Kuala Lumpur City. The built-up areas have greater influence on the LST as compared to the green areas. The built-up areas tend to increase the LST while green areas especially the densely vegetated areas help to reduce the LST within an urban areas. Future studies should focus on improving existing urban climatic model by including other urban parameters.

Nowadays, UAV is preferred by experts since it is more affordable with reliable accuracy. However, debates on its accuracy draw worldwide attention in order to maintain the output’s quality. Flight altitude is one of the most debated issues of UAV employment due to various ground conditions. Thus, this study intends to investigate the effects of flight altitude towards the final output accuracy. In this study, three different flight altitudes (60m, 80m and 100m) were used to test the outputs accuracy within selected sites in UPNM campus by employing DJI Phantom 4 Pro V2.0 drone. Orthophotos and Digital Surface Model (DSM) of the selected sites were then generated using Pix4D Mapper Software. On-screen measurements of selected features within the selected sites were taken and compared with the actual measurements obtained on grounds. Later, these outputs were used to generate contours using ArcGIS software. The generated contours were compared with available as-built plan. The results were examined qualitatively and quantitatively. From this study, it is found that the mean variance values on flat surface using different flight elevation were 0.86m, 0.99m and 1.16m for 60m, 80m and 100m respectively. Whereas, the mean variance values on hilly surface were 6.95m, 4.35m and 4.3m for 60m, 80m and 100m. On flat surfaces, 60m flight altitude was the best height to be used for UAV mapping. However, for hilly surfaces, 100m flight altitude was the best height to be used. This contrast may due to the lower overlapping images in 60m flight altitude image capture. From the study also, it is found that the accuracy of UAV mapping on hilly surfaces tends to be lower than flat surfaces. This called for further studies to identify the best measures to reduce the errors resulted by extreme ground characteristics.

In recent years, it has been observed that numerous cases of windstorm event. There are many factors that cause windstorms to occur. The factors of meteorology, urban morphology, the topography need to be studied to find out the cause of windstorms. The work analyzed meteorology factors such as: wind speed, humidity and temperature, occurring in 2017. Meteorological data from the Department of Environment Malaysia (DOE) station, allow determining the wind speed, humidity and temperature data daily in 2017. As well as, the pattern of parameter and their relationship between them being determined. The pattern of wind speed monthly was inconsistent. The highest average wind speed in 2017 was 4.72 m/s and the lowest average was 0.56 m/s. While humidity, the highest average was 83.12 % and the lowest average humidity was 72.33 %. For temperature, the maximum average for 2017 was 28.43 °C and the minimum average was 26.26 °C. The correlation of wind speed between humidity and temperature was -0.256 and 0.278, which is low correlate. That must be other active factors that influence the wind speed and contribute to the windstorm event. Wind speed, humidity and temperature during the windstorm event on 11 February 2017 was analyzed. During the windstorm event, the wind speed blows up to 15.7 m/s while the humidity reading decrease to 68.4 % and the temperature was 30.9 °C. When the wind speed reading is high, the temperature reading also increases and the humidity reading will go down and vice versa and has caused the windstorm event to happen.

No abstract

Lightning is a major climatic phenomenon in Southeast Asia over Indian Ocean and Malaysia is the most affected area in the region. Damages in the different industries, real estates, defense and human fatalities are caused by lightning strikes and it is very common in Malaysia. Existing non-effective lightning detection network in Malaysia now has become an urge to modify the system and improve it according to the need of the Malaysian Meteorological Department. Research facilities in the Malaysian universities and related research organizations need to give substantial effort in developing lightning science and technology to solve this problem. In this article, current status of lightning detection network in Malaysia and its weaknesses have been discussed briefly. Also, suggestion have been proposed to improve it.