Globally, rapid urban expansion has caused green spaces in urban areas to decline considerably. In this study, the rapid expansion of three Southeast Asia cities were considered, namely, Kuala Lumpur City, Malaysia; Jakarta, Indonesia; and Metro Manila, Philippines. This study evaluates the changes in spatial and temporal patterns of urban areas and green space structure in the three cities over the last two decades. Land use land cover (LULC) maps of the cities (1988/1989, 1999 and 2014) were developed based on 30-m resolution satellite images. The changes in the landscape and spatial structure were analysed using change detection, landscape metrics and statistical analysis. The percentage of green space in the three cities reduced in size from 45% to 20% with the rapid expansion of urban areas over the 25-year period. In Metro Manila and Jakarta, the proportion of green space converted to urban areas was higher in the initial 1989 to 1999 period than over the latter 1999 to 2014 period. Significant changes in green space structure were observed in Jakarta and Metro Manila. Green space gradually fragmented and became less connected and more unevenly distributed. These changes were not seen in Kuala Lumpur City. Overall, the impact of spatial structure of urban areas and population density on green space is higher in Jakarta and Metro Manila when this is compared to Kuala Lumpur. Thus, the results have the potential to clarify the relative contribution of green space structure especially for cities in Southeast Asia where only a few studies in urban areas have taken place.

Eradicating poverty has become the main concern for Malaysian government since independence. Recognising the incidence of poverty through standard statistical data tables alone is no longer adequate. This study examines socio-demographic effects on poverty and measures spatial patterns in poverty risk looking for high risk of areas. The poverty data were counts of the numbers of poverty cases occurring in every ten districts of Kelantan. To model these data, a spatial autocorrelation was detected prior to a Poisson Log Linear Leroux Conditional Autoregressive was fitted to the data. The result shows the variables household members, number of non-education of household head and log number of female household head significantly associated with the number of poor households. Tumpat was found as the highest risk area of poverty.

Poverty eradication among poor household head becomes a significant concern. Previous research employed the traditional statistical method to model the poverty data. However, these traditional statistical methods do not consider the spatial elements of poverty data. This study compares the performance of Poisson log-linear Leroux Conditional Autoregressive (CAR) model with difference neighbourhood matrices. A Poisson Log-Linear Leroux Conditional Autoregressive model with different neighbourhood matrices was fitted to the poverty data for 66 districts in Kelantan for 2010. The results show that the performance of the model with the contiguity matrix was nearly similar to the Delaunay triangulation neighbourhood matrix in estimate poverty risk. The variables that are significantly associated with the poverty in Kelantan are the number of non-education, number of female household head and the average age of the household head.

Kota Bharu city in Kelantan, Malaysia was reported with the highest cases of coronavirus disease 2019 (COVID-19) among other districts. Kota Bharu is the capital city of Kelantan, which acts as the administrative, commercial, and financial areas. A large population pool may become a potential carrier for disease transmission to become an epidemic. However, the impact of population density on the COVID-19 outbreak in Malaysia is still unknown and undiscovered. Therefore, this study investigates the impact of population density on COVID-19 as a potential virus transmission carrier using linear regression models. The chances of formulating new strategies for combating COVID-19 are higher when the driver of transmission potential is identified. This study shows that the highest value of infected area density is in Kota Bharu (0.76), while the infected risk area was highest in Jeli (0.33). This study found that there is a strong relationship between COVID-19 infection cases in Kelantan and population density (R2 which is 0.845). Therefore, high population density was identified as a potential driver of transmission of COVID-19 outbreak. Understanding the potential drivers of the disease in a local setting is very important for better preparation and management. The outcome of the study can aid in the development of a new analytical model for strategic planning of Zero COVID-19 for securing the public health and wellness, both social and economic, by researchers, scientists, planners, resource managers, and decision-makers.

Globally, the amount of green space in urban areas has significantly decreased because of fast urban expansion. Urbanization may modify the spatial structure of a landscape and have an impact on its ecological function. The research aims to quantify the landscape structure changes of green space in the years 1994, 2004, and 2014 in Pasir Mas using remote sensing, GIS and landscape ecology approach. Three satellite images were classified into five land use land cover (LULC) which are forest, agriculture area, cleared land, water bodies and built-up area. The results show that the highest percentage of area in year 1994 is forest followed by agriculture, built up area and water bodies. However, in year 2014 the percentage of land use are vice versa. In the period from 1994 to 2004, 1.92% of forest was converted into built up areas in Pasir Mas district. However, in the period of year 2004 to 2014, the percentage of forest area that has been converted into built up area is increase about 4.32%. Forest shows significance increase in the transition into agriculture area by 49.63% in the year of 1994 and 2004. For the period of year 2004 and 2014, the conversion of forest area into agriculture area also in high percentage which is 17.66%. Landscape structure changes analysis show that there are significant changes of Euclidean nearest neighbour distance (MNN) indicating that there is fragmentation and isolation between patches. Similarly, the size and shape of forest patches also decreased indicating by percentage of area (PAREA) and landscape shape index (LSI). Therefore, using remote sensing, GIS, and landscape ecology, this project will help understand the spatial structure of green space and the impact of urban expansion in Pasir Mas, Kelantan, in order to give the knowledge necessary for sustainable land use planning.