Unveiling the Impact of Physical Geography on Poverty: A Comprehensive Analysis for Sustainable Development

This study examines the effects of physical geography, demographic characteristics of household heads, and poverty, with a specific focus on the number of poor household heads within districts of Terengganu. Through the utilization of a Poisson log-linear modeling approach, the research investigates the effects of physical geography and demographic factors, on the number of poor household heads for each of the sub-districts. The central concern of this research revolves around the need to comprehend the underlying reasons for differing poverty rates among sub-districts in Terengganu. To carry out the analysis, a Poisson log-linear modeling is employed for the data, leveraging SPSS and Rstudio for statistical analysis. This method enabled us to thoroughly assess how physical geography factors (including terrain and accessibility) and demographic characteristics of household heads (including age, education level, and employment status) influence poverty rates. To determine the distribution of spatial poverty, ArcMap is used to visualize the Standardised Poverty Ratio. The results of the study show that 31 sub-districts were identified as not being at risk of poverty and another 31 were labeled as having a high poverty rate. Furthermore, the Poisson regression analysis yielded several important insights into the factors influencing poverty rates. Specifically, it is found that a higher average age is associated with a decrease in poverty. Conversely, an increase in non-formal education levels, lower elevations, steeper slopes, and higher river density are linked to an increase in poverty. These findings have significant implications for policy formulation and targeted interventions in Terengganu, providing valuable guidance for addressing poverty-related challenges. The mapping of high-risk poverty areas offers crucial information for spatially targeted interventions, facilitating the implementation of more efficient poverty reduction measures. Furthermore, research findings enhance the understanding of the intricate dynamics between physical geography, demographic characteristics, and household poverty. By identifying the significant factors impacting poverty, this study provides valuable insights for developing targeted poverty alleviation strategies and formulating evidence-based policies. In conclusion, this study serves to inform policymakers, researchers, and practitioners about the multifaceted relationships between physical geography, demographic characteristics, and household poverty. By recognizing the critical role played by these factors, stakeholders can devise comprehensive approaches tailored to specific contexts, effectively addressing poverty, promoting inclusive growth, and improving the well-being of vulnerable populations

Habitat quality assessment in the Royal Belum rainforest, Malaysia using spatial analysis

Royal Belum rainforest contains various flora and fauna species, however, the assessment of habitat quality is still lacking. This study aims to develop the habitat quality zone in the Royal Belum rainforest. The downloaded Landsat 8 OLI/TIRS CI satellite images in the year 2020 from the United States Geological Survey (USGS) were processed using supervised classification and exported into vector data in ArcGis 10.8. Land use, normalized difference vegetation index (NDVI), buffer, and land structure were then analyzed. The result shows that the highest percentage and density of the land use of the Royal Belum rainforest is vegetation. Buffer zone analysis identifies the risky area for habitat in the range of 1km and 5km from the built-up area. The area within the buffer ring should be protected from building and construction to ensure habitat quality in that area can be maintained. This study will give a better understanding of land use and vegetation index assessment for future planning in the Royal Belum rainforest. Therefore, habitat quality assessment is an important tool that can help to identify areas of high-quality habitat that are crucial for the survival and reproduction of target species and to prioritize these areas for conservation and management

Evolution of green space under rapid urban expansion in Southeast Asian cities

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

Boroaluminosilicate glasses – Effect of composition on mechanical properties

Boroaluminosilicate glasses are of significant interest for a variety of applications. More generally these glasses are interesting because both boron and alumina are in competition for charge compensating modifiers that allow them to adopt tetrahedral coordination within the glass network, which can be expected to affect overall glass properties Understanding composition-structure-property relationships in boroaluminosilicate glass is important to enabling property optimisation as a function of composition design. This project is aimed at increasing understanding of how composition affects the mechanical properties of boroaluminosilicate glasses with varying amounts of the three glass formers (SiO2, Al2O3 and B2O3) and different alkaline earth modifiers. Particular attention is focussed on the structural role of sodium as a charge compensator on the composition-structure-properties relationships in boroaluminosilicate glass. Essentially the network modifiers can be associated with SiO2, Al2O3 and B2O3 in different ways making it difficult to predict the mechanical properties of such glasses. In this research, 10 different series of glasses have been synthesized. The series had varying silica/alumina ratios, boron/alumina ratios, alkaline earth/alumina ratios, alkaline earth/silica ratios or alkaline earth + alumina/silica ratios. The alkaline earths used were CaO or BaO. Variations in the hardness and fracture toughness of the glasses were measured using the indentation method and acoustic measurements were used to find their moduli. Differential thermal analysis was used to measure the glass transition temperature. Fourier Transform Infra-red spectroscopy (FTIR), Raman and Nuclear Magnetic Resonance (NMR) were used to investigate the base glass structure and the structural effects of adding different alkaline earth elements. It was found that the amount of Al2O3 used in the boroaluminosilicate glass significantly affects the properties: the glass transition temperature (Tg) and molar volume increased with increasing Al2O3 content in the series N7.6M1.1C3AXB7.6S80.7-X glasses. Meanwhile, observation for Tg to network charge balance for specific composition were notably in range of error bars when the network charge balance are > 0. However, Tg notably shows huge decreases when network charge balance between -21 to 0. The Raman peak at ~ 1000 cm–1 changes shape significantly for most of the glass series indicative of notable changes in the detailed structure of the glass including silica connectivity with composition. FTIR showed that the maximum peak shifted to lower wavenumbers (from 1047 to 1018 cm-1) with increasing amounts of Al2O3 and the intensity (absorption of IR) reduced which indicated that the polymerisation of glass is increased. Raman spectra were used to calculate a value of polymerisation index, specifically to see the connectivity of the glass structure in the boroaluminosilicate glass system. It was found that glasses that contain CaO had a higher polymerisation index compared to those that contained BaO and that higher Al2O3 contents gave higher polymerisation indices. This was also borne out by NMR studies on some of the glasses investigated. In a composition-structure-properties relationship, from the overview of the correlations between the properties investigated, the network modifiers, formers and intermediates show there is a connection between most of the composition as shown in ternary diagrams and 3-D correlations. When the glass transition temperature increases the molar volume increases and the shear modulus decreases. Meanwhile, when correlating hardness, glass transition temperature and network former, it was found that increasing the network charge balance resulted in decreasing glass transition temperatures and increased hardness values. Overall it can be seen that increasing of network charge balance, the mechanical properties such as Young’s modulus, shear modulus, bulk modulus, Poisson’s ratio and hardness are increased and polymerisation index are decreased if the total network charge balance is > 0. Meanwhile, the value of Poisson’s ratio is ~0.24 for most of the compositions studied, and the hardness exhibited similar behaviour to Young’s modulus which increased with increasing network modifier. The composition-structure-mechanical properties can be controlled and designed from the various mixing ratio of different networks. However, the mixed network former in the composition leads to the non-linear trends in macroscopic properties as a function of composition design

Self-Fluxing Mechanism in Geopolymerization for Low-Sintering Temperature of Ceramic

Kaolin, theoretically known as having low reactivity during geopolymerization, was used as a source of aluminosilicate materials in this study. Due to this concern, it is challenging to directly produce kaolin geopolymers without pre-treatment. The addition of ground granulated blast furnace slag (GGBS) accelerated the geopolymerization process. Kaolin–GGBS geopolymer ceramic was prepared at a low sintering temperature due to the reaction of the chemical composition during the initial stage of geopolymerization. The objective of this work was to study the influence of the chemical composition towards sintering temperature of sintered kaolin–GGBS geopolymer. Kaolin–GGBS geopolymer was prepared with a ratio of solid to liquid 2:1 and cured at 60 °C for 14 days. The cured geopolymer was sintered at different temperatures: 800, 900, 1000, and 1100 °C. Sintering at 900 °C resulted in the highest compressive strength due to the formation of densified microstructure, while higher sintering temperature led to the formation of interconnected pores. The difference in the X-ray absorption near edge structure (XANES) spectra was related to the phases obtained from the X-ray diffraction analysis, such as akermanite and anothite. Thermal analysis indicated the stability of sintered kaolin–GGBS geopolymer when exposed to 1100 °C, proving that kaolin can be directly used without heat treatment in geopolymers. The geopolymerization process facilitates the stability of cured samples when directly sintered, as well as plays a significant role as a self-fluxing agent to reduce the sintering temperature when producing sintered kaolin–GGBS geopolymers

Unveiling the Impact of Physical Geography on Poverty: A Comprehensive Analysis for Sustainable Development

This study examines the effects of physical geography, demographic characteristics of household heads, and poverty, with a specific focus on the number of poor household heads within districts of Terengganu. Through the utilization of a Poisson log-linear modeling approach, the research investigates the effects of physical geography and demographic factors, on the number of poor household heads for each of the sub-districts. The central concern of this research revolves around the need to comprehend the underlying reasons for differing poverty rates among sub-districts in Terengganu. To carry out the analysis, a Poisson log-linear modeling is employed for the data, leveraging SPSS and Rstudio for statistical analysis. This method enabled us to thoroughly assess how physical geography factors (including terrain and accessibility) and demographic characteristics of household heads (including age, education level, and employment status) influence poverty rates. To determine the distribution of spatial poverty, ArcMap is used to visualize the Standardised Poverty Ratio. The results of the study show that 31 sub-districts were identified as not being at risk of poverty and another 31 were labeled as having a high poverty rate. Furthermore, the Poisson regression analysis yielded several important insights into the factors influencing poverty rates. Specifically, it is found that a higher average age is associated with a decrease in poverty. Conversely, an increase in non-formal education levels, lower elevations, steeper slopes, and higher river density are linked to an increase in poverty. These findings have significant implications for policy formulation and targeted interventions in Terengganu, providing valuable guidance for addressing poverty-related challenges. The mapping of high-risk poverty areas offers crucial information for spatially targeted interventions, facilitating the implementation of more efficient poverty reduction measures. Furthermore, research findings enhance the understanding of the intricate dynamics between physical geography, demographic characteristics, and household poverty. By identifying the significant factors impacting poverty, this study provides valuable insights for developing targeted poverty alleviation strategies and formulating evidence-based policies. In conclusion, this study serves to inform policymakers, researchers, and practitioners about the multifaceted relationships between physical geography, demographic characteristics, and household poverty. By recognizing the critical role played by these factors, stakeholders can devise comprehensive approaches tailored to specific contexts, effectively addressing poverty, promoting inclusive growth, and improving the well-being of vulnerable populations

Habitat quality assessment in the Royal Belum rainforest, Malaysia using spatial analysis

Royal Belum rainforest contains various flora and fauna species, however, the assessment of habitat quality is still lacking. This study aims to develop the habitat quality zone in the Royal Belum rainforest. The downloaded Landsat 8 OLI/TIRS CI satellite images in the year 2020 from the United States Geological Survey (USGS) were processed using supervised classification and exported into vector data in ArcGis 10.8. Land use, normalized difference vegetation index (NDVI), buffer, and land structure were then analyzed. The result shows that the highest percentage and density of the land use of the Royal Belum rainforest is vegetation. Buffer zone analysis identifies the risky area for habitat in the range of 1km and 5km from the built-up area. The area within the buffer ring should be protected from building and construction to ensure habitat quality in that area can be maintained. This study will give a better understanding of land use and vegetation index assessment for future planning in the Royal Belum rainforest. Therefore, habitat quality assessment is an important tool that can help to identify areas of high-quality habitat that are crucial for the survival and reproduction of target species and to prioritize these areas for conservation and management

Spatial Distribution of COVID-19 Infected Cases in Kelantan, Malaysia

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