Many countries are committed to boosting renewable energy in their national energy mix by 2030 through the support and incentives for solar energy harnessing. However, the observed solar data limitation may result in ineffective decision making, regarding solar farm locations. Therefore, the aim of this study is to utilise GIS-based multi criteria decision making (MCDM) and NASA POWER data to identify the optimal locations for solar farm installations, with the George Town Conurbation as a case study. Although NASA POWER is tailored for the application, at least, on the regional level, the information it provided on the solar radiation and the maximum and minimum temperatures are deemed useful for the initial solar mapping attempt at the local level, especially in the absence or lack of local data. The performance of the GIS-based MCDM model is categorized as good in identifying solar farms. There are no significant differences in the area under the curve (AUC) values between the map of the NASA POWER data and ground-measured data. This indicates the potential of using the NASA POWER data for generating the much-needed initial insights for the local optimal solar farm site selection. The stakeholders can benefit from the suitability map generated to effectively target the locations that have the highest potential to generate solar energy efficiently and sustainably.

Although the aquaculture industry contributes less than 0.2% to the Gross Domestic Product (GDP) of Malaysia, it has slowly become an important economic activity due to the high-value species productions for domestic and international markets. In addition, aquaculture can potentially be used as a sustainable solution for food security in the future. At present, the selection of aquaculture sites has not received much attention. Thus, this study aims to integrate a Geographic Information System and multi-criteria evaluation approach in identifying the potential sites for brackish aquaculture in the George Town Conurbation, Malaysia. ArcGIS 10.4 was used to perform site selection analysis together with the essential spatial data such as current land use, environmentally sensitive data, and soil quality that influence suitable sites selection for aquaculture. The selection was undertaken in ad hoc manners based on available land identified by aquaculture operators. The results indicated that the George Town Conurbation has a minimal potential site (0.37%) for aquaculture sites. This minimal number results from the expansion of built-up areas towards urban fringe areas; hence less land becomes available for aquaculture. A reasonable buffer zone should be designated as a boundary between urban development and aquaculture to avoid land-use conflict between these two activities.

Many new agricultural activities resulted in severe soil erosion across the Cameron Highlands’ land surface. Therefore, this study determines the cover (C) and land management (P) factors of the USLE for predicting soil loss risk in Cameron Highlands using a Geographic Information System (GIS). For this study, data from the Department of Agriculture Malaysia (DOAM) and the Department of Town and Country Planning Malaysia (PLANMalaysia) were used to generate several C&P factors in the Cameron Highlands. Data from both agencies have resulted in C factors with 0.01 to 1.00 and P factors with 0.30 to 0.49. Due to the cover and land management factor varies depending on the data collected by the various agencies, this study used the two data sets to come up with a C&P factor that accurately reflected both agricultural and urban growth effects. RKLS factors of USLE were obtained from the DOAM with values R (2375–2875), K (0.005), LS (2.5–25), respectively. The Cameron Highlands’ soil loss risk with these new C&P values resulted in a soil loss of 6.72 per cent (4547.22 hectares) from high to critical, with a percentage difference range of −0.77 to +3.37 under both agencies, respectively.

Urban growth, which caused spatial land use and land cover changes has affected various physical environment, social, and economic activities. Thus, in order to understand the dynamic process of urban spatial growth, researchers throughout the world have implemented diverse approaches, where spatial models have been developed to predict and simulate future urban growth. Those models were developed based on the driving forces that stimulate urban spatial growth. Therefore, in ensuring reliable models to be developed will be able to forecast future changes and their potential environmental effects, the driving forces must be identified. The objective of this paper is to identify possible driving forces that promote urban spatial growth of the George Town Conurbation. The study was conducted based on reviewing recent publications in journals and an on-line survey. An on-line survey was generated and distributed to academicians and urban planners to identify factors influencing urban spatial growth and their weights. The findings indicated that distance to public amenities, cheap housing price, and distance to the workplace are among factors that are important determinants of urban development. The results provide valuable insights in modelling urban growth in future research.