The development of sustainable energy systems is very important to addressing the economic, environmental, and social pressures of the energy sector. Globally, buildings consume up to 40% of the world’s total energy. By 2030, it is expected to increase to 50%. Therefore, the world is facing a great challenge to overcome these problems related to global energy production. Malaysia is one of the top consumers of primary energy in Asia. In 2018, primary energy consumption for Malaysia was 3.79 quadrillion btu at an average annual rate of 4.58%. In this paper, we have carried out a detailed literature review on several previous studies of energy consumption in the world, especially in Malaysia, and how geographical information system (GIS) methods have been used for the spatial assessment of energy efficiency. Indeed, strategies of energy efficiency are essential in energy policy that could be created using various approaches used for energy savings in buildings. The findings of this review reveal that, for estimating energy consumption, exploring renewable energy sources, and investigating solar radiation, several geographic information system techniques such as multiple criteria decision analysis (MCDA), machine learning (ML), and deep learning (DL) are mainly utilized. The result indicates that the fuzzy DS method can more reliably determine the optimal PV farm locations. The 3D models are also regarded as an effective tool for estimating solar radiation, since this method generates a 3D model exportable to software tools. In addition, GIS and 3D can contribute to several purposes, such as sunlight access to buildings in urban areas, city growth prediction models and analysis of the habitability of public places.

Extraction of information from Remote sensing satellites is significant and effective tools for hazard activities such as flooding. essentially, if the field was under disaster conditions it will be so difficult to do surveying in that region. flash floods are sudden natural disaster events, which impact an extensive variety of ecological elements and applications associated with natural resources, agriculture, human activities and natural phenomena and economies. The utilization of SAR information gives much more information to control and monitor the flash floods, and additionally the information used for the damage assessment after the disasters. To recognize the region that has been flooded; a few procedures were trailed by Snap and Arc Map software. The fundamental step was flooded area in image its determined during extraction process by sets threshold estimation of radar backscatter which is taken from the calculation binary algorithm (the equitation of band math) to decide if a specified raster pixel is overflowed or not. The outcomes are indicated extend out of flash floods amid to time. On 26th of Mar Flood area was about 4.5%, however, it became around 45% in about month from the disaster beginning. This is evidence of the speed of the flood on the grounds that the nearness of high statures with Heavy rains around there and its foundation, on first of May agriculture damages, was around 1037 km2 as result appeared of this flash flood. Therefore, these outcomes are extremely helpful to make an evaluation of situations to save the people lives, property and nature from this natural disaster in the future.