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.

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.

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Creating environmentally friendly energy schemes that are sustainable is critical as a solution to the economic, ecological, and societal influences related to the energy sector. It should be noted that buildings utilize up to forty percent of global energy consumption. Furthermore, by 2030, it is anticipated to reach fifty percent. As a result, the world faces a significant dilemma in overcoming such worldwide energy generation issues. Concerning primary energy consumption, Malaysia is among Asia’s largest consumers. Malaysia’s immediate energy use in 2018 was 3.79 quadrillion Btu, growing at a 4.58% annualized rate. This article thoroughly reviewed past studies of global energy usage, particularly in Malaysia, and how the geographical information system (GIS) methodologies were employed for spatial evaluation of energy efficacy. Undoubtedly, effective energy strategies are critical in energy policy, and they can be developed through the application of a variety of methods for energy conservation in building structures. The findings of this study indicate that some GIS methods, such as machine learning, deep learning and multiple criteria decision analysis, are mainly employed for calculating energy consumption, researching renewable energy sources, and analyzing solar radiation. The results also show that the fuzzy_AHP and fuzzy_DS techniques have a higher capability and reliability in identifying the most suitable sites for photovoltaic (PV) farms. Due to the generation of a 3D model exportable to software tools through this technique, the 3D models are deemed efficient for calculating solar radiation. Furthermore, GIS and 3D can assist with various tasks, including access to sunlight in built structures and environments in urban areas, urban growth prediction models, and the habitability of public spaces analysis.