Energy expansion and security in the current world scenario focuses on increasing the energy generation capacity and if possible, adopting cleaner and greener energy in that development process. However, too often this expansion and planning alters the landscape and human influence on its surroundings through a very complex mechanism. Resource extraction and land management activity involved in energy infrastructure development and human management of such development systems have long-term and sometimes unforeseen consequences. Although alternative energy sources are being explored, energy production is still highly dependent on fossil fuel, especially in most developing countries. Further, energy production can potentially affect land productivity, land cover, human migration, and other factors involved in running an energy production system, which presents a complex integration of these factors. Thus, land use, energy choices, infrastructure development and the population for which such facilities are being developed must be cognizant of each other, and the interactions between them need to be studied and understood closely. This study strives to analyze the implications of linkages between the energy industry, urbanization, and population and especially highlights processes that can be affected by their interaction. It is found that despite advancement in scientific tools, each of the three components, i.e., population growth, urbanization, and energy production, operates in silos, especially in developing countries, and that this complex issue of nexus is not dealt with in a comprehensive way.

Renewable energy has received noteworthy attention during the last few decades. This is partly due to the fact that fossil fuels are depleting and the need for energy is soaring because of the growing population of the world. This paper attempts to provide an idea of what is being done by researchers in remote sensing and geographical information system (GIS) field for exploring the renewable energy resources in order to get to a more sustainable future. Several studies related to renewable energy resources viz. geothermal energy, wind energy, hydropower, biomass, and solar energy, have been considered in this paper. The focus of this review paper is on exploring how remote sensing and GIS-based techniques have been beneficial in exploring optimal locations for renewable energy resources. Several case studies from different parts of the world which use such techniques in exploring renewable energy resource sites of different kinds have also been included in this paper. Though each of the remote sensing and GIS techniques used for exploration of renewable energy resources seems to efficiently sell itself in being the most effective among others, it is important to keep in mind that in actuality, a combination of different techniques is more efficient for the task. Throughout the paper, many issues relating to the use of remote sensing and GIS for renewable energy are examined from both current and future perspectives and potential solutions are suggested. The authors believe that the conclusions and recommendations drawn from the case studies and the literature reviewed in the present study will be valuable to renewable energy scientists and policymakers.

Remote sensing technology has seen a massive rise in popularity over the last two decades, becoming an integral part of our lives. Space-based satellite technologies facilitated access to the inaccessible terrains, helped humanitarian teams, support complex emergencies, and contributed to monitoring and verifying conflict zones. The scoping phase of this review investigated the utility of the role of remote sensing application to complement international peace and security activities owing to their ability to provide objective near real-time insights at the ground level. The first part of this review looks into the major research concepts and implementation of remote sensing-based techniques for international peace and security applications and presented a meta-analysis on how advanced sensor capabilities can support various aspects of peace and security. With key examples, we demonstrated how this technology assemblage enacts multiple versions of peace and security: for refugee relief operations, in armed conflicts monitoring, tracking acts of genocide, providing evidence in courts of law, and assessing contravention in human rights. The second part of this review anticipates future challenges that can hinder the applicative capabilities of remote sensing in peace and security. Varying types of sensors pose discrepancies in image classifications and issues like cost, resolution, and difficulty of ground-truth in conflict areas. With emerging technologies and sufficient secondary resources available, remote sensing plays a vital operational tool in conflict-affected areas by supporting an extensive diversity in public policy actions for peacekeeping processes.

Spatiotemporal fusion (STF) techniques play important roles in Earth observation analysis as they can produce images with both high spatial and temporal resolution. However, existing STF models often fuse images from various satellites, not satisfying the demand for precise crop monitoring. In contrast, unmanned aerial vehicle (UAV) images can deliver detailed data, and deep learning (DL)-based STF models have a high potential for automatically extracting abstract features. To this end, this study proposed a novel end-to-end DL-based STF model named UAV-Net, which can produce centimeter-scale UAV images. UAV-Net has an encoder-decoder architecture with Modified ResNet (MResNet), Feature Pyramid Network (FPN), and decoder modules. The encoder uses MResNet modules to extract input features, while the FPN module performs a multiscale fusion of these features before reconstructing UAV images using transposed convolution in the decoder module. Through the comparison and ablation experiments, this study evaluated the efficacies of the MResNet modules with 18, 34, and 50 layers, along with FPN module of UAV-Net. The experimental results on real-world datasets demonstrated that UAV-Net adequately produce UAV images both visually and quantitatively. Furthermore, Comparison with state-of-the-art STF models highlights the innovative and effective of UAV-Net for producing centimeter-scale images. The predicted centimeter-scale images have the potential to be useful for various environmental monitoring applications.