# Editorial for the Special Issue: Assessment of Renewable Energy Resources with Remote Sensing
## 1 Aims and Goals  
The socio-economic development of a region or country is intrinsically associated with energy consumption. Continuous growth is expected in energy demand in countries with a robust emerging economy along the next decade to support enhancing the quality of life and essential services such as food, health, education, transportation, and entertainment. On the other hand, energy consumption is a remarkable contributor to the growing concentration of greenhouse gases (GHG) in the atmosphere due to the burning of fossil fuels, the energy source with the highest share. Concerns associated with climate change have been driving the development of increasingly efficient technologies to exploit renewable energy resources with low GHG emissions. However, technological developments in energy conversion are not a unique challenge that will support the expansion of renewable energy resources like solar energy, wind energy, hydroelectric energy, and wave energy. Reliable data on renewable energy resource assessment are also required and essential to ensure sustainable expansion considering environmental, financial, and energetic security. Renewable energy resources have an intrinsic relationship with local atmospheric conditions and the regional climate. Even small and fast changes in meteorological conditions can significantly affect power generation at different time and space scales. Methodologies based on the remote sensing of the atmosphere are the primary source of information for developing numerical models that aim to support an electric system's planning and operation with a substantial share of intermittent energy sources. Concerning solar energy, remote sensing technologies and methods become a fundamental tool to deal with the challenging task of solar resource assessment and forecasting in spatial and very short-time scales. The satellite-derived surface solar irradiance measurements are fundamental for high-resolution spatial solar resource assessment. A huge technological advance made satellite data possible at a horizontal resolution of around 500 m every 15 min during the last decade. Solar energyforecasting methodologies based on satellite data also became vital to support electricity system operation with increasing solar power share. Concerning short-term forecasting (or nowcasting), the total sky imagers become a crucial tool to investigate and deal with the high temporal local variability of the surface solar irradiance related to cloud conditions. Mature and commercially competitive technology for wind power generation is already available around the world. However, wind velocity is highly variable in time and space. The regional climate and local meteorological processes influence wind variability, demanding high-quality tools and methods based on remote sensing techniques for wind energy applications. The leading remote sensing techniques are LiDAR (wind LiDAR and ceilometers), radar, and satellites. Besides solar and wind energy, other renewable resources also require remote sensing technologies and methods to assess resource availability and variability. We can cite geothermal, hydro, and ocean energy resources, for instance. Time and spatial complementarity between renewable energy resources is getting more attention from academia and energy stakeholders to increase energy security and improve the energy quality delivered to the consumers. Here, we also have a great opportunity for remote sensing applications. Finally, remote sensing can help assess and plan the use of renewable resources to improve energy efficiency in buildings and cities based on observations of local environmental conditions. This Special Issue combines multidisciplinary contributions that address remote sensing aspects applied to the energy sector, from scientific fundamentals to practical energy industry needs.