# Editorial for the Special Issue: Assessment of Renewable Energy Resources with Remote Sensing
## 3 Brief Discussion of the Published Articles in the Special Issue  
Energy demand is intrinsically associated with population growth, the demographic concentration in urban areas, and socio-economic development, including human well-being with its aspects related to health, education, culture, and entertainment. The Sustainable Development Goals, specifically \"SDG-7--Providing clean and accessible energy to the world population\" and \"SDG-13--Action against global climate change\" [12], reinforce the relevance of the Special Issue. [PERSON] et al. [13] pointed out that 69% of greenhouse gas (GHG) emissions in the world are due to the burning of \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Research Article** & **Energy Resource** & **Remote Sensing Data and Methods** & **Study Area** \\ \hline [PERSON] et al. [1] & PV power & Improved variant of the whale optimization algorithm based on the parameters of PV modules & Guiyang, China \\ \hline [PERSON] et al. [2] & Solar energy & MLRegression, PolRegression, and neural networks based on DNlobservations and all-sky images & SIO in Mexico City \\ \hline [PERSON] et al. [3] & Wind energy & Two-parameter velocity volume processing (VVP) method based on LiDAR measurements & HORS in Japan \\ \hline [PERSON] [4] & Solar energy & Cloud identification using threshold criteria applied to all-sky images & CIESOL in Spain \\ \hline [PERSON] et al. [5] & Geothermal energy & Time domain electromagnetic method and electrical resistivity tomography & Central Spain \\ \hline [PERSON] et al. [6] & PV power & Multistep-ahead (MSA) forecasting using meteorological data and historical global solar radiation data & Jeju Island in Korea \\ \hline [PERSON] et al. [7] & Solar energy & SOLENapproach based on 3D terrestrial laser scanning datasets & Citarip, Indonesia \\ \hline [PERSON] et al. [8] & Solar energy & modeling approaches using the GOES-16 visible imagery, ISCCPatabase products, and meteorological ground observations & Central Brazil \\ \hline [PERSON] et al. [9] & Wind energy & The global basin-scale and near-coastal wind using a calibrated multi-mission scatterometer dataset & Global coverage \\ \hline [PERSON] et al. [10] & PV power & Machine learning algorithms based on open-source meteorological data and PV system parameters & Astrahan, Russia \\ \hline [PERSON] et al. [11] & Solar energy & Statistical analysis of climate data from two satellite, CLARA-A2 and SARAH-2 and ground-based pyranometer measurements & Baltic Region \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary list of remote sensing data, methods, and study regions discussed in the eleven articles included in the Special Issue (sorted by the publication date). fossil fuels. [PERSON] et al. [14] mentioned data pointing to an increase in emissions linked to fossil fuel consumption between 2017 and 2019 of around 1.3% per year. Recent data indicate that about one billion people do not have access to electricity, and more than two billion use solid biomass as stove fuel [15]. The numbers presented above indicate that the energy mix expansion needs a comprehensive approach when considering the socio-environmental issue. Currently, around 81% of the world's primary energy comes from fossil fuels, 25% of which is consumed as electricity, leading to average emissions of 515 g CO2/kWh. These aspects reinforce the need to make progress in the efficient use of energy resources combined with the decarbonization of the world energy matrix. Recent data show that more plants for renewable energy sources such as solar, wind, hydroelectric, and geothermal were installed than thermopower plants based on fossil and nuclear fuels since 2015 [16]. Solar and wind resources present high variability intrinsically linked to the environmental and meteorological conditions, and this can significantly affect the quality and safety of the electrical system.