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Special Issue "Remote Sensing of Renewable Energy"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 30 November 2023 | Viewed by 3520

Special Issue Editors

Department of Mathematics, Natural and Economic Sciences, Ulm University of Applied Sciences, Ulm 89233, Germany
Interests: statistical data analytics; forecasting; renewable energy
Department of Geography, Kyungpook National University, Daegu 41566, Republic of Korea
Interests: cyber-physical system; remote sensing; geographic information system; designing of special information system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The energy sector is one of the key drivers of global warming as it contributes to large parts of worldwide greenhouse gas emissions. In order to reach the target of a sustainable economy, the sector needs to transform, especially by significantly increasing the share of renewable energies. However, energy sources such as wind and sunshine are highly stochastic. Both weather conditions and production outputs need to be surveyed closely in order to maintain grid stability. For this purpose, all kinds of sensors and other recording systems such as unmanned aerial vehicles (UAVs) are required. For example, UAVs are applied to monitor the current status of solar panels, sensors measure heat, electricity production, wind speed, etc. With the increasing significance of renewable energies techniques in this field have been developing quickly.

This Special Issue intends to provide an overview over the latest developments in the field of remote sensing on renewable energies. These might be novel/improved methods, techniques, or algorithms in the field of remote sensing. The objective is clear but the variety of methods is high. Therefore, articles may come from the fields of engineering, statistics, data science, economics, or mathematics, for example. Articles may address, but are not limited to, the following topics:

  • Advancements in error detection on solar panels or concentrated solar power mirrors.
  • Advancements in UAV-based solar panel monitoring.
  • Advances in the analysis of data (from sensors or satellites, for example).
  • Data analytics in general.
  • Technical advances in the field of remote sensing.
  • Sensor data-based forecasting of renewable energy.
  • Wind power remote sensing.
  • Solar power remote sensing.

Prof. Dr. Stephan Schlüter
Prof. Dr. Jung-Sup Um
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • UAVs
  • Pattern recognition
  • Greenhouse gases
  • Data analytics
  • Sensor technology
  • Wind and solar power

Published Papers (1 paper)

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An Empirical Correction Model for Remote Sensing Data of Global Horizontal Irradiance in High-Cloudiness-Index Locations
Remote Sens. 2022, 14(21), 5496; - 31 Oct 2022
Viewed by 3080
Facing the energy transition, solar energy, whether thermal or electric, is currently one of the most viable alternatives, due to its technological maturity and its ease of operation and maintenance compared to other renewable energies. However, before its implementation, it is necessary to [...] Read more.
Facing the energy transition, solar energy, whether thermal or electric, is currently one of the most viable alternatives, due to its technological maturity and its ease of operation and maintenance compared to other renewable energies. However, before its implementation, it is necessary to assess its potential. Remote sensing represents one of the low-cost solutions for solar energy assessment. Nevertheless, cloud cover is a main problem when validating the data. This study identifies satellite GHI profiles that cannot be used in energy production simulation. The validation is performed using parametric and non-parametric statistical tests. From the profile identified as invalid for simulation purposes, a site-adaptation methodology is proposed based on statistical learning using the machine learning algorithms “Best subset selection” and “Forward Stepwise Selection”. Linear and non-linear heuristic models are also proposed. The final AS7 model is selected through RMSE, MBE and adjusted R2 indicators and is valid for any sky condition. The results show an increase in R2 from 0.607 to 0.876. Full article
(This article belongs to the Special Issue Remote Sensing of Renewable Energy)
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