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Remote Sensing for Solar Radiation Applications

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

Deadline for manuscript submissions: 15 June 2024 | Viewed by 624

Special Issue Editor


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Guest Editor
Department of Chemistry and Physics, University of Almería, 04120 Almeria, Spain
Interests: solar irradiance forecasting; cloud forecasting; CSP plants; PV plants; atmospheric extinction; sky cameras; satellite images; remote sensing; artificial neural networks; image processing; cloud detection; solar irradiance estimation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Surface solar radiation is a key part dictating the radiation–energy balance, surface‒atmosphere interactions, the water cycle, meteorological and climatic conditions, and land surface processes.

It is the primary energy source that drives many of Earth's physical and biological processes.

Accurate information about solar radiation is needed in many fields. Understanding its importance to the landscape at a variety of scales is key to understanding a broad range of natural processes and human activities. Additionally, solar radiation measurements are necessary for the assessment of potential solar energy resources.

To gain information on Solar Radiation, remote sensing techniques provide an important means to determine the spatial distribution of solar radiation and forecasting of solar irradiance. Especially, satellites offer information about atmospheric states, which can be further explored for better accuracy.

Therefore, the Special Issue aims to review remote sensing techniques (new or updated satellite products, on-board instruments, and retrieval techniques) for solar radiation measurements and modeling. The use of machine learning and deep learning with remote sensing data for understanding solar radiation observations and generating more useful data is also welcome.

Prof. Dr. Joaquín Alonso-Montesinos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com 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.

Keywords

  • solar radiation
  • PV systems
  • solar energy
  • remote sensing
  • radiation budget
  • satellite
  • surface albedo
  • global irradiance

Published Papers (1 paper)

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Research

21 pages, 16174 KiB  
Article
Surface Solar Radiation Resource Evaluation of Xizang Region Based on Station Observation and High-Resolution Satellite Dataset
by Huangjie Kong, Jianguo Wang, Li Cai, Jinxin Cao, Mi Zhou and Yadong Fan
Remote Sens. 2024, 16(8), 1405; https://0-doi-org.brum.beds.ac.uk/10.3390/rs16081405 - 16 Apr 2024
Viewed by 402
Abstract
Xizang boasts a vast and geographically complex landscape with an average elevation surpassing 4000 m. Understanding the spatiotemporal distribution of surface solar radiation is indispensable for simulating surface processes, studying climate change, and designing photovoltaic power generation and solar heating systems. A multi-dimensional, [...] Read more.
Xizang boasts a vast and geographically complex landscape with an average elevation surpassing 4000 m. Understanding the spatiotemporal distribution of surface solar radiation is indispensable for simulating surface processes, studying climate change, and designing photovoltaic power generation and solar heating systems. A multi-dimensional, long-term, spatial, and temporal investigation of solar radiation in Xizang was conducted using three unique datasets, including the difference in surface solar radiation (SSR) between high-resolution satellite and ground station data, the annual and monthly distribution of SSR, and the interannual–monthly–daily variation and the coefficient of hourly variability. Combined with high-resolution elevation data, a strong linear correlation was shown between the radiation and the elevation below 4000 m. Furthermore, analysis reveals greater differences in data between east and west compared to the center, as well as between summer and winter seasons. SSR levels vary in steps, reaching the highest from Ngari to Shigatse and the lowest in a U-shaped area formed by southeastern Shannan and southern Nyingchi. In June, high monthly SSR coverage was the highest of the year. Since 1960, the annual mean SSR has generally exhibited a declining trend, displaying distinctive trends across various seasons and datasets. Owing to intricate meteorological factors, some regions exhibited double peaks in monthly SSR. Finally, we have introduced a solar resource assessment standard, along with a multidimensional evaluation of the resources, and categorized all townships. We offer a thorough analysis of Xizang’s solar radiation to provide a comprehensive understanding, which will help to prioritize recommendations for PV construction in Xizang. Full article
(This article belongs to the Special Issue Remote Sensing for Solar Radiation Applications)
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