Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2018.05.010 |
Methodology for optimizing a photosynthetically active radiation monitoring network from satellite-derived estimations: A case study over mainland Spain | |
Vindel, J. M.; Valenzuela, R. X.; Navarro, A. A.; Zarzalejo, L. F. | |
2018-11-01 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2018 |
卷号 | 212页码:227-239 |
文章类型 | Article |
语种 | 英语 |
国家 | Spain |
英文摘要 | A methodology is presented for determining optimal locations to install photosynthetically active radiation (PAR) measurement stations. Initially, a cluster analysis was performed from PAR satellite-derived estimations over mainland Spain. Once the optimal number of clusters was obtained, the total number of locations included in the monitoring network was distributed among different groups, according to the size and variability of each group. Finally, the specific locations for measurement stations placement was determined using an iterative technique: The largest region within each cluster was split into two new sub-regions, providing two new sites for substituting the initial location. Clustering analysis has previously been applied to determine locations to monitor solar radiation. However, this is the first implementation for PAR stations in mainland Spain. Another novelty developed in this work is the distribution employed for specific sites within each cluster. The outcome achieved using clustering analysis was compared to those obtained using three other methods: two methods without clustering analysis and the third where clustering is performed but not optimizing the number of clusters. In one technique without clusters, the largest region is split into two new sub-regions, similar to the clustering analysis with optimization. In the second without clustering analysis, since the data variability was not previously addressed, the region divided is those with the largest combined effect of variance and size. The results fully justify using a clustering process; however, clustering without optimization is the worst performing method. |
英文关键词 | Photosynthetically active radiation Clustering analysis K-means algorithm |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000439403300019 |
WOS关键词 | GLOBAL SOLAR-RADIATION ; SPATIAL VARIABILITY ; SURFACE IRRADIANCE ; SKY CONDITIONS ; VALIDATION ; MODELS ; REGION ; ERRORS ; PAR ; UV |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/15253 |
专题 | 地球科学 |
作者单位 | CIEMAT, Renewable Energy Div, Ave Complutense 40, E-28040 Madrid, Spain |
推荐引用方式 GB/T 7714 | Vindel, J. M.,Valenzuela, R. X.,Navarro, A. A.,et al. Methodology for optimizing a photosynthetically active radiation monitoring network from satellite-derived estimations: A case study over mainland Spain[J]. ATMOSPHERIC RESEARCH,2018,212:227-239. |
APA | Vindel, J. M.,Valenzuela, R. X.,Navarro, A. A.,&Zarzalejo, L. F..(2018).Methodology for optimizing a photosynthetically active radiation monitoring network from satellite-derived estimations: A case study over mainland Spain.ATMOSPHERIC RESEARCH,212,227-239. |
MLA | Vindel, J. M.,et al."Methodology for optimizing a photosynthetically active radiation monitoring network from satellite-derived estimations: A case study over mainland Spain".ATMOSPHERIC RESEARCH 212(2018):227-239. |
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