globalchange  > 影响、适应和脆弱性
DOI: 10.1016/j.atmosres.2018.05.010
Scopus ID: 2-s2.0-85047828629
Methodology for optimizing a photosynthetically active radiation monitoring network from satellite-derived estimations: A case study over mainland Spain
Author: Vindel J.M.; Valenzuela R.X.; Navarro A.A.; Zarzalejo L.F.
Source Publication: Atmospheric Research
ISSN: 1698095
Publishing Year: 2018
Volume: 212
pages begin: 227
pages end: 239
Language: 英语
Keyword: Clustering analysis ; K-means algorithm ; Photosynthetically active radiation
Scopus Keyword: Clustering algorithms ; Iterative methods ; Location ; Nuclear reactors ; Clustering analysis ; Clustering process ; Iterative technique ; k-Means algorithm ; Monitoring network ; Number of clusters ; Optimal locations ; Photosynthetically active radiation ; Cluster analysis
English Abstract: 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. © 2018
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Document Type: 期刊论文
Appears in Collections:影响、适应和脆弱性

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Affiliation: Renewable Energy Division, CIEMAT, Av. Complutense, Madrid, 40 28040, Spain

Recommended Citation:
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,2018-01-01,212
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