ArticleScientific data2025
A high spatial resolution suitability layers to support feasible power plant site selection in China.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- A GIS-based fermatean fuzzy MCDM approach for identifying the optimal sites for solar power plant installation in Kermanshah Province.Scientific reports · 2025Article
- A high spatial resolution suitability layers to support feasible power plant site selection in China.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
China is undergoing significant energy system transitions to meet carbon neutrality targets, which requires the rapid deployment of new power plants, driven by the need for large-scale renewable energy expansion and increasing electricity demand. Moreover, the policy context emphasizes the critical need for effective local land planning and integrated ecological conservation. However, current capacity expansion planning models primarily focus on provincial or regional scales and overlook key location- and technology-specific factors for feasible power plant site selection. To effectively address these challenges, we use a transparent and comprehensive assessment framework that supports high-resolution spatial analysis of power generation technologies in mainland China, named Geospatial Raster Input Data for Capacity Expansion Regional Feasibility in China (GRIDCERF-China). It provides suitability layers for 7 technologies in GeoTIFF format that can be easily integrated with various modeling tools. GRIDCERF-China fills a significant open-source data gap, offering valuable insights for regional feasible planning and decision-making while addressing diverse scientific objectives across future scenarios.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.